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Sample records for forest mapping debuting

  1. The Risks and Rewards of Sexual Debut

    Science.gov (United States)

    Golden, Rachel Lynn; Furman, Wyndol; Collibee, Charlene

    2016-01-01

    The sex-positive framework of sexual development hypothesizes that healthy sexual experiences can be developmentally appropriate and rewarding for adolescents despite the risks involved. Research has not examined whether risky behaviors and rewarding cognitions actually change with sexual debut at a normative or late age. This study measured the longitudinal impact of sexual debut using 7 waves of data from 88 male and 86 female adolescents from a Western U.S. city who were in the 10th grade at the study’s onset. We used piecewise growth curve analyses to compare behavior and cognitions before and after first sexual intercourse for those whose debut was at a normative or late age. These analyses revealed that sexual debut was related to rewards including increases in romantic appeal, and sexual satisfaction. In addition, internalizing symptoms declined over time after sexual debut, and substance use grew at a slower rate after sexual debut. We also examined whether differences existed among those whose debut was at an early, normative, or late age. Linear growth curve analyses revealed early sexual debut was related to risks, such as greater substance use, more internalizing and externalizing symptoms and lower global self-worth. Rewards associated with an early debut included greater romantic appeal, dating satisfaction (males only), and sexual satisfaction (males only). Although there are some inherent risks with sexual activity, the results suggest that sexual debut at a normative or late age is also associated with a decrease in some risks and increase in rewards. PMID:27709996

  2. Casual sex-debuts among female adolescents in Addis Ababa ...

    African Journals Online (AJOL)

    Background: In the era of HIV/AIDS epidemic understanding the nature of sexual debuts among female adolescents is critical in developing effective preventive strategies. Objectives: The objectives of the study where to investigate the specific age at sex-debuts, to identify the specific reasons for sex-debuts, and to examine ...

  3. Parenting Style and the Timing of Jewish Adolescents’ Sexual Debut

    Directory of Open Access Journals (Sweden)

    Robby Etzkin

    2010-06-01

    Full Text Available Parenting style and its effect on the timing of Jewish adolescents’ sexual debuts were examined in the reported study. One hundred sixty-eight research participants between the ages of 18 and 22 from a large university in the Southeast participated in the study. A survey instrument was administered at three fraternities and two sororities to examine parenting style and sexual debut retrospectively. Data were analyzed using descriptive statistics, frequency chi square tests, and Analysis of Variance (ANOVA; while post hoc results were determined through Tukey’s honestly significant difference. Results found that authoritative parenting provides a delay in the age of sexual debut for Jewish adolescents. All other parenting styles had mean ages less than the overall mean age of sexual debut, 17.10 years old, with indifferent parenting having the earliest debut. These findings suggest that parenting style may affect the timing of Jewish adolescents’ sexual debut. The study has implications for understanding factors that may affect the timing of a Jewish adolescent’s sexual debut and may help parents protect their adolescent from the negative effects associated with early sexual debut, such as low academic achievement. Recommendations for future research include exploring the effects of family structure and peer networks to understand fully the many factors that affect the timing of adolescents’ sexual debut.

  4. Sexual Debut and Mental Health Among South Korean Adolescents.

    Science.gov (United States)

    Kim, Hyun Sik

    2016-01-01

    Numerous studies have demonstrated the negative influence of sexual debut during adolescence on mental health outcomes. This article contributes to this literature by investigating whether sexual debut has negative effects on mental health among South Korean adolescents and whether the timing of adolescent sexual debut matters. Drawing on longitudinal data from a nationally representative survey, we first predicted mental health outcomes at one year after high school graduation using first sexual intercourse that had occurred before the outcomes were measured. In a second statistical model, adolescent sexual debut was defined as first coitus that had occurred before high school graduation. Sexual debut was associated with an increase in problematic aggressive behaviors for both genders. In contrast, only girls experienced a rise in depressive symptoms after becoming sexually active. For girls, having sex before high school graduation was correlated with worse mental health outcomes to the extent that sexual debut even enhanced the risk of suicidal ideation. We concluded that the negative effects of sexual activity among South Korean adolescents are attributable mainly to the sexually conservative atmosphere and gendered sexuality in that country.

  5. Mapping Forest Inventory and Analysis forest land use: timberland, reserved forest land, and other forest land

    Science.gov (United States)

    Mark D. Nelson; John Vissage

    2007-01-01

    The Forest Inventory and Analysis (FIA) program produces area estimates of forest land use within three subcategories: timberland, reserved forest land, and other forest land. Mapping these subcategories of forest land requires the ability to spatially distinguish productive from unproductive land, and reserved from nonreserved land. FIA field data were spatially...

  6. Application of mapped plots for single-owner forest surveys

    Science.gov (United States)

    Paul C. Van Deusen; Francis Roesch

    2009-01-01

    Mapped plots are used for the nation forest inventory conducted by the U.S. Forest Service. Mapped plots are also useful foro single ownership inventoires. Mapped plots can handle boundary overlap and can aprovide less variable estimates for specified forest conditions. Mapping is a good fit for fixed plot inventories where the fixed area plot is used for both mapping...

  7. Cognitive representations of sexual self differ as a function of gender and sexual debut.

    Science.gov (United States)

    Lindgren, Kristen P; Schacht, Rebecca L; Mullins, Peter M; Blayney, Jessica A

    2011-02-01

    This research evaluated the association between gender and sexual debut (initial sexual intercourse) and indirect measures of sexuality. A sample of 440 U.S. college students (pre-sexual debut: 144 women, 153 men; post-sexual debut: 49 women, 94 men) completed the Sexual Self-Schema Scale (SSSS), which assessed cognitive representations about sexual aspects of oneself, and three Implicit Association Tests (IAT), which measured the strength of the associations between the concepts of self + sex, women + sex, and men + sex. Results replicated previous findings that (1) men more strongly associated self + sex and women + sex than did women, and (2) men and women had similarly strong associations of men + sex. Post-sexual debut women's self + sexual and women + sexual associations were stronger than pre-sexual debut women's. Men's associations did not differ significantly as a function of sexual debut. Post-sexual debut women's SSSS scores were more direct, more romantic, and less conservative than pre-sexual debut women's. Post-sexual debut men's SSSS scores were more aggressive and more open-minded than pre-sexual debut men's. Sexual debut appeared to be associated with sexualized and sexually liberal cognitive representations in women and, to a lesser extent, sexually liberal and aggressive cognitive representations in men. Findings were consistent with theories of cognitive consistency and provide preliminary evidence that sexual debut status was associated with differing cognitive representations.

  8. Forest fire risk zonation mapping using remote sensing technology

    Science.gov (United States)

    Chandra, Sunil; Arora, M. K.

    2006-12-01

    Forest fires cause major losses to forest cover and disturb the ecological balance in our region. Rise in temperature during summer season causing increased dryness, increased activity of human beings in the forest areas, and the type of forest cover in the Garhwal Himalayas are some of the reasons that lead to forest fires. Therefore, generation of forest fire risk maps becomes necessary so that preventive measures can be taken at appropriate time. These risk maps shall indicate the zonation of the areas which are in very high, high, medium and low risk zones with regard to forest fire in the region. In this paper, an attempt has been made to generate the forest fire risk maps based on remote sensing data and other geographical variables responsible for the occurrence of fire. These include altitude, temperature and soil variations. Key thematic data layers pertaining to these variables have been generated using various techniques. A rule-based approach has been used and implemented in GIS environment to estimate fuel load and fuel index leading to the derivation of fire risk zonation index and subsequently to fire risk zonation maps. The fire risk maps thus generated have been validated on the ground for forest types as well as for forest fire risk areas. These maps would help the state forest departments in prioritizing their strategy for combating forest fires particularly during the fire seasons.

  9. 75 FR 16719 - Information Collection; Forest Landscape Value and Special Place Mapping for National Forest...

    Science.gov (United States)

    2010-04-02

    ... Collection; Forest Landscape Value and Special Place Mapping for National Forest Planning AGENCY: Forest... on the new information collection, Forest Landscape Value and Special Place Mapping for National Forest Planning. DATES: Comments must be received in writing on or before June 1, 2010 to be assured of...

  10. Sexual debut in Mexico: a comparison of household national surveys.

    Directory of Open Access Journals (Sweden)

    Cecilia Gayet

    2014-11-01

    Full Text Available Objective. To estimate calendar of sexual debut in Mexico and its trends using national representative household surveys. Materials and methods. Analysis of five birth cohorts extracted from four national population based household surveys in Mexico (National Health Survey 2000, National Survey on Demographic Dynamics 2009, National Youth Survey 2010, and National Health and Nutrition Survey 2012, using as outcome the proportion of individuals that reported sexual debut before the age of 16 and before the age of 20. Results. Overall, the four analyzed surveys produce consistent results, although some differences were found. While a larger proportion among younger cohorts reported sexual debut before the age of 20, that was not the case for sexual debut before 16 years. Conclusions. While data seems to reflect a relative stable age of sexual debut in Mexico, there is a recent trend to prepone sexual initiation that highlights the need to strengthen comprehensive sexual education and the supply of sexual and reproductive health services that are accessible and friendly to adolescents thus responding to the growing demand from this age group.

  11. Early sexual debut and condom nonuse among adolescents in South Korea.

    Science.gov (United States)

    Kim, Jiyun; Lee, Jong-Eun

    2012-11-01

    The purpose of this study was to investigate the factors related to sexual debut among adolescents, and to examine the association between subject characteristics and condom nonuse among those who experienced sexual intercourse in South Korea. Data were obtained from the 2009 Korean Youth Risk Behaviour Survey, a nationally representative sample. Logistic regression analysis was conducted to investigate the factors related to sexual debut, associations of condom nonuse and subject characteristics. Among male adolescents, age, early age at first emission, low academic achievement, living with a step-parent, perceived low level of household income, frequent drinking and smoking, and depressive feelings were associated with early sexual debut. Attending a coeducational school, living with a single biological parent and step-parent, risky health behaviour such as drinking and smoking, and depressive feelings were related risks factors for early sexual debut among female students. Factors associated with condom nonuse included early sexual debut (less than 16 years of age) (odds ratio (OR)=1.79, 95% confidence interval (CI)=1.32-2.43) and frequent smoking behaviour (OR=1.49, 95% CI=1.08-2.05) for males and early sexual debut (OR=4.37, 95% CI=1.02-18.68) and frequent drinking (OR=2.05, 95% CI=1.12-3.75) for females. Appropriate interventions should be implemented for adolescents in Korea to delay sexual debut and educate them on the proper use of condoms.

  12. Detailed maps of tropical forest types are within reach: forest tree communities for Trinidad and Tobago mapped with multiseason Landsat and multiseason fine-resolution imagery

    Science.gov (United States)

    Eileen H. Helmer; Thomas S. Ruzycki; Jay Benner; Shannon M. Voggesser; Barbara P. Scobie; Courtenay Park; David W. Fanning; Seepersad. Ramnarine

    2012-01-01

    Tropical forest managers need detailed maps of forest types for REDD+, but spectral similarity among forest types; cloud and scan-line gaps; and scarce vegetation ground plots make producing such maps with satellite imagery difficult. How can managers map tropical forest tree communities with satellite imagery given these challenges? Here we describe a case study of...

  13. Mapping the World's Intact Forest Landscapes by Remote Sensing

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    Peter Potapov

    2008-12-01

    Full Text Available Protection of large natural forest landscapes is a highly important task to help fulfill different international strategic initiatives to protect forest biodiversity, to reduce carbon emissions from deforestation and forest degradation, and to stimulate sustainable forest management practices. This paper introduces a new approach for mapping large intact forest landscapes (IFL, defined as an unbroken expanse of natural ecosystems within areas of current forest extent, without signs of significant human activity, and having an area of at least 500 km2. We have created a global IFL map using existing fine-scale maps and a global coverage of high spatial resolution satellite imagery. We estimate the global area of IFL within the current extent of forest ecosystems (forest zone to be 13.1 million km2 or 23.5% of the forest zone. The vast majority of IFL are found in two biomes: Dense Tropical and Subtropical Forests (45.3% and Boreal Forests (43.8%. The lowest proportion of IFL is found in Temperate Broadleaf and Mixed Forests. The IFL exist in 66 of the 149 countries that together make up the forest zone. Three of them - Canada, Russia, and Brazil - contain 63.8% of the total IFL area. Of the world's IFL area, 18.9% has some form of protection, but only 9.7% is strictly protected, i.e., belongs to IUCN protected areas categories I-III. The world IFL map presented here is intended to underpin the development of a general strategy for nature conservation at the global and regional scales. It also defines a baseline for monitoring deforestation and forest degradation that is well suited for use with operational and cost-effective satellite data. All project results and IFL maps are available on a dedicated web site (http://www.intactforests.org.

  14. Choice of forest map has implications for policy analysis

    DEFF Research Database (Denmark)

    Seebach, Lucia Maria; McCallum, Ian; Fritz, Steffen

    2012-01-01

    /non-forest map (FMAP), the Corine Land Cover (CLC), the Calibrated European Forest Map (CEFM) and the Global Land Cover (GLC). Finally, the impact of potential differences owing to input datasets on decision-making was tested in a selected case study: reaching the EU 10% biofuel target through enhanced....... Similarly, depending on the choice of the input alternate options for decision-making were found within the hypothesized biofuel target (case study), demonstrating a substantial value of information. In general, it was demonstrated that input maps are the major driver of decision-making if forest resource...... outputs of the model are their basis. Improvement of the input forest map would result in immediate benefit for a better decision-making basis....

  15. Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data

    Directory of Open Access Journals (Sweden)

    Tianyu Hu

    2016-07-01

    Full Text Available As a large carbon pool, global forest ecosystems are a critical component of the global carbon cycle. Accurate estimations of global forest aboveground biomass (AGB can improve the understanding of global carbon dynamics and help to quantify anthropogenic carbon emissions. Light detection and ranging (LiDAR techniques have been proven that can accurately capture both horizontal and vertical forest structures and increase the accuracy of forest AGB estimation. In this study, we mapped the global forest AGB density at a 1-km resolution through the integration of ground inventory data, optical imagery, Geoscience Laser Altimeter System/Ice, Cloud, and Land Elevation Satellite data, climate surfaces, and topographic data. Over 4000 ground inventory records were collected from published literatures to train the forest AGB estimation model and validate the resulting global forest AGB product. Our wall-to-wall global forest AGB map showed that the global forest AGB density was 210.09 Mg/ha on average, with a standard deviation of 109.31 Mg/ha. At the continental level, Africa (333.34 ± 63.80 Mg/ha and South America (301.68 ± 67.43 Mg/ha had higher AGB density. The AGB density in Asia, North America and Europe were 172.28 ± 94.75, 166.48 ± 84.97, and 132.97 ± 50.70 Mg/ha, respectively. The wall-to-wall forest AGB map was evaluated at plot level using independent plot measurements. The adjusted coefficient of determination (R2 and root-mean-square error (RMSE between our predicted results and the validation plots were 0.56 and 87.53 Mg/ha, respectively. At the ecological zone level, the R2 and RMSE between our map and Intergovernmental Panel on Climate Change suggested values were 0.56 and 101.21 Mg/ha, respectively. Moreover, a comprehensive comparison was also conducted between our forest AGB map and other published regional AGB products. Overall, our forest AGB map showed good agreements with these regional AGB products, but some of the regional

  16. Simultaneous comparison and assessment of eight remotely sensed maps of Philippine forests

    Science.gov (United States)

    Estoque, Ronald C.; Pontius, Robert G.; Murayama, Yuji; Hou, Hao; Thapa, Rajesh B.; Lasco, Rodel D.; Villar, Merlito A.

    2018-05-01

    This article compares and assesses eight remotely sensed maps of Philippine forest cover in the year 2010. We examined eight Forest versus Non-Forest maps reclassified from eight land cover products: the Philippine Land Cover, the Climate Change Initiative (CCI) Land Cover, the Landsat Vegetation Continuous Fields (VCF), the MODIS VCF, the MODIS Land Cover Type product (MCD12Q1), the Global Tree Canopy Cover, the ALOS-PALSAR Forest/Non-Forest Map, and the GlobeLand30. The reference data consisted of 9852 randomly distributed sample points interpreted from Google Earth. We created methods to assess the maps and their combinations. Results show that the percentage of the Philippines covered by forest ranges among the maps from a low of 23% for the Philippine Land Cover to a high of 67% for GlobeLand30. Landsat VCF estimates 36% forest cover, which is closest to the 37% estimate based on the reference data. The eight maps plus the reference data agree unanimously on 30% of the sample points, of which 11% are attributable to forest and 19% to non-forest. The overall disagreement between the reference data and Philippine Land Cover is 21%, which is the least among the eight Forest versus Non-Forest maps. About half of the 9852 points have a nested structure such that the forest in a given dataset is a subset of the forest in the datasets that have more forest than the given dataset. The variation among the maps regarding forest quantity and allocation relates to the combined effects of the various definitions of forest and classification errors. Scientists and policy makers must consider these insights when producing future forest cover maps and when establishing benchmarks for forest cover monitoring.

  17. Mapping Forest Biomass Using Remote Sensing and National Forest Inventory in China

    Directory of Open Access Journals (Sweden)

    Ling Du

    2014-06-01

    Full Text Available Quantifying the spatial pattern of large-scale forest biomass can provide a general picture of the carbon stocks within a region and is of great scientific and political importance. The combination of the advantages of remote sensing data and field survey data can reduce uncertainty as well as demonstrate the spatial distribution of forest biomass. In this study, the seventh national forest inventory statistics (for the period 2004–2008 and the spatially explicit MODIS Land Cover Type product (MCD12C1 were used together to quantitatively estimate the spatially-explicit distribution of forest biomass in China (with a resolution of 0.05°, ~5600 m. Our study demonstrated that the calibrated forest cover proportion maps allow proportionate downscaling of regional forest biomass statistics to forest cover pixels to produce a relatively fine-resolution biomass map. The total stock of forest biomass in China was 11.9 Pg with an average of 76.3 Mg ha−1 during the study period; the high values were located in mountain ranges in northeast, southwest and southeast China and were strongly correlated with forest age and forest density.

  18. Mapping Russian forest biomass with data from satellites and forest inventories

    International Nuclear Information System (INIS)

    Houghton, R A; Butman, D; Bunn, A G; Krankina, O N; Schlesinger, P; Stone, T A

    2007-01-01

    The forests of Russia cover a larger area and hold more carbon than the forests of any other nation and thus have the potential for a major role in global warming. Despite a systematic inventory of these forests, however, estimates of total carbon stocks vary, and spatial variations in the stocks within large aggregated units of land are unknown, thus hampering measurement of sources and sinks of carbon. We mapped the distribution of living forest biomass for the year 2000 by developing a relationship between ground measurements of wood volume at 12 sites throughout the Russian Federation and data from the MODIS satellite bidirectional reflectance distribution function (BRDF) product (MOD43B4). Based on the results of regression-tree analyses, we used the MOD43B4 product to assign biomass values to individual 500 m x 500 m cells in areas identified as forest by two satellite-based maps of land cover. According to the analysis, the total living biomass varied between 46 and 67 Pg, largely because of different estimates of forest area. Although optical data are limited in distinguishing differences in biomass in closed canopy forests, the estimates of total living biomass obtained here varied more in response to different definitions of forest than to saturation of the optical sensing of biomass

  19. Mapping Russian forest biomass with data from satellites and forest inventories

    Energy Technology Data Exchange (ETDEWEB)

    Houghton, R A [Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540 (United States); Butman, D [Yale School of Forestry and Environmental Science, Yale University, New Haven, CT 06511 (United States); Bunn, A G [Department of Environmental Sciences, Huxley College of the Environment, Western Washington University, 516 High Street, Bellingham, WA 98225-9181 (United States); Krankina, O N [Department of Forest Science, Oregon State University, 202 Richardson Hall, Corvallis, OR 97331-5752 (United States); Schlesinger, P [Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540 (United States); Stone, T A [Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540 (United States)

    2007-10-15

    The forests of Russia cover a larger area and hold more carbon than the forests of any other nation and thus have the potential for a major role in global warming. Despite a systematic inventory of these forests, however, estimates of total carbon stocks vary, and spatial variations in the stocks within large aggregated units of land are unknown, thus hampering measurement of sources and sinks of carbon. We mapped the distribution of living forest biomass for the year 2000 by developing a relationship between ground measurements of wood volume at 12 sites throughout the Russian Federation and data from the MODIS satellite bidirectional reflectance distribution function (BRDF) product (MOD43B4). Based on the results of regression-tree analyses, we used the MOD43B4 product to assign biomass values to individual 500 m x 500 m cells in areas identified as forest by two satellite-based maps of land cover. According to the analysis, the total living biomass varied between 46 and 67 Pg, largely because of different estimates of forest area. Although optical data are limited in distinguishing differences in biomass in closed canopy forests, the estimates of total living biomass obtained here varied more in response to different definitions of forest than to saturation of the optical sensing of biomass.

  20. Urban forest topographical mapping using UAV LIDAR

    Science.gov (United States)

    Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi

    2017-12-01

    Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

  1. Assessment and Mapping of Forest Parcel Sizes

    Science.gov (United States)

    Brett J. Butler; Susan L. King

    2005-01-01

    A method for analyzing and mapping forest parcel sizes in the Northeastern United States is presented. A decision tree model was created that predicts forest parcel size from spatially explicit predictor variables: population density, State, percentage forest land cover, and road density. The model correctly predicted parcel size for 60 percent of the observations in a...

  2. Mapping the Distribution of Cloud Forests Using MODIS Imagery

    Science.gov (United States)

    Douglas, M. W.; Mejia, J.; Murillo, J.; Orozco, R.

    2007-05-01

    Tropical cloud forests - those forests that are frequently immersed in clouds or otherwise very humid, are extremely difficult to map from the ground, and are not easily distinguished in satellite imagery from other forest types, but they have a very different flora and fauna than lowland rainforest. Cloud forests, although found in many parts of the tropics, have a very restricted vertical extent and thus are also restricted horizontally. As a result, they are subject to both human disturbance (coffee growing for example) and the effects of possible climate change. Motivated by a desire to seek meteorological explanations for the distribution of cloud forests, we have begun to map cloudiness using MODIS Terra and Aqua visible imagery. This imagery, at ~1030 LT and 1330 LT, is an approximation for mid-day cloudiness. In tropical regions the amount of mid-day cloudiness strongly controls the shortwave radiation and thus the potential for evaporation (and aridity). We have mapped cloudiness using a simple algorithm that distinguishes between the cloud-free background brightness and the generally more reflective clouds to separate clouds from the underlying background. A major advantage of MODIS imagery over many other sources of satellite imagery is its high spatial resolution (~250m). This, coupled with precisely navigated images, means that detailed maps of cloudiness can be produced. The cloudiness maps can then be related to the underlying topography to further refine the location of the cloud forests. An advantage of this technique is that we are mapping the potential cloud forest, based on cloudiness, rather than the actual cloud forest, which are commonly based on forest estimates from satellite and digital elevation data. We do not derive precipitation, only estimates of daytime cloudiness. Although only a few years of MODIS imagery has been used in our studies, we will show that this is sufficient to describe the climatology of cloudiness with acceptable

  3. Tropical forest carbon assessment: integrating satellite and airborne mapping approaches

    International Nuclear Information System (INIS)

    Asner, Gregory P

    2009-01-01

    Large-scale carbon mapping is needed to support the UNFCCC program to reduce deforestation and forest degradation (REDD). Managers of forested land can potentially increase their carbon credits via detailed monitoring of forest cover, loss and gain (hectares), and periodic estimates of changes in forest carbon density (tons ha -1 ). Satellites provide an opportunity to monitor changes in forest carbon caused by deforestation and degradation, but only after initial carbon densities have been assessed. New airborne approaches, especially light detection and ranging (LiDAR), provide a means to estimate forest carbon density over large areas, which greatly assists in the development of practical baselines. Here I present an integrated satellite-airborne mapping approach that supports high-resolution carbon stock assessment and monitoring in tropical forest regions. The approach yields a spatially resolved, regional state-of-the-forest carbon baseline, followed by high-resolution monitoring of forest cover and disturbance to estimate carbon emissions. Rapid advances and decreasing costs in the satellite and airborne mapping sectors are already making high-resolution carbon stock and emissions assessments viable anywhere in the world.

  4. Mapping of forest disturbance magnitudes across the US National Forest System

    Science.gov (United States)

    Hernandez, A. J.; Healey, S. P.; Ramsey, R. D.; McGinty, C.; Garrard, C.; Lu, N.; Huang, C.

    2013-12-01

    A precise record in conjunction with ongoing monitoring of carbon pools constitutes essentials inputs for the continuous modernization of an ever- dynamic science such as climate change. This is particularly important in forested ecosystems for which accurate field archives are available and can be used in combination with historic satellite imagery to obtain spatially explicit estimates of several indicators that can be used in the assessment of said carbon pools. Many forest disturbance processes limit storage of carbon in forested ecosystems and thereby reduce those systems' capacity to mitigate changes in the global climate system. A component of the US National Forest System's (NFS) comprehensive plan for carbon monitoring includes accounting for mapped disturbances, such as fires, harvests, and insect activity. A long-term time series of maps that show the timing, extent, type, and magnitude of disturbances going back to 1990 has been prepared for the United States Forest Service (USFS) Northern Region, and is currently under preparation for the rest of the NFS regions covering more than 75 million hectares. Our mapping approach starts with an automated initial detection of annual disturbances using imagery captured within the growing season from the Landsat archive. Through a meticulous process, the initial detections are then visually inspected, manually corrected and labeled using various USFS ancillary datasets and Google Earth high-resolution historic imagery. We prepared multitemporal models of percent canopy cover and live tree carbon (T/ha) that were calibrated with extensive (in excess of 2000 locations) field data from the US Forest Service Forest Inventory and Analysis program (FIA). The models were then applied to all the years of the radiometrically corrected and normalized Landsat time series in order to provide annual spatially explicit estimates of the magnitude of change in terms of these two attributes. Our results provide objective, widely

  5. Combining forest inventory, satellite remote sensing, and geospatial data for mapping forest attributes of the conterminous United States

    Science.gov (United States)

    Mark Nelson; Greg Liknes; Charles H. Perry

    2009-01-01

    Analysis and display of forest composition, structure, and pattern provides information for a variety of assessments and management decision support. The objective of this study was to produce geospatial datasets and maps of conterminous United States forest land ownership, forest site productivity, timberland, and reserved forest land. Satellite image-based maps of...

  6. Forest Cover Mapping in Iskandar Malaysia Using Satellite Data

    Science.gov (United States)

    Kanniah, K. D.; Mohd Najib, N. E.; Vu, T. T.

    2016-09-01

    Malaysia is the third largest country in the world that had lost forest cover. Therefore, timely information on forest cover is required to help the government to ensure that the remaining forest resources are managed in a sustainable manner. This study aims to map and detect changes of forest cover (deforestation and disturbance) in Iskandar Malaysia region in the south of Peninsular Malaysia between years 1990 and 2010 using Landsat satellite images. The Carnegie Landsat Analysis System-Lite (CLASlite) programme was used to classify forest cover using Landsat images. This software is able to mask out clouds, cloud shadows, terrain shadows, and water bodies and atmospherically correct the images using 6S radiative transfer model. An Automated Monte Carlo Unmixing technique embedded in CLASlite was used to unmix each Landsat pixel into fractions of photosynthetic vegetation (PV), non photosynthetic vegetation (NPV) and soil surface (S). Forest and non-forest areas were produced from the fractional cover images using appropriate threshold values of PV, NPV and S. CLASlite software was found to be able to classify forest cover in Iskandar Malaysia with only a difference between 14% (1990) and 5% (2010) compared to the forest land use map produced by the Department of Agriculture, Malaysia. Nevertheless, the CLASlite automated software used in this study was found not to exclude other vegetation types especially rubber and oil palm that has similar reflectance to forest. Currently rubber and oil palm were discriminated from forest manually using land use maps. Therefore, CLASlite algorithm needs further adjustment to exclude these vegetation and classify only forest cover.

  7. A 50-m forest cover map in Southeast Asia from ALOS/PALSAR and its application on forest fragmentation assessment.

    Directory of Open Access Journals (Sweden)

    Jinwei Dong

    Full Text Available Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×10(6 km(2 (GlobCover to 2.69×10(6 km(2 (MCD12Q1 in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR onboard the Advanced Land Observing Satellite (ALOS became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%. The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+ implementation, and

  8. A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

    Science.gov (United States)

    Mascaro, Joseph; Asner, Gregory P; Knapp, David E; Kennedy-Bowdoin, Ty; Martin, Roberta E; Anderson, Christopher; Higgins, Mark; Chadwick, K Dana

    2014-01-01

    Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag"), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1) when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

  9. A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

    Directory of Open Access Journals (Sweden)

    Joseph Mascaro

    Full Text Available Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus. The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag", which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

  10. Time from Symptom Debut to Dementia Assessment by the Specialist Healthcare Service in Norway

    Directory of Open Access Journals (Sweden)

    Anne-Sofie Helvik

    2018-03-01

    Full Text Available Objectives: We described the duration from symptom debut to assessment at specialist healthcare outpatient clinics for dementia in Norway and explored whether educational level was associated with time from symptom debut to dementia assessment. Methods: The study comprised 835 persons from a register for individuals with cognitive symptoms (NorCog. The outcome variable was time in months from symptom debut to assessment. The main independent variable was the number of years of education. Also age, gender, marital status, cognitive function, neuropsychiatric symptoms, assistance and location were assessed. Results: In an adjusted linear mixed model, a higher educational level was associated with a longer duration from symptom debut to assessment, where 5 additional years of education increased the time from symptom debut to consultation by 10%. Conclusion: The findings may perhaps be explained by the hypothesis that highly educated people may be able to compensate better for cognitive impairment, which is in line with a hypothesis of cognitive reserve.

  11. Future forest carbon accounting challenges: the question of regionalization

    Science.gov (United States)

    Michael C. Nichols

    2015-01-01

    Forest carbon accounting techniques are changing. This year, a new accounting system is making its debut with the production of forest carbon data for EPA’s National Greenhouse Gas Inventory. The Forest Service’s annualized inventory system is being more fully integrated into estimates of forest carbon at the national and state levels both for the present and the...

  12. Pre-marital sexual debut and its associated factors among in-school adolescents in eastern Ethiopia

    Directory of Open Access Journals (Sweden)

    Oljira Lemessa

    2012-05-01

    Full Text Available Abstract Background More adolescents in Ethiopia are in school today than ever, but few studies have assessed the sexual behaviour of these learners. Thus, this study tried to assess pre-marital sexual debut and factors associated with it among in-school adolescents in Eastern Ethiopia. Methods A cross-sectional school-based study was conducted using a facilitator guided selfadministered questionnaire. Respondents were students attending regular school classes in fourteen high schools. The proportion of adolescents involved in pre-marital sexual debut and the mean age at sexual debut was computed. Factors associated with pre-marital sexual debut were assessed using bivariate and multivariable logistic regression. Results About one in four, 686 (24.8% never married in-school adolescent respondents reported pre-marital sexual debut of these 28.8% were males and 14.7% were females (p  Conclusion A significant proportion of in-school adolescents were engaged in sexual relationship. Thus, public health interventions should consider the broader determinants of premarital sexual debut, including the ecological factors in which the behavior occurs.

  13. VT Green Mountain National Forest Map - Northern Section

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) The BasemapOther_GMNFMAPN is a cartographic map product depicting the northern half of the Green Mountain National Forest (GMNF). The paper map...

  14. VT Green Mountain National Forest Map - Southern Section

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) The BasemapOther_GMNFMAPS is a cartographic map product depicting the southern half of the Green Mountain National Forest (GMNF). The paper map...

  15. Uncertainties in mapping forest carbon in urban ecosystems.

    Science.gov (United States)

    Chen, Gang; Ozelkan, Emre; Singh, Kunwar K; Zhou, Jun; Brown, Marilyn R; Meentemeyer, Ross K

    2017-02-01

    Spatially explicit urban forest carbon estimation provides a baseline map for understanding the variation in forest vertical structure, informing sustainable forest management and urban planning. While high-resolution remote sensing has proven promising for carbon mapping in highly fragmented urban landscapes, data cost and availability are the major obstacle prohibiting accurate, consistent, and repeated measurement of forest carbon pools in cities. This study aims to evaluate the uncertainties of forest carbon estimation in response to the combined impacts of remote sensing data resolution and neighborhood spatial patterns in Charlotte, North Carolina. The remote sensing data for carbon mapping were resampled to a range of resolutions, i.e., LiDAR point cloud density - 5.8, 4.6, 2.3, and 1.2 pt s/m 2 , aerial optical NAIP (National Agricultural Imagery Program) imagery - 1, 5, 10, and 20 m. Urban spatial patterns were extracted to represent area, shape complexity, dispersion/interspersion, diversity, and connectivity of landscape patches across the residential neighborhoods with built-up densities from low, medium-low, medium-high, to high. Through statistical analyses, we found that changing remote sensing data resolution introduced noticeable uncertainties (variation) in forest carbon estimation at the neighborhood level. Higher uncertainties were caused by the change of LiDAR point density (causing 8.7-11.0% of variation) than changing NAIP image resolution (causing 6.2-8.6% of variation). For both LiDAR and NAIP, urban neighborhoods with a higher degree of anthropogenic disturbance unveiled a higher level of uncertainty in carbon mapping. However, LiDAR-based results were more likely to be affected by landscape patch connectivity, and the NAIP-based estimation was found to be significantly influenced by the complexity of patch shape. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Delaying sexual debut amongst out-of-school youth in rural southwest Uganda.

    Science.gov (United States)

    Nobelius, Ann-Maree; Kalina, Bessie; Pool, Robert; Whitworth, Jimmy; Chesters, Janice; Power, Robert

    2010-08-01

    This paper focuses on 'sexual debut' among out-of-school youth in Masaka District, Uganda, factors influencing its timing and assistance young people feel they need to delay sexual initiation. Data were drawn from a sexual health needs assessment using applied anthropological techniques with young people aged 13-19 years. Parents, guardians and community leaders were also consulted. All participants felt that young people begin their sexual lives too early. Young men feel under pressure from friends and older men to prove their masculinity. Most delay further activity after debut and want assistance to resist the pressure. Young women's debut after physical maturation prompts 'pestering' for sex from boys and men who offer gifts. After debut, young women remain sexually active but believe younger women need assistance to resist pressure. Programmes are needed to help young people achieve these goals. Structurally, the community needs to develop means of preventing men from pestering young women for sex and of redeveloping both the social role and pathway to marriage for young women who are marrying later than is traditional.

  17. ESTIMATION OF STAND HEIGHT AND FOREST VOLUME USING HIGH RESOLUTION STEREO PHOTOGRAPHY AND FOREST TYPE MAP

    Directory of Open Access Journals (Sweden)

    K. M. Kim

    2016-06-01

    Full Text Available Traditional field methods for measuring tree heights are often too costly and time consuming. An alternative remote sensing approach is to measure tree heights from digital stereo photographs which is more practical for forest managers and less expensive than LiDAR or synthetic aperture radar. This work proposes an estimation of stand height and forest volume(m3/ha using normalized digital surface model (nDSM from high resolution stereo photography (25cm resolution and forest type map. The study area was located in Mt. Maehwa model forest in Hong Chun-Gun, South Korea. The forest type map has four attributes such as major species, age class, DBH class and crown density class by stand. Overlapping aerial photos were taken in September 2013 and digital surface model (DSM was created by photogrammetric methods(aerial triangulation, digital image matching. Then, digital terrain model (DTM was created by filtering DSM and subtracted DTM from DSM pixel by pixel, resulting in nDSM which represents object heights (buildings, trees, etc.. Two independent variables from nDSM were used to estimate forest stand volume: crown density (% and stand height (m. First, crown density was calculated using canopy segmentation method considering live crown ratio. Next, stand height was produced by averaging individual tree heights in a stand using Esri’s ArcGIS and the USDA Forest Service’s FUSION software. Finally, stand volume was estimated and mapped using aerial photo stand volume equations by species which have two independent variables, crown density and stand height. South Korea has a historical imagery archive which can show forest change in 40 years of successful forest rehabilitation. For a future study, forest volume change map (1970s–present will be produced using this stand volume estimation method and a historical imagery archive.

  18. Georeferenced historical forest maps of Bukovina (Northern Romania) - important tool for paleoenvironmental analyses

    Science.gov (United States)

    Popa, Ionel; Crǎciunescu, Vasile; Candrea, Bogdan; Timár, Gábor

    2010-05-01

    The historical region of Bukovina is one of the most forested areas of Romania. The name itself, beech land, suggest the high wood resources located here. The systematic wood exploitation started in Bukovina during the Austrian rule (1775 - 1918). To fully asses the region's wood potential and to make the exploitation and replantation processes more efficient, the Austrian engineers developed a dedicated mapping system. The result was a series of maps, surveyed for each forest district. In the first editions, we can find maps crafted at different scales (e.g. 1:50 000, 1: 20 000, 1: 25 000). Later on (after 1900), the map sheets scale was standardized to 1: 25 000. Each sheet was accompanied by a register with information regarding the forest parcels. The system was kept after 1918, when Bukovina become a part of Romania. For another 20 years, the forest districts were periodically surveyed and the maps updated. The basemap content also changed during time. For most of the maps, the background was compiled from the Austrian Third Military Survey maps. After the Second World War, the Romanian military maps ("planurile directoare de tragere") were also used. The forest surveys were positioned using the Austrian triangulation network with the closest baseline at Rădăuţi. Considered lost after WWII, an important part of this maps were recently recovered by a fortunate and accidental finding. Such informations are highly valuable for the today forest planners. By careful studying this kind of documents, a modern forest manager can better understand the way forests were managed in the past and the implications of that management in today's forest reality. In order to do that, the maps should be first georeferenced into a known coordinate system of the Third Survey and integrated with recent geospatial datasets using a GIS environment. The paper presents the challenges of finding and applying the right informations regarding the datum and projection used by the

  19. ASSOCIATION BETWEEN SINGLE-PARENT FAMILY STRUCTURE AND AGE OF SEXUAL DEBUT AMONG YOUNG PERSONS IN JAMAICA.

    Science.gov (United States)

    Oshi, Daniel C; Mckenzie, Jordan; Baxter, Martin; Robinson, Royelle; Neil, Stephan; Greene, Tayla; Wright, Wayne; Lodge, Jeorghino

    2018-02-26

    There is a high and increasing proportion of single-parent families in Jamaica. This has raised concerns about the potential impact of single-parent families on the social, cognitive and behavioural development of children, including their sexual relationships. The aim of this study was to investigate the association between being raised in a single-parent family and age of sexual debut among young people in Jamaica. The study was cross-sectional in design, and based on a multi-stage sampling procedure. The study was conducted in July/September 2016. The study sample comprised 233 respondents (110 males and 123 females) aged from 18 to 35 years (mean 26.37 years; SD 5.46). Respondents completed a self-administered questionnaire with questions on socio-demographic characteristics, family structure, sexual debut and current sexual behaviour. Ninety-seven (41.7%) respondents grew up in single-parent families. A total of 201 (86.3%) had had sex (102 males and 99 females). Their mean age of sexual debut was 15.51 years (SD 3.41). Sixty-five (32.3%) had early sexual debut (single-parent families were more likely to have had early sexual debut (56.9%; n=37) compared with those from two-parent families (43.1%, n=28; p=0.004). Only 44.6% (n=29) of those who experienced early sexual debut used a condom during their first sexual encounter compared with 73% (n=100) of those who had a later sexual debut (≥16 years; p=single-father family structure was a significant predictor of early sexual debut (AOR 5.5; 95%CI: 1.1-25.8). The study found a significant association between single-parent family structure and age of sexual debut.

  20. Detailed forest formation mapping in the land cover map series for the Caribbean islands

    Science.gov (United States)

    Helmer, E. H.; Schill, S.; Pedreros, D. H.; Tieszen, L. L.; Kennaway, T.; Cushing, M.; Ruzycki, T.

    2006-12-01

    Forest formation and land cover maps for several Caribbean islands were developed from Landsat ETM+ imagery as part of a multi-organizational project. The spatially explicit data on forest formation types will permit more refined estimates of some forest attributes. The woody vegetation classification scheme relates closely to that of Areces-Malea et al. (1), who classify Caribbean vegetation according to standards of the US Federal Geographic Data Committee (FGDC, 1997), with modifications similar to those in Helmer et al. (2). For several of the islands, we developed image mosaics that filled cloudy parts of scenes with data from other scene dates after using regression tree normalization (3). The regression tree procedure permitted us to develop mosaics for wet and drought seasons for a few of the islands. The resulting multiseason imagery facilitated separation between classes such as seasonal evergreen forest, semi-deciduous forest (including semi-evergreen forest), and drought deciduous forest or woodland formations. We used decision tree classification methods to classify the Landsat image mosaics to detailed forest formations and land cover for Puerto Rico (4), St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines and Grenada. The decision trees classified a stack of raster layers for each mapping area that included the Landsat image bands and various ancillary raster data layers. For Puerto Rico, for example, the ancillary data included climate parameters (5). For some islands, the ancillary data included topographic derivatives such as aspect, slope and slope position, SRTM (6) or other topographic data. Mapping forest formations with decision tree classifiers, ancillary geospatial data, and cloud-free image mosaics, accurately distinguished spectrally similar forest formations, without the aid of ecological zone maps, on the islands where the approach was used. The approach resulted in maps of forest formations with comparable or better detail

  1. Mapping forest functional type in a forest-shrubland ecotone using SPOT imagery and predictive habitat distribution modelling

    Science.gov (United States)

    Assal, Timothy J.; Anderson, Patrick J.; Sibold, Jason

    2015-01-01

    The availability of land cover data at local scales is an important component in forest management and monitoring efforts. Regional land cover data seldom provide detailed information needed to support local management needs. Here we present a transferable framework to model forest cover by major plant functional type using aerial photos, multi-date Système Pour l’Observation de la Terre (SPOT) imagery, and topographic variables. We developed probability of occurrence models for deciduous broad-leaved forest and needle-leaved evergreen forest using logistic regression in the southern portion of the Wyoming Basin Ecoregion. The model outputs were combined into a synthesis map depicting deciduous and coniferous forest cover type. We evaluated the models and synthesis map using a field-validated, independent data source. Results showed strong relationships between forest cover and model variables, and the synthesis map was accurate with an overall correct classification rate of 0.87 and Cohen’s kappa value of 0.81. The results suggest our method adequately captures the functional type, size, and distribution pattern of forest cover in a spatially heterogeneous landscape.

  2. Associations of Partner Age Gap at Sexual Debut with Teenage Parenthood and Lifetime Number of Partners.

    Science.gov (United States)

    Masho, Saba W; Chambers, Gregory J; Wallenborn, Jordyn T; Ferrance, Jacquelyn L

    2017-06-01

    Age at sexual debut and age gap between partners at debut are modifiable characteristics that may be related to risky sexual behaviors. Understanding any such relationships is a necessary first step toward strengthening risk interventions. Age at sexual debut and partner age gap were examined for 3,154 female and 2,713 male respondents to the 2011-2013 National Survey of Family Growth who first had intercourse before age 18. Multivariable logistic regression was used to assess associations between these measures and teenage parenthood and reporting a high lifetime number of partners (i.e., a number above the sample median). Females' odds of teenage parenthood were elevated if sexual debut occurred at ages 15-17 and involved a partner age gap of 3-4 years (odds ratio, 1.8) or more (2.0); they were reduced if debut occurred before age 15 and the gap was 3-4 years (0.8). Females' likelihood of reporting a high lifetime number of partners was negatively associated with age gap (0.4-0.7, depending on age at debut and length of age gap). Males' likelihood of reporting a large number of partners was positively associated with age gap if sexual debut was before age 15 and the gap was five or more years (1.7) or if debut was at ages 15-17 and involved a 3-4-year gap (2.0). Identifying the mechanisms underlying these associations could inform program design and implementation. Copyright © 2017 by the Guttmacher Institute.

  3. Capability of integrated MODIS imagery and ALOS for oil palm, rubber and forest areas mapping in tropical forest regions.

    Science.gov (United States)

    Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

    2014-05-07

    Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions.

  4. Mapping forest canopy disturbance in the Upper Great Lakes, USA

    Science.gov (United States)

    James D. Garner; Mark D. Nelson; Brian G. Tavernia; Charles H. (Hobie) Perry; Ian W. Housman

    2015-01-01

    A map of forest canopy disturbance was generated for Michigan, Wisconsin, and most of Minnesota using 42 Landsat time series stacks (LTSS) and a vegetation change tracker (VCTw) algorithm. Corresponding winter imagery was used to reduce commission errors of forest disturbance by identifying areas of persistent snow cover. The resulting disturbance age map was classed...

  5. Pre-marital sexual debut and its associated factors among in-school adolescents in Eastern Ethiopia.

    Science.gov (United States)

    Oljira, Lemessa; Berhane, Yemane; Worku, Alemayehu

    2012-05-24

    More adolescents in Ethiopia are in school today than ever, but few studies have assessed the sexual behaviour of these learners. Thus, this study tried to assess pre-marital sexual debut and factors associated with it among in-school adolescents in Eastern Ethiopia. A cross-sectional school-based study was conducted using a facilitator guided selfadministered questionnaire. Respondents were students attending regular school classes in fourteen high schools. The proportion of adolescents involved in pre-marital sexual debut and the mean age at sexual debut was computed. Factors associated with pre-marital sexual debut were assessed using bivariate and multivariable logistic regression. About one in four, 686 (24.8%) never married in-school adolescent respondents reported pre-marital sexual debut of these 28.8% were males and 14.7% were females (p pocket money per month (Adjusted OR and [95% CI] = 1.56 [1.19-2.04]), who perceived low self-educational rank (Adjusted OR and [95% CI] = 1.89 [1.07-3.34]) and who lived in rented houses (Adjusted OR and [95% CI] = 1.32 [1.03-1.70]). The females and those who were less influenced by external pressure were more protected against pre-marital sexual debut (Adjusted OR and [95% CI] = 0.44 [0.35-0.56; 0.62 [0.52-0.74, respectively]) than their counterparts. A significant proportion of in-school adolescents were engaged in sexual relationship. Thus, public health interventions should consider the broader determinants of premarital sexual debut, including the ecological factors in which the behavior occurs.

  6. Mapping forest transition trends in Okomu reserve using Landsat ...

    African Journals Online (AJOL)

    The unsupervised Iterative Self Organising Data Analysis technique was used to generate forest maps and subsequently used for forest change detection over two periods (1987 – 1999 and 1999 – 2011). From the results generated we were able to determine the effectiveness level of forest protected status assigned the ...

  7. Evaluating kriging as a tool to improve moderate resolution maps of forest biomass

    Science.gov (United States)

    Elizabeth A. Freeman; Gretchen G. Moisen

    2007-01-01

    The USDA Forest Service, Forest Inventory and Analysis program (FIA) recently produced a nationwide map of forest biomass by modeling biomass collected on forest inventory plots as nonparametric functions of moderate resolution satellite data and other environmental variables using Cubist software. Efforts are underway to develop methods to enhance this initial map. We...

  8. High-resolution mapping of forest carbon stocks in the Colombian Amazon

    Directory of Open Access Journals (Sweden)

    G. P. Asner

    2012-07-01

    Full Text Available High-resolution mapping of tropical forest carbon stocks can assist forest management and improve implementation of large-scale carbon retention and enhancement programs. Previous high-resolution approaches have relied on field plot and/or light detection and ranging (LiDAR samples of aboveground carbon density, which are typically upscaled to larger geographic areas using stratification maps. Such efforts often rely on detailed vegetation maps to stratify the region for sampling, but existing tropical forest maps are often too coarse and field plots too sparse for high-resolution carbon assessments. We developed a top-down approach for high-resolution carbon mapping in a 16.5 million ha region (> 40% of the Colombian Amazon – a remote landscape seldom documented. We report on three advances for large-scale carbon mapping: (i employing a universal approach to airborne LiDAR-calibration with limited field data; (ii quantifying environmental controls over carbon densities; and (iii developing stratification- and regression-based approaches for scaling up to regions outside of LiDAR coverage. We found that carbon stocks are predicted by a combination of satellite-derived elevation, fractional canopy cover and terrain ruggedness, allowing upscaling of the LiDAR samples to the full 16.5 million ha region. LiDAR-derived carbon maps have 14% uncertainty at 1 ha resolution, and the regional map based on stratification has 28% uncertainty in any given hectare. High-resolution approaches with quantifiable pixel-scale uncertainties will provide the most confidence for monitoring changes in tropical forest carbon stocks. Improved confidence will allow resource managers and decision makers to more rapidly and effectively implement actions that better conserve and utilize forests in tropical regions.

  9. Historical satellite data used to map Pan-Amazon forest cover

    Science.gov (United States)

    Kalluri, Satya; Desch, Arthur; Curry, Troy; Altstatt, Alice; Devers, Didier; Townshend, John; Tucker, Compton

    Deforestation in the Brazilian Amazon is well documented and the contributions of Brazilian deforestation to global change have been extensively discussed in both scientific and popular literature [e.g., Skole and Tucker, 1993]. However, deforestation within the non-Brazilian tropics of South America has received much less attention. The Pan-Amazon region covering Venezuela, Colombia, Ecuador, Peru, and Bolivia comprises ˜2 million km2 of tropical forest that is under increasing pressure from logging and development. Wall-to-wall high-resolution forest cover maps are needed to properly document the complex distribution patterns of deforestation in the Pan-Amazon [Tucker and Townshend, 2000]. The Deforestation Mapping Group at the University of Marylands Global Land Cover Facility is using Landsat data to generate tropical forest cover maps in this region (Figure l). The study shows that while rates of forest loss are generally lower than those in Brazil, there are hot spots where deforestation rates run as high as 2,200 km2 yr1.

  10. How Similar Are Forest Disturbance Maps Derived from Different Landsat Time Series Algorithms?

    Directory of Open Access Journals (Sweden)

    Warren B. Cohen

    2017-03-01

    Full Text Available Disturbance is a critical ecological process in forested systems, and disturbance maps are important for understanding forest dynamics. Landsat data are a key remote sensing dataset for monitoring forest disturbance and there recently has been major growth in the development of disturbance mapping algorithms. Many of these algorithms take advantage of the high temporal data volume to mine subtle signals in Landsat time series, but as those signals become subtler, they are more likely to be mixed with noise in Landsat data. This study examines the similarity among seven different algorithms in their ability to map the full range of magnitudes of forest disturbance over six different Landsat scenes distributed across the conterminous US. The maps agreed very well in terms of the amount of undisturbed forest over time; however, for the ~30% of forest mapped as disturbed in a given year by at least one algorithm, there was little agreement about which pixels were affected. Algorithms that targeted higher-magnitude disturbances exhibited higher omission errors but lower commission errors than those targeting a broader range of disturbance magnitudes. These results suggest that a user of any given forest disturbance map should understand the map’s strengths and weaknesses (in terms of omission and commission error rates, with respect to the disturbance targets of interest.

  11. Forest cover of North America in the 1970s mapped using Landsat MSS data

    Science.gov (United States)

    Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.

    2015-12-01

    The distribution and changes in Earth's forests impact hydrological, biogeochemical, and energy fluxes, as well as ecosystems' capacity to support biodiversity and human economies. Long-term records of forest cover are needed across a broad range of investigation, including climate and carbon-cycle modeling, hydrological studies, habitat analyzes, biological conservation, and land-use planning. Satellite-based observations enable mapping and monitoring of forests at ecologically and economically relevant resolutions and continental or even global extents. Following early forest-mapping efforts using coarser resolution remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS), forests have been mapped regionally at developed by the Global Land Cover Facility (GLCF) as reference, we developed an automated approach to detect forests using MSS data by leveraging the multispectral and phenological characteristics of forests observed in MSS time-series. The forest-cover map is produced with layers representing the year of observation, detection of forest-cover change relative to 1990, and the uncertainty of forest-cover and -change layers. The approach has been implemented with open-source libraries to facilitate processing large volumes of Landsat MSS images on high-performance computing machines. As the first result of our global mapping effort, we present the forest cover for North America. More than 25,000 Landsat MSS scenes were processed to provide a 120-meter resolution forest cover for North America, which will be made publicly available on the GLCF website (http://www.landcover.org).

  12. ADVANCED EARTH OBSERVATION APPROACH FOR MULTISCALE FOREST ECOSYSTEM SERVICES MODELING AND MAPPING (MIMOSE

    Directory of Open Access Journals (Sweden)

    G. Chirici

    2014-04-01

    Full Text Available In the last decade ecosystem services (ES have been proposed as a method for quantifying the multifunctional role of forest ecosystems. Their spatial distribution on large areas is frequently limited by the lack of information, because field data collection with traditional methods requires much effort in terms of time and cost.  In this contribution we propose a methodology (namely, MultIscale Mapping Of ecoSystem servicEs - MIMOSE based on the integration of remotely sensed images and field observation to produce a wall-to-wall geodatabase of forest parcels accompanied with several information useful as a basis for future trade-off analysis of different ES. Here, we present the application of the MIMOSE approach to a study area of 443,758 hectares  coincident with administrative Molise Region in Central Italy. The procedure is based on a local high resolution forest types map integrated with information on the main forest management approaches. Through the non-parametric k-Nearest Neighbors techniques, we produced a growing stock volume map integrating a local forest inventory with a multispectral satellite IRS LISS III imagery. With the growing stock volume map we derived a forest age map for even-aged forest types. Later these information were used to automatically create a vector forest parcels map by multidimensional image segmentation that were finally populated with a number of information useful for ES spatial estimation. The contribution briefly introduce to the MIMOSE methodology presenting the preliminary results we achieved which constitute the basis for a future implementation of ES modeling.

  13. Mapping forest structure, species gradients and growth in an urban area using lidar and hyperspectral imagery

    Science.gov (United States)

    Gu, Huan

    Urban forests play an important role in the urban ecosystem by providing a range of ecosystem services. Characterization of forest structure, species variation and growth in urban forests is critical for understanding the status, function and process of urban ecosystems, and helping maximize the benefits of urban ecosystems through management. The development of methods and applications to quantify urban forests using remote sensing data has lagged the study of natural forests due to the heterogeneity and complexity of urban ecosystems. In this dissertation, I quantify and map forest structure, species gradients and forest growth in an urban area using discrete-return lidar, airborne imaging spectroscopy and thermal infrared data. Specific objectives are: (1) to demonstrate the utility of leaf-off lidar originally collected for topographic mapping to characterize and map forest structure and associated uncertainties, including aboveground biomass, basal area, diameter, height and crown size; (2) to map species gradients using forest structural variables estimated from lidar and foliar functional traits, vegetation indices derived from AVIRIS hyperspectral imagery in conjunction with field-measured species data; and (3) to identify factors related to relative growth rates in aboveground biomass in the urban forests, and assess forest growth patterns across areas with varying degree of human interactions. The findings from this dissertation are: (1) leaf-off lidar originally acquired for topographic mapping provides a robust, potentially low-cost approach to quantify spatial patterns of forest structure and carbon stock in urban areas; (2) foliar functional traits and vegetation indices from hyperspectral data capture gradients of species distributions in the heterogeneous urban landscape; (3) species gradients, stand structure, foliar functional traits and temperature are strongly related to forest growth in the urban forests; and (4) high uncertainties in our

  14. Mapping of forest types confined to the lay of land

    Directory of Open Access Journals (Sweden)

    S. K. Farber

    2018-04-01

    Full Text Available The principles for the formation of forest typological classification and outlines promising areas for development, allowing to solve problems of not only inventory and forest management, but also mapping forest types are discussed in the paper. The analysis is performed by interpreting the concept of «natural regularity» proposed by D. L. Armand (1975. It is shown when the left side of the pattern is a set of indicators of site condition, structure of forest typological constructions will take into account not only the static indicators of the stands, but also their location, the origin and direction of the succession. For relatively similar climatic conditions, the indicators of the lay of land mainly limit the environment of formation of vegetation cover. The method of mapping forest types provides for consideration of site condition and indicators of stands of forest types. Testing is conducted on a test axis West-Sayan forest district, located in the mountains of southern Siberia. Conjugation types of forests, indicators of the topography revealed through the analysis of literary sources and characteristics of forest types accompanying diagnostic table (Smagin et al., 1980. The work is done in a GIS environment using DEM SRTM and Landsat space images. For indexing locations, the inputs are accepted: altitude (gradation 100 m, flat location, slope up to 20° and 20° slopes with northern and southern exposure. Classification of pixels of satellite images is conducted by the method of unsupervised classification separately for each scene, the high-altitude zone and location, which allows increase of the quality of interpretation, because the types of forests are confined to the topography. However completely avoiding mistakes is not possible. The main reasons are an inaccuracy of the DEM and the hit in one class of spectral brightness of different objects of interpretation. The map legend includes characteristics of the terrain, description

  15. SLAM-Aided Stem Mapping for Forest Inventory with Small-Footprint Mobile LiDAR

    Directory of Open Access Journals (Sweden)

    Jian Tang

    2015-12-01

    Full Text Available Accurately retrieving tree stem location distributions is a basic requirement for biomass estimation of forest inventory. Combining Inertial Measurement Units (IMU with Global Navigation Satellite Systems (GNSS is a commonly used positioning strategy in most Mobile Laser Scanning (MLS systems for accurate forest mapping. Coupled with a tactical or consumer grade IMU, GNSS offers a satisfactory solution in open forest environments, for which positioning accuracy better than one decimeter can be achieved. However, for such MLS systems, positioning in a mature and dense forest is still a challenging task because of the loss of GNSS signals attenuated by thick canopy. Most often laser scanning sensors in MLS systems are used for mapping and modelling rather than positioning. In this paper, we investigate a Simultaneous Localization and Mapping (SLAM-aided positioning solution with point clouds collected by a small-footprint LiDAR. Based on the field test data, we evaluate the potential of SLAM positioning and mapping in forest inventories. The results show that the positioning accuracy in the selected test field is improved by 38% compared to that of a traditional tactical grade IMU + GNSS positioning system in a mature forest environment and, as a result, we are able to produce a unambiguous tree distribution map.

  16. Bringing Together Users and Developers of Forest Biomass Maps

    Science.gov (United States)

    Brown, Molly Elizabeth; Macauley, Molly K.

    2012-01-01

    Forests store carbon and thus represent important sinks for atmospheric carbon dioxide. Reducing uncertainty in current estimates of the amount of carbon in standing forests will improve precision of estimates of anthropogenic contributions to carbon dioxide in the atmosphere due to deforestation. Although satellite remote sensing has long been an important tool for mapping land cover, until recently aboveground forest biomass estimates have relied mostly on systematic ground sampling of forests. In alignment with fiscal year 2010 congressional direction, NASA has initiated work toward a carbon monitoring system (CMS) that includes both maps of forest biomass and total carbon flux estimates. A goal of the project is to ensure that the products are useful to a wide community of scientists, managers, and policy makers, as well as to carbon cycle scientists. Understanding the needs and requirements of these data users is helpful not just to the NASA CMS program but also to the entire community working on carbon-related activities. To that end, this meeting brought together a small group of natural resource managers and policy makers who use information on forests in their work with NASA scientists who are working to create aboveground forest biomass maps. These maps, derived from combining remote sensing and ground plots, aim to be more accurate than current inventory approaches when applied at local and regional scales. Meeting participants agreed that users of biomass information will look to the CMS effort not only to provide basic data for carbon or biomass measurements but also to provide data to help serve a broad range of goals, such as forest watershed management for water quality, habitat management for biodiversity and ecosystem services, and potential use for developing payments for ecosystem service projects. Participants also reminded the CMS group that potential users include not only public sector agencies and nongovernmental organizations but also the

  17. Comparison results of forest cover mapping of Peninsular Malaysia using geospatial technology

    Science.gov (United States)

    Hamid, Wan Abdul; Abd Rahman, Shukri B. Wan

    2016-06-01

    Climate change and global warming transpire due to several factors. Among them is deforestation which occur mostly in developing countries including Malaysia where forested areas are converted to other land use for tangible economic returns and to a smaller extent, as subsistence for local communities. As a cause for concern, efforts have been taken by the World Resource Institute (WRI) and World Wildlife Fund (WWF) to monitor forest loss using geospatial technology - interpreting time-based remote sensing imageries and producing statistics of forested areas lost since 2001. In Peninsular Malaysia, the Forestry Department of Peninsular Malaysia(FDPM) has conducted forest cover mapping for the region using the same technology since 2011, producing GIS maps for 2009-2010,2011-2012,2013-2014 and 2015. This paper focuses on the comparative study of the results generated from WRI,WWF and FDPM interpretations between 2010 and 2015, the methodologies used, the similarities and differences, challenges and recommendations for future enhancement of forest cover mapping technique.

  18. RELATIONSHIP BETWEEN ORPHANHOOD STATUS, LIVING ARRANGEMENTS AND SEXUAL DEBUT: EVIDENCE FROM FEMALES IN MIDDLE ADOLESCENCE IN SOUTHERN AFRICA.

    Science.gov (United States)

    Shoko, Mercy; Ibisomi, Latifat; Levin, Jonathan; Ginsburg, Carren

    2018-05-01

    SummaryThis study examined the relationship between orphanhood status, living arrangements and sexual debut. The study is important in the context of southern Africa, where a substantial number of children live apart from their parents because the parent is dead or living elsewhere, and where female adolescents face disproportionate sexual and reproductive health risks. Data for female adolescents were taken from Demographic and Health Surveys conducted in seven southern African countries. Unadjusted and adjusted hazard ratios of sexual debut were estimated using Cox Proportional Hazard models. The results from multivariate analyses showed that non-co-residence with biological parents was significantly associated with higher risk of sexual debut in five of the seven countries. Using pooled data, the results showed that father absence was associated with higher risk of sexual debut - whether the father was deceased or living elsewhere. Interventions to delay sexual debut among female adolescents should seek to promote father-adolescent co-residence and improve access to education.

  19. Improving snow cover mapping in forests through the use of a canopy reflectance model

    International Nuclear Information System (INIS)

    Klein, A.G.; Hall, D.K.; Riggs, G.A.

    1998-01-01

    MODIS, the moderate resolution imaging spectro radiometer, will be launched in 1998 as part of the first earth observing system (EOS) platform. Global maps of land surface properties, including snow cover, will be created from MODIS imagery. The MODIS snow-cover mapping algorithm that will be used to produce daily maps of global snow cover extent at 500 m resolution is currently under development. With the exception of cloud cover, the largest limitation to producing a global daily snow cover product using MODIS is the presence of a forest canopy. A Landsat Thematic Mapper (TM) time-series of the southern Boreal Ecosystem–Atmosphere Study (BOREAS) study area in Prince Albert National Park, Saskatchewan, was used to evaluate the performance of the current MODIS snow-cover mapping algorithm in varying forest types. A snow reflectance model was used in conjunction with a canopy reflectance model (GeoSAIL) to model the reflectance of a snow-covered forest stand. Using these coupled models, the effects of varying forest type, canopy density, snow grain size and solar illumination geometry on the performance of the MODIS snow-cover mapping algorithm were investigated. Using both the TM images and the reflectance models, two changes to the current MODIS snow-cover mapping algorithm are proposed that will improve the algorithm's classification accuracy in forested areas. The improvements include using the normalized difference snow index and normalized difference vegetation index in combination to discriminate better between snow-covered and snow-free forests. A minimum albedo threshold of 10% in the visible wavelengths is also proposed. This will prevent dense forests with very low visible albedos from being classified incorrectly as snow. These two changes increase the amount of snow mapped in forests on snow-covered TM scenes, and decrease the area incorrectly identified as snow on non-snow-covered TM scenes. (author)

  20. Early sexual debut: Voluntary or coerced? Evidence from ...

    African Journals Online (AJOL)

    Early sexual debut among young women and men. (commonly defined as having had first sexual intercourse at or before age 14 years) is associated with risks to sexual and reproductive health. These include risky sexual behaviours such as multiple partners, sex under the influence of alcohol or drugs, unplanned ...

  1. Forest Biomass Mapping From Lidar and Radar Synergies

    Science.gov (United States)

    Sun, Guoqing; Ranson, K. Jon; Guo, Z.; Zhang, Z.; Montesano, P.; Kimes, D.

    2011-01-01

    The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R(exp 2) of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI Mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R2 of 0.63-0.71, RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar- SAR synergy 63 was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the

  2. Mapping forest tree species over large areas with partially cloudy Landsat imagery

    Science.gov (United States)

    Turlej, K.; Radeloff, V.

    2017-12-01

    Forests provide numerous services to natural systems and humankind, but which services forest provide depends greatly on their tree species composition. That makes it important to track not only changes in forest extent, something that remote sensing excels in, but also to map tree species. The main goal of our work was to map tree species with Landsat imagery, and to identify how to maximize mapping accuracy by including partially cloudy imagery. Our study area covered one Landsat footprint (26/28) in Northern Wisconsin, USA, with temperate and boreal forests. We selected this area because it contains numerous tree species and variable forest composition providing an ideal study area to test the limits of Landsat data. We quantified how species-level classification accuracy was affected by a) the number of acquisitions, b) the seasonal distribution of observations, and c) the amount of cloud contamination. We classified a single year stack of Landsat-7, and -8 images data with a decision tree algorithm to generate a map of dominant tree species at the pixel- and stand-level. We obtained three important results. First, we achieved producer's accuracies in the range 70-80% and user's accuracies in range 80-90% for the most abundant tree species in our study area. Second, classification accuracy improved with more acquisitions, when observations were available from all seasons, and is the best when images with up to 40% cloud cover are included. Finally, classifications for pure stands were 10 to 30 percentage points better than those for mixed stands. We conclude that including partially cloudy Landsat imagery allows to map forest tree species with accuracies that were previously only possible for rare years with many cloud-free observations. Our approach thus provides important information for both forest management and science.

  3. Mapping Deforestation and Forest Degradation Patterns in Western Himalaya, Pakistan

    Directory of Open Access Journals (Sweden)

    Faisal Mueen Qamer

    2016-05-01

    Full Text Available The Himalayan mountain forest ecosystem has been degrading since the British ruled the area in the 1850s. Local understanding of the patterns and processes of degradation is desperately required to devise management strategies to halt this degradation and provide long-term sustainability. This work comprises a satellite image based study in combination with national expert validation to generate sub-district level statistics for forest cover over the Western Himalaya, Pakistan, which accounts for approximately 67% of the total forest cover of the country. The time series of forest cover maps (1990, 2000, 2010 reveal extensive deforestation in the area. Indeed, approximately 170,684 ha of forest has been lost, which amounts to 0.38% per year clear cut or severely degraded during the last 20 years. A significant increase in the rate of deforestation is observed in the second half of the study period, where much of the loss occurs at the western borders along with Afghanistan. The current study is the first systematic and comprehensive effort to map changes to forest cover in Northern Pakistan. Deforestation hotspots identified at the sub-district level provide important insight into deforestation patterns, which may facilitate the development of appropriate forest conservation and management strategies in the country.

  4. Performance of non-parametric algorithms for spatial mapping of tropical forest structure

    Directory of Open Access Journals (Sweden)

    Liang Xu

    2016-08-01

    Full Text Available Abstract Background Mapping tropical forest structure is a critical requirement for accurate estimation of emissions and removals from land use activities. With the availability of a wide range of remote sensing imagery of vegetation characteristics from space, development of finer resolution and more accurate maps has advanced in recent years. However, the mapping accuracy relies heavily on the quality of input layers, the algorithm chosen, and the size and quality of inventory samples for calibration and validation. Results By using airborne lidar data as the “truth” and focusing on the mean canopy height (MCH as a key structural parameter, we test two commonly-used non-parametric techniques of maximum entropy (ME and random forest (RF for developing maps over a study site in Central Gabon. Results of mapping show that both approaches have improved accuracy with more input layers in mapping canopy height at 100 m (1-ha pixels. The bias-corrected spatial models further improve estimates for small and large trees across the tails of height distributions with a trade-off in increasing overall mean squared error that can be readily compensated by increasing the sample size. Conclusions A significant improvement in tropical forest mapping can be achieved by weighting the number of inventory samples against the choice of image layers and the non-parametric algorithms. Without future satellite observations with better sensitivity to forest biomass, the maps based on existing data will remain slightly biased towards the mean of the distribution and under and over estimating the upper and lower tails of the distribution.

  5. Mapping of Shorea robusta Forest Using Time Series MODIS Data

    NARCIS (Netherlands)

    Ghimire, Bhoj; Nagai, Masahiko; Tripathi, Nitin; Witayangkurn, Apichon; Mishra, Bhogendra; Sasaki, Nophea

    2017-01-01

    Mapping forest types in a natural heterogeneous forest environment using remote sensing data is a long-standing challenge due to similar spectral reflectance from different tree species and significant time and resources are required for acquiring and processing the remote sensing data. The purpose

  6. Mapping Forest Cover and Forest Cover Change with Airborne S-Band Radar

    Directory of Open Access Journals (Sweden)

    Ramesh K. Ningthoujam

    2016-07-01

    Full Text Available Assessments of forest cover, forest carbon stocks and carbon emissions from deforestation and degradation are increasingly important components of sustainable resource management, for combating biodiversity loss and in climate mitigation policies. Satellite remote sensing provides the only means for mapping global forest cover regularly. However, forest classification with optical data is limited by its insensitivity to three-dimensional canopy structure and cloud cover obscuring many forest regions. Synthetic Aperture Radar (SAR sensors are increasingly being used to mitigate these problems, mainly in the L-, C- and X-band domains of the electromagnetic spectrum. S-band has not been systematically studied for this purpose. In anticipation of the British built NovaSAR-S satellite mission, this study evaluates the benefits of polarimetric S-band SAR for forest characterisation. The Michigan Microwave Canopy Scattering (MIMICS-I radiative transfer model is utilised to understand the scattering mechanisms in forest canopies at S-band. The MIMICS-I model reveals strong S-band backscatter sensitivity to the forest canopy in comparison to soil characteristics across all polarisations and incidence angles. Airborne S-band SAR imagery over the temperate mixed forest of Savernake Forest in southern England is analysed for its information content. Based on the modelling results, S-band HH- and VV-polarisation radar backscatter and the Radar Forest Degradation Index (RFDI are used in a forest/non-forest Maximum Likelihood classification at a spatial resolution of 6 m (70% overall accuracy, κ = 0.41 and 20 m (63% overall accuracy, κ = 0.27. The conclusion is that S-band SAR such as from NovaSAR-S is likely to be suitable for monitoring forest cover and its changes.

  7. ACUTE RESPIRATORY DISEASE AS THE DEBUT OF SYSTEMIC LUPUS ERYTHEMATOSUS

    Directory of Open Access Journals (Sweden)

    A. Yu. Ischenko

    2015-01-01

    Full Text Available Systemic lupus erythematosus — a chronic autoimmune disease that is often associated with infectious processes. The paper presents two clinical cases of systemic lupus erythematosus , debuted with acute respiratory infection.

  8. Age of Sexual Debut and Physical Dating Violence Victimization: Sex Differences among US High School Students

    Science.gov (United States)

    Ihongbe, Timothy O.; Cha, Susan; Masho, Saba W.

    2017-01-01

    Background: Research has shown that early age of sexual debut is associated with physical dating violence (PDV), but sex-specific associations are sparse. We estimated the prevalence of PDV victimization in high school students who have initiated sexual intercourse and examined sex-specific association between age of sexual debut and PDV…

  9. Small forest cuttings mapped with Landsat digital data

    Science.gov (United States)

    Bryant, E.; Dodge, A. G.; Eger, M. J. E.

    1979-01-01

    The Cooperative Landsat Applications Research Group used computer classification of Landsat digital data to map forest cuttings (clearcuts) in northern New Hampshire. Cuttings as small as 3 hectares were identified. Several ages or conditions of clearcuts could be distinguished. Progress in two methods of duplicating classification categories from one Landsat pass to another are discussed. One method was used in making maps of areas in 1973, 1975, and 1978.

  10. Factors associated with pre-marital sexual debut among unmarried high school female students in bahir Dar town, Ethiopia: cross- sectional study.

    Science.gov (United States)

    Mulugeta, Yeshalem; Berhane, Yemane

    2014-05-31

    Pre-marital sexual debut increase the risk of sexually transmitted infections (STIs) including HIV/AIDS and unwanted pregnancy. It may also affect their school performance and completion rate. In spite of this fact, number of unmarried female students who started sexual debut is increasing from time to time. However, information on the extent of pre-marital sexual debut and associated factors were not well studied and documented in the study area where pre-marital sexual debut is largely condemned. Therefore this study was conducted to assess the magnitude and associated factors of pre-marital sexual debut. School based cross-sectional survey was conducted from May 10-13/2012. A total of 1123 unmarried high school female students were selected by multi- stage sampling technique. Data were collected using structured, self administered questionnaire. Descriptive statistics, binary and multivariable logistic regression analyses were used to identify factors associated with pre-marital sexual debut. Among unmarried high school female students 30.8% reported pre-marital sexual debut. The major associated factors were frequent watching of pornographic video [AOR = 10.15, 95% CI: (6.63, 15.53)], peer pressure [AOR = 2.98, 95% CI: (1.57, 5.67)] and chewing khat [AOR = 8.99, 95% CI: (3.84, 21.06)]. Significant proportion of unmarried high school female students have started pre-marital sexual debut. The finding suggests the need for communicating and supporting school students to help them make informed and safer decisions on their sexual behavior. Therefore, Bahir dar city administration health and education bureau should design persistent and effective health education to decrease pre-marital sexual debut in unmarried female students.

  11. Factors associated with pre-marital sexual debut among unmarried high school female students in bahir Dar town, Ethiopia: cross- sectional study

    Science.gov (United States)

    2014-01-01

    Background Pre-marital sexual debut increase the risk of sexually transmitted infections (STIs) including HIV/AIDS and unwanted pregnancy. It may also affect their school performance and completion rate. In spite of this fact, number of unmarried female students who started sexual debut is increasing from time to time. However, information on the extent of pre-marital sexual debut and associated factors were not well studied and documented in the study area where pre-marital sexual debut is largely condemned. Therefore this study was conducted to assess the magnitude and associated factors of pre-marital sexual debut. Methods School based cross-sectional survey was conducted from May 10-13/2012. A total of 1123 unmarried high school female students were selected by multi- stage sampling technique. Data were collected using structured, self administered questionnaire. Descriptive statistics, binary and multivariable logistic regression analyses were used to identify factors associated with pre-marital sexual debut. Results Among unmarried high school female students 30.8% reported pre-marital sexual debut. The major associated factors were frequent watching of pornographic video [AOR = 10.15, 95% CI: (6.63, 15.53)], peer pressure [AOR = 2.98, 95% CI: (1.57, 5.67)] and chewing khat [AOR = 8.99, 95% CI: (3.84, 21.06)]. Conclusion Significant proportion of unmarried high school female students have started pre-marital sexual debut. The finding suggests the need for communicating and supporting school students to help them make informed and safer decisions on their sexual behavior. Therefore, Bahir dar city administration health and education bureau should design persistent and effective health education to decrease pre-marital sexual debut in unmarried female students. PMID:24885739

  12. Monitoring air quality with lichens: A comparison between mapping in forest sites and in open areas

    International Nuclear Information System (INIS)

    Policnik, Helena; Simoncic, Primoz; Batic, Franc

    2008-01-01

    Four different methods of epiphytic lichen mapping were used for the assessment of air quality in the region under the influence of the Sostanj Thermal Power Plant (Salek Valley, Slovenia). Three methods were based on the presence of different lichen species (VDI, EU and ICP-Forest), the fourth on a frequency and coverage assessment of different growth forms of epiphytic lichens, e.g. crustose, foliose and fruticose (SI). A comparison of the results from the assessment of air quality between forest sites (ICP-Forest, SI) and open areas (VDI, EU and SI), obtained by the different methods of epiphytic lichen mapping, is presented in the contribution. Data showed that lichen species richness is worse in forest sites in comparison with open areas. From the data obtained it can be concluded that epiphytic lichen mapping in open areas is a better method for the assessment of air pollution in a given area than mapping in forest sites. The species-based methods in open areas are more powerful and useful for air quality assessment in polluted research areas than the SI and ICP-Forest methods. - The mapping of epiphytic lichens in open areas is more suitable for air quality assessment than mapping in forest sites in the Salek Valley, Slovenia

  13. Possibilities of a Personal Laser Scanning System for Forest Mapping and Ecosystem Services

    Science.gov (United States)

    Liang, Xinlian; Kukko, Antero; Kaartinen, Harri; Hyyppä, Juha; Yu, Xiaowei; Jaakkola, Anttoni; Wang, Yunsheng

    2014-01-01

    A professional-quality, personal laser scanning (PLS) system for collecting tree attributes was demonstrated in this paper. The applied system, which is wearable by human operators, consists of a multi-constellation navigation system and an ultra-high-speed phase-shift laser scanner mounted on a rigid baseplate and consisting of a single sensor block. A multipass-corridor-mapping method was developed to process PLS data and a 2,000 m2 forest plot was utilized in the test. The tree stem detection accuracy was 82.6%; the root mean square error (RMSE) of the estimates of tree diameter at breast height (DBH) was 5.06 cm; the RMSE of the estimates of tree location was 0.38 m. The relative RMSE of the DBH estimates was 14.63%. The results showed, for the first time, the potential of the PLS system in mapping large forest plots. Further research on mapping accuracy in various forest conditions, data correction methods and multi-sensoral positioning techniques is needed. The utilization of this system in different applications, such as harvester operations, should also be explored. In addition to collecting tree-level and plot-level data for forest inventory, other possible applications of PLS for forest ecosystem services include mapping of canopy gaps, measuring leaf area index of large areas, documenting and visualizing forest routes feasible for recreation, hiking and berry and mushroom picking. PMID:24434879

  14. Mapping aboveground woody biomass using forest inventory, remote sensing and geostatistical techniques.

    Science.gov (United States)

    Yadav, Bechu K V; Nandy, S

    2015-05-01

    Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m × 31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10-40, 40-70 and >70% of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m(3) ha(-1). The total growing stock of the forest was found to be 2,024,652.88 m(3). The AGWB ranged from 143 to 421 Mgha(-1). Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE) = 42.25 Mgha(-1)) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha(-1) respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha(-1). The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.

  15. Large-Scale Mapping of Tree-Community Composition as a Surrogate of Forest Degradation in Bornean Tropical Rain Forests

    Directory of Open Access Journals (Sweden)

    Shogoro Fujiki

    2016-12-01

    Full Text Available Assessment of the progress of the Aichi Biodiversity Targets set by the Convention on Biological Diversity (CBD and the safeguarding of ecosystems from the perverse negative impacts caused by Reducing Emissions from Deforestation and Forest Degradation Plus (REDD+ requires the development of spatiotemporally robust and sensitive indicators of biodiversity and ecosystem health. Recently, it has been proposed that tree-community composition based on count-plot surveys could serve as a robust, sensitive, and cost-effective indicator for forest intactness in Bornean logged-over rain forests. In this study, we developed an algorithm to map tree-community composition across the entire landscape based on Landsat imagery. We targeted six forest management units (FMUs, each of which ranged from 50,000 to 100,000 ha in area, covering a broad geographic range spanning the most area of Borneo. Approximately fifty 20 m-radius circular plots were established in each FMU, and the differences in tree-community composition at a genus level among plots were examined for trees with diameter at breast height ≥10 cm using an ordination with non-metric multidimensional scaling (nMDS. Subsequently, we developed a linear regression model based on Landsat metrics (e.g., reflectance value, vegetation indices and textures to explain the nMDS axis-1 scores of the plots, and extrapolated the model to the landscape to establish a tree-community composition map in each FMU. The adjusted R2 values based on a cross-validation approach between the predicted and observed nMDS axis-1 scores indicated a close correlation, ranging from 0.54 to 0.69. Histograms of the frequency distributions of extrapolated nMDS axis-1 scores were derived from each map and used to quantitatively diagnose the forest intactness of the FMUs. Our study indicated that tree-community composition, which was reported as a robust indicator of forest intactness, could be mapped at a landscape level to

  16. Remote sensing mapping of carbon and energy fluxes over forests

    NARCIS (Netherlands)

    Roerink, G.J.; Wit, de A.J.W.; Pelgrum, H.; Mücher, C.A.

    2001-01-01

    This report presents the results of the EU project "Carbon and water fluxes of Mediterranean forests and impacts of land use/cover changes". The objectives of the project can be summarized as follows: (I) surface energy balance mapping using remote sensing, (ii) carbon uptake mapping using remote

  17. Mapping change of older forest with nearest-neighbor imputation and Landsat time-series

    Science.gov (United States)

    Janet L. Ohmann; Matthew J. Gregory; Heather M. Roberts; Warren B. Cohen; Robert E. Kennedy; Zhiqiang. Yang

    2012-01-01

    The Northwest Forest Plan (NWFP), which aims to conserve late-successional and old-growth forests (older forests) and associated species, established new policies on federal lands in the Pacific Northwest USA. As part of monitoring for the NWFP, we tested nearest-neighbor imputation for mapping change in older forest, defined by threshold values for forest attributes...

  18. Mapping beech (Fagus sylvatica L.) forest structure with airborne hyperspectral imagery

    CSIR Research Space (South Africa)

    Cho, Moses A

    2009-06-01

    Full Text Available The objective of this study was to assess the utility of hyperspectral data in estimating and mapping forest structural parameters including mean diameter-at-breast-height (DBH), mean tree height and tree density of a closed canopy beech forest...

  19. Mapping Annual Forest Cover in Sub-Humid and Semi-Arid Regions through Analysis of Landsat and PALSAR Imagery

    Directory of Open Access Journals (Sweden)

    Yuanwei Qin

    2016-11-01

    Full Text Available Accurately mapping the spatial distribution of forests in sub-humid to semi-arid regions over time is important for forest management but a challenging task. Relatively large uncertainties still exist in the spatial distribution of forests and forest changes in the sub-humid and semi-arid regions. Numerous publications have used either optical or synthetic aperture radar (SAR remote sensing imagery, but the resultant forest cover maps often have large errors. In this study, we propose a pixel- and rule-based algorithm to identify and map annual forests from 2007 to 2010 in Oklahoma, USA, a transitional region with various climates and landscapes, using the integration of the L-band Advanced Land Observation Satellite (ALOS PALSAR Fine Beam Dual Polarization (FBD mosaic dataset and Landsat images. The overall accuracy and Kappa coefficient of the PALSAR/Landsat forest map were about 88.2% and 0.75 in 2010, with the user and producer accuracy about 93.4% and 75.7%, based on the 3270 random ground plots collected in 2012 and 2013. Compared with the forest products from Japan Aerospace Exploration Agency (JAXA, National Land Cover Database (NLCD, Oklahoma Ecological Systems Map (OKESM and Oklahoma Forest Resource Assessment (OKFRA, the PALSAR/Landsat forest map showed great improvement. The area of the PALSAR/Landsat forest was about 40,149 km2 in 2010, which was close to the area from OKFRA (40,468 km2, but much larger than those from JAXA (32,403 km2 and NLCD (37,628 km2. We analyzed annual forest cover dynamics, and the results show extensive forest cover loss (2761 km2, 6.9% of the total forest area in 2010 and gain (3630 km2, 9.0% in southeast and central Oklahoma, and the total area of forests increased by 684 km2 from 2007 to 2010. This study clearly demonstrates the potential of data fusion between PALSAR and Landsat images for mapping annual forest cover dynamics in sub-humid to semi-arid regions, and the resultant forest maps would be

  20. Possibilities of a Personal Laser Scanning System for Forest Mapping and Ecosystem Services

    Directory of Open Access Journals (Sweden)

    Xinlian Liang

    2014-01-01

    Full Text Available A professional-quality, personal laser scanning (PLS system for collecting tree attributes was demonstrated in this paper. The applied system, which is wearable by human operators, consists of a multi-constellation navigation system and an ultra-high-speed phase-shift laser scanner mounted on a rigid baseplate and consisting of a single sensor block. A multipass-corridor-mapping method was developed to process PLS data and a 2,000 m2 forest plot was utilized in the test. The tree stem detection accuracy was 82.6%; the root mean square error (RMSE of the estimates of tree diameter at breast height (DBH was 5.06 cm; the RMSE of the estimates of tree location was 0.38 m. The relative RMSE of the DBH estimates was 14.63%. The results showed, for the first time, the potential of the PLS system in mapping large forest plots. Further research on mapping accuracy in various forest conditions, data correction methods and multi-sensoral positioning techniques is needed. The utilization of this system in different applications, such as harvester operations, should also be explored. In addition to collecting tree-level and plot-level data for forest inventory, other possible applications of PLS for forest ecosystem services include mapping of canopy gaps, measuring leaf area index of large areas, documenting and visualizing forest routes feasible for recreation, hiking and berry and mushroom picking.

  1. Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps.

    Science.gov (United States)

    Mitchard, Edward Ta; Saatchi, Sassan S; Baccini, Alessandro; Asner, Gregory P; Goetz, Scott J; Harris, Nancy L; Brown, Sandra

    2013-10-26

    Mapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m - 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by the same spaceborne LiDAR dataset providing systematic forest height and canopy structure estimates, but use different ground datasets for calibration and different spatial modelling methodologies. Here, we compare these two maps to each other, to the FAO's Forest Resource Assessment (FRA) 2010 country-level data, and to a high resolution (100 m) biomass map generated for a portion of the Colombian Amazon. We find substantial differences between the two maps, in particular in central Amazonia, the Congo basin, the south of Papua New Guinea, the Miombo woodlands of Africa, and the dry forests and savannas of South America. There is little consistency in the direction of the difference. However, when the maps are aggregated to the country or biome scale there is greater agreement, with differences cancelling out to a certain extent. When comparing country level biomass stocks, the two maps agree with each other to a much greater extent than to the FRA 2010 estimates. In the Colombian Amazon, both pantropical maps estimate higher biomass than the independent high resolution map, but show a similar spatial distribution of this biomass. Biomass mapping has progressed enormously over the past decade, to the stage where we can produce globally consistent maps of aboveground biomass. We show that there are still large uncertainties in these maps, in particular in areas with little field data. However, when used at a regional scale, different maps appear to converge, suggesting we can provide

  2. Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010.

    Science.gov (United States)

    Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhang, Geli; Roy, Partha Sarathi; Joshi, Pawan Kumar; Gilani, Hammad; Murthy, Manchiraju Sri Ramachandra; Jin, Cui; Wang, Jie; Zhang, Yao; Chen, Bangqian; Menarguez, Michael Angelo; Biradar, Chandrashekhar M; Bajgain, Rajen; Li, Xiangping; Dai, Shengqi; Hou, Ying; Xin, Fengfei; Moore, Berrien

    2016-02-11

    Extensive forest changes have occurred in monsoon Asia, substantially affecting climate, carbon cycle and biodiversity. Accurate forest cover maps at fine spatial resolutions are required to qualify and quantify these effects. In this study, an algorithm was developed to map forests in 2010, with the use of structure and biomass information from the Advanced Land Observation System (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) mosaic dataset and the phenological information from MODerate Resolution Imaging Spectroradiometer (MOD13Q1 and MOD09A1) products. Our forest map (PALSARMOD50 m F/NF) was assessed through randomly selected ground truth samples from high spatial resolution images and had an overall accuracy of 95%. Total area of forests in monsoon Asia in 2010 was estimated to be ~6.3 × 10(6 )km(2). The distribution of evergreen and deciduous forests agreed reasonably well with the median Normalized Difference Vegetation Index (NDVI) in winter. PALSARMOD50 m F/NF map showed good spatial and areal agreements with selected forest maps generated by the Japan Aerospace Exploration Agency (JAXA F/NF), European Space Agency (ESA F/NF), Boston University (MCD12Q1 F/NF), Food and Agricultural Organization (FAO FRA), and University of Maryland (Landsat forests), but relatively large differences and uncertainties in tropical forests and evergreen and deciduous forests.

  3. Age differences at sexual debut and subsequent reproductive health: Is there a link?

    Directory of Open Access Journals (Sweden)

    Reynolds Heidi

    2008-10-01

    Full Text Available Abstract Background Experiences at sexual debut may be linked to reproductive health later in life. Additionally, young women with older sexual partners may be at greater risk for HIV and sexually transmitted infections. This study examines sexual debut with an older partner and subsequent reproductive health outcomes among 599 sexually experienced women aged 15–24 who utilized voluntary counseling and testing or reproductive health services in Port-au-Prince, Haiti. Methods Logistic regression models, controlling for socioeconomic and demographic factors, examined whether age differences at first sex were significantly associated with STI diagnosis in the previous 12 months and family planning method use at last intercourse. Results Sixty-five percent of women reported sexual initiation with a partner younger or less than 5 years older, 28% with a partner 5 to 10 years older, and 7% with a partner 10 or more years older. There was a trend towards decreased likelihood of recent use of family planning methods in women who had first sexual intercourse with a partner 5 to 9 years older compared to women with partners who were younger or less than 5 years older. Age differences were not linked to recent STI diagnosis. Conclusion Programs focusing on delaying sexual debut should consider age and gender-based power differentials between younger women and older men. Future research should examine whether wide age differences at sexual debut are predictive of continued involvement in cross-generational relationships and risky sexual behaviors and explore the mechanisms by which cross-generational first sex and subsequent reproductive health may be connected.

  4. A practical and automated approach to large area forest disturbance mapping with remote sensing.

    Directory of Open Access Journals (Sweden)

    Mutlu Ozdogan

    Full Text Available In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i creating masks for water, non-forested areas, clouds, and cloud shadows; ii identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR difference image; iii filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission, issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for

  5. Modelling and mapping the suitability of European forest formations at 1-km resolution

    DEFF Research Database (Denmark)

    Casalegno, Stefano; Amatulli, Giuseppe; Bastrup-Birk, Annemarie

    2011-01-01

    factors. Here, we used the bootstrap-aggregating machine-learning ensemble classifier Random Forest (RF) to derive a 1-km resolution European forest formation suitability map. The statistical model use as inputs more than 6,000 field data forest inventory plots and a large set of environmental variables...

  6. Comparison of interferometric and stereo-radargrammetric 3D metrics in mapping of forest resources

    Science.gov (United States)

    Karila, K.; Karjalainen, M.; Yu, X.; Vastaranta, M.; Holopainen, M.; Hyyppa, J.

    2015-04-01

    Accurate forest resources maps are needed in diverse applications ranging from the local forest management to the global climate change research. In particular, it is important to have tools to map changes in forest resources, which helps us to understand the significance of the forest biomass changes in the global carbon cycle. In the task of mapping changes in forest resources for wide areas, Earth Observing satellites could play the key role. In 2013, an EU/FP7-Space funded project "Advanced_SAR" was started with the main objective to develop novel forest resources mapping methods based on the fusion of satellite based 3D measurements and in-situ field measurements of forests. During the summer 2014, an extensive field surveying campaign was carried out in the Evo test site, Southern Finland. Forest inventory attributes of mean tree height, basal area, mean stem diameter, stem volume, and biomass, were determined for 91 test plots having the size of 32 by 32 meters (1024 m2). Simultaneously, a comprehensive set of satellite and airborne data was collected. Satellite data also included a set of TanDEM-X (TDX) and TerraSAR-X (TSX) X-band synthetic aperture radar (SAR) images, suitable for interferometric and stereo-radargrammetric processing to extract 3D elevation data representing the forest canopy. In the present study, we compared the accuracy of TDX InSAR and TSX stereo-radargrammetric derived 3D metrics in forest inventory attribute prediction. First, 3D data were extracted from TDX and TSX images. Then, 3D data were processed as elevations above the ground surface (forest canopy height values) using an accurate Digital Terrain Model (DTM) based on airborne laser scanning survey. Finally, 3D metrics were calculated from the canopy height values for each test plot and the 3D metrics were compared with the field reference data. The Random Forest method was used in the forest inventory attributes prediction. Based on the results InSAR showed slightly better

  7. Mapping Forest Canopy Height over Continental China Using Multi-Source Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Xiliang Ni

    2015-06-01

    Full Text Available Spatially-detailed forest height data are useful to monitor local, regional and global carbon cycle. LiDAR remote sensing can measure three-dimensional forest features but generating spatially-contiguous forest height maps at a large scale (e.g., continental and global is problematic because existing LiDAR instruments are still data-limited and expensive. This paper proposes a new approach based on an artificial neural network (ANN for modeling of forest canopy heights over the China continent. Our model ingests spaceborne LiDAR metrics and multiple geospatial predictors including climatic variables (temperature and precipitation, forest type, tree cover percent and land surface reflectance. The spaceborne LiDAR instrument used in the study is the Geoscience Laser Altimeter System (GLAS, which can provide within-footprint forest canopy heights. The ANN was trained with pairs between spatially discrete LiDAR metrics and full gridded geo-predictors. This generates valid conjugations to predict heights over the China continent. The ANN modeled heights were evaluated with three different reference data. First, field measured tree heights from three experiment sites were used to validate the ANN model predictions. The observed tree heights at the site-scale agreed well with the modeled forest heights (R = 0.827, and RMSE = 4.15 m. Second, spatially discrete GLAS observations and a continuous map from the interpolation of GLAS-derived tree heights were separately used to evaluate the ANN model. We obtained R of 0.725 and RMSE of 7.86 m and R of 0.759 and RMSE of 8.85 m, respectively. Further, inter-comparisons were also performed with two existing forest height maps. Our model granted a moderate agreement with the existing satellite-based forest height maps (R = 0.738, and RMSE = 7.65 m (R2 = 0.52, and RMSE = 8.99 m. Our results showed that the ANN model developed in this paper is capable of estimating forest heights over the China continent with a

  8. Tasting the Forbidden Fruit: The Social Context of Debut Sexual ...

    African Journals Online (AJOL)

    Tasting the Forbidden Fruit: The Social Context of Debut Sexual Encounters Among Young Persons in a Rural Nigerian Community. ... Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.

  9. High-resolution global maps of 21st-century forest cover change.

    Science.gov (United States)

    Hansen, M C; Potapov, P V; Moore, R; Hancher, M; Turubanova, S A; Tyukavina, A; Thau, D; Stehman, S V; Goetz, S J; Loveland, T R; Kommareddy, A; Egorov, A; Chini, L; Justice, C O; Townshend, J R G

    2013-11-15

    Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.

  10. Benchmark map of forest carbon stocks in tropical regions across three continents.

    Science.gov (United States)

    Saatchi, Sassan S; Harris, Nancy L; Brown, Sandra; Lefsky, Michael; Mitchard, Edward T A; Salas, William; Zutta, Brian R; Buermann, Wolfgang; Lewis, Simon L; Hagen, Stephen; Petrova, Silvia; White, Lee; Silman, Miles; Morel, Alexandra

    2011-06-14

    Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a "benchmark" map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ± 6% to ± 53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ± 5% and ca. ± 1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete.

  11. Benchmark map of forest carbon stocks in tropical regions across three continents

    Science.gov (United States)

    Saatchi, Sassan S.; Harris, Nancy L.; Brown, Sandra; Lefsky, Michael; Mitchard, Edward T. A.; Salas, William; Zutta, Brian R.; Buermann, Wolfgang; Lewis, Simon L.; Hagen, Stephen; Petrova, Silvia; White, Lee; Silman, Miles; Morel, Alexandra

    2011-01-01

    Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a “benchmark” map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ±6% to ±53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ±5% and ca. ±1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete. PMID:21628575

  12. Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps

    OpenAIRE

    Mitchard, Edward TA; Saatchi, Sassan S; Baccini, Alessandro; Asner, Gregory P; Goetz, Scott J; Harris, Nancy L; Brown, Sandra

    2013-01-01

    BackgroundMapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m – 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by t...

  13. Bridging scale gaps between regional maps of forest aboveground biomass and field sampling plots using TanDEM-X data

    Science.gov (United States)

    Ni, W.; Zhang, Z.; Sun, G.

    2017-12-01

    Several large-scale maps of forest AGB have been released [1] [2] [3]. However, these existing global or regional datasets were only approximations based on combining land cover type and representative values instead of measurements of actual forest aboveground biomass or forest heights [4]. Rodríguez-Veiga et al[5] reported obvious discrepancies of existing forest biomass stock maps with in-situ observations in Mexico. One of the biggest challenges to the credibility of these maps comes from the scale gaps between the size of field sampling plots used to develop(or validate) estimation models and the pixel size of these maps and the availability of field sampling plots with sufficient size for the verification of these products [6]. It is time-consuming and labor-intensive to collect sufficient number of field sampling data over the plot size of the same as resolutions of regional maps. The smaller field sampling plots cannot fully represent the spatial heterogeneity of forest stands as shown in Figure 1. Forest AGB is directly determined by forest heights, diameter at breast height (DBH) of each tree, forest density and tree species. What measured in the field sampling are the geometrical characteristics of forest stands including the DBH, tree heights and forest densities. The LiDAR data is considered as the best dataset for the estimation of forest AGB. The main reason is that LiDAR can directly capture geometrical features of forest stands by its range detection capabilities.The remotely sensed dataset, which is capable of direct measurements of forest spatial structures, may serve as a ladder to bridge the scale gaps between the pixel size of regional maps of forest AGB and field sampling plots. Several researches report that TanDEM-X data can be used to characterize the forest spatial structures [7, 8]. In this study, the forest AGB map of northeast China were produced using ALOS/PALSAR data taking TanDEM-X data as a bridges. The TanDEM-X InSAR data used in

  14. Forest Aboveground Biomass Mapping and Canopy Cover Estimation from Simulated ICESat-2 Data

    Science.gov (United States)

    Narine, L.; Popescu, S. C.; Neuenschwander, A. L.

    2017-12-01

    The assessment of forest aboveground biomass (AGB) can contribute to reducing uncertainties associated with the amount and distribution of terrestrial carbon. With a planned launch date of July 2018, the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) will provide data which will offer the possibility of mapping AGB at global scales. In this study, we develop approaches for utilizing vegetation data that will be delivered in ICESat-2's land-vegetation along track product (ATL08). The specific objectives are to: (1) simulate ICESat-2 photon-counting lidar (PCL) data using airborne lidar data, (2) utilize simulated PCL data to estimate forest canopy cover and AGB and, (3) upscale AGB predictions to create a wall-to-wall AGB map at 30-m spatial resolution. Using existing airborne lidar data for Sam Houston National Forest (SHNF) located in southeastern Texas and known ICESat-2 beam locations, PCL data are simulated from discrete return lidar points. We use multiple linear regression models to relate simulated PCL metrics for 100 m segments along the ICESat-2 ground tracks to AGB from a biomass map developed using airborne lidar data and canopy cover calculated from the same. Random Forest is then used to create an AGB map from predicted estimates and explanatory data consisting of spectral metrics derived from Landsat TM imagery and land cover data from the National Land Cover Database (NLCD). Findings from this study will demonstrate how data that will be acquired by ICESat-2 can be used to estimate forest structure and characterize the spatial distribution of AGB.

  15. Automatic crown cover mapping to improve forest inventory

    Science.gov (United States)

    Claude Vidal; Jean-Guy Boureau; Nicolas Robert; Nicolas Py; Josiane Zerubia; Xavier Descombes; Guillaume Perrin

    2009-01-01

    To automatically analyze near infrared aerial photographs, the French National Institute for Research in Computer Science and Control developed together with the French National Forest Inventory (NFI) a method for automatic crown cover mapping. This method uses a Reverse Jump Monte Carlo Markov Chain algorithm to locate the crowns and describe those using ellipses or...

  16. Mapping Biomass for REDD in the Largest Forest of Central Africa: the Democratic Republic of Congo

    Science.gov (United States)

    Shapiro, Aurelie; Saatchi, Sassan

    2014-05-01

    With the support of the International Climate Initiative (ICI) of the Federal Ministry of the Environment, Conservation, and Nuclear Security, the implementation of the German Development Bank KfW, the World Wide Fund for Nature (WWF) Germany, the University of California Los Angeles (UCLA) and local DRC partners will produce a national scale biomass map for the entire forest coverage of the Democratic Republic of Congo (DRC) along with feasibility assessments of different forest protection measures within a framework of a REDD+ model project. The « Carbon Map and Model (CO2M&M) » project will produce a national forest biomass map for the DRC, which will enable quantitative assessments of carbon stocks and emissions in the largest forest of the Congo Basin. This effort will support the national REDD (Reducing Emissions from Deforestation and Degradation) program in DRC, which plays a major role in sustainable development and poverty alleviation. This map will be developed from field data, complemented by airborne LiDAR (Light Detection and Ranging) and aerial photos, systematically sampled throughout the forests of the DRC and up-scaled to satellite images to accurately estimate carbon content in all forested areas. The second component of the project is to develop specific approaches for model REDD projects in key landscapes. This project represents the largest LiDAR-derived mapping effort in Africa, under unprecedented logistical constraints, which will provide one of the poorest nations in the world with the richest airborne and satellites derived datasets for analyzing forest structure, biomass and biodiversity.

  17. Sexual behaviour, debut and identity among Swedish Schoolchildren

    OpenAIRE

    Kastbom, Åsa A.

    2015-01-01

    Background: Sexual behaviour among schoolchildren and adolescents is a sparsely researched area and there are delicate methodological obstacles and ethical concerns when conducting such research. Still it is a subject that engages both parents and professionals. A sexualized behaviour or an early sexual debut (younger than 14 years) can be a sign of sexual abuse. It is therefore of importance to describe what is common and what is uncommon sexual behaviour among children and what the conseque...

  18. Association mapping in forest trees and fruit crops.

    Science.gov (United States)

    Khan, M Awais; Korban, Schuyler S

    2012-06-01

    Association mapping (AM), also known as linkage disequilibrium (LD) mapping, is a viable approach to overcome limitations of pedigree-based quantitative trait loci (QTL) mapping. In AM, genotypic and phenotypic correlations are investigated in unrelated individuals. Unlike QTL mapping, AM takes advantage of both LD and historical recombination present within the gene pool of an organism, thus utilizing a broader reference population. In plants, AM has been used in model species with available genomic resources. Pursuing AM in tree species requires both genotyping and phenotyping of large populations with unique architectures. Recently, genome sequences and genomic resources for forest and fruit crops have become available. Due to abundance of single nucleotide polymorphisms (SNPs) within a genome, along with availability of high-throughput resequencing methods, SNPs can be effectively used for genotyping trees. In addition to DNA polymorphisms, copy number variations (CNVs) in the form of deletions, duplications, and insertions also play major roles in control of expression of phenotypic traits. Thus, CNVs could provide yet another valuable resource, beyond those of microsatellite and SNP variations, for pursuing genomic studies. As genome-wide SNP data are generated from high-throughput sequencing efforts, these could be readily reanalysed to identify CNVs, and subsequently used for AM studies. However, forest and fruit crops possess unique architectural and biological features that ought to be taken into consideration when collecting genotyping and phenotyping data, as these will also dictate which AM strategies should be pursued. These unique features as well as their impact on undertaking AM studies are outlined and discussed.

  19. Experiences and conceptualizations of sexual debut from the narratives of South African men and women in the context of HIV/AIDS.

    Science.gov (United States)

    Stern, Erin; Cooper, Diane

    2014-01-01

    Given the pivotal role of first sex in the development of sexual and reproductive health (SRH) practices, there is a need for more contextualised and nuanced understandings of young people's early sexual debut experiences. This study used sexual history narratives to investigate how South African men and women experience and attribute meaning to their sexual debut, and their SRH practices. In light of the gendered disparities among young people's SRH awareness and risk, differences between men and women's narratives of sexual debut were assessed. Fifty sexual history interviews were conducted with men and 25 sexual history interviews with women, with participants purposively sampled from three age categories, a range of cultural and racial backgrounds and urban and rural sites across five provinces. Narrative interviews were designed to elicit stories around participants' early knowledge of sex and sexual experimentation, their range of sexual relationships and SRH practices. The data were analysed using a thematic approach. Participants generally reflected on their early sexual experiences with feelings of inadequacy and disappointment. While men appeared to hold greater decision-making power than women at sexual debut, descriptions of men's early sexual experiences were often characterised by respect, intimacy and vulnerability. Many men attributed the timing of their sexual debut to peer pressure, which typically generated higher social status and rarely included consideration of the need to practice safer sex. Several women felt pressured by their partner to sexually debut, which could have informed their perceptions of men being sexually controlling and aggressive. The study demonstrates the value of a narrative approach for generating insights on young people's sexual debut experiences and SRH practices, and the underlying gendered norms and expectations that shape these. The findings indicate the need for gender transformative HIV interventions to take into

  20. Forest biomass mapping from fusion of GEDI Lidar data and TanDEM-X InSAR data

    Science.gov (United States)

    Qi, W.; Hancock, S.; Armston, J.; Marselis, S.; Dubayah, R.

    2017-12-01

    Mapping forest above-ground biomass (hereafter biomass) can significantly improve our ability to assess the role of forest in terrestrial carbon budget and to analyze the ecosystem productivity. Global Ecosystem Dynamic Investigation (GEDI) mission will provide the most complete lidar observations of forest vertical structure and has the potential to provide global-scale forest biomass data at 1-km resolution. However, GEDI is intrinsically a sampling mission and will have a between-track spacing of 600 m. An increase in adjacent-swath distance and the presence of cloud cover may also lead to larger gaps between GEDI tracks. In order to provide wall-to-wall forest biomass maps, fusion algorithms of GEDI lidar data and TanDEM-X InSAR data were explored in this study. Relationship between biomass and lidar RH metrics was firstly developed and used to derive biomass values over GEDI tracks which were simulated using airborne lidar data. These GEDI biomass values were then averaged in each 1-km cell to represent the biomass density within that cell. Whereas for cells without any GEDI observations, regression models developed between GEDI-derived biomass and TDX InSAR variables were applied to predict biomass over those places. Based on these procedures, contiguous biomass maps were finally generated at 1-km resolution over three representative forest types. Uncertainties for these biomass maps were also estimated at 1 km following methods developed in Saarela et al. (2016). Our results indicated great potential of GEDI/TDX fusion for large-scale biomass mapping. Saarela, S., Holm, S., Grafstrom, A., Schnell, S., Naesset, E., Gregoire, T.G., Nelson, R.F., & Stahl, G. (2016). Hierarchical model-based inference for forest inventory utilizing three sources of information. Annals of Forest Science, 73, 895-910

  1. An Integrated GNSS/INS/LiDAR-SLAM Positioning Method for Highly Accurate Forest Stem Mapping

    Directory of Open Access Journals (Sweden)

    Chuang Qian

    2016-12-01

    Full Text Available Forest mapping, one of the main components of performing a forest inventory, is an important driving force in the development of laser scanning. Mobile laser scanning (MLS, in which laser scanners are installed on moving platforms, has been studied as a convenient measurement method for forest mapping in the past several years. Positioning and attitude accuracies are important for forest mapping using MLS systems. Inertial Navigation Systems (INSs and Global Navigation Satellite Systems (GNSSs are typical and popular positioning and attitude sensors used in MLS systems. In forest environments, because of the loss of signal due to occlusion and severe multipath effects, the positioning accuracy of GNSS is severely degraded, and even that of GNSS/INS decreases considerably. Light Detection and Ranging (LiDAR-based Simultaneous Localization and Mapping (SLAM can achieve higher positioning accuracy in environments containing many features and is commonly implemented in GNSS-denied indoor environments. Forests are different from an indoor environment in that the GNSS signal is available to some extent in a forest. Although the positioning accuracy of GNSS/INS is reduced, estimates of heading angle and velocity can maintain high accurate even with fewer satellites. GNSS/INS and the LiDAR-based SLAM technique can be effectively integrated to form a sustainable, highly accurate positioning and mapping solution for use in forests without additional hardware costs. In this study, information such as heading angles and velocities extracted from a GNSS/INS is utilized to improve the positioning accuracy of the SLAM solution, and two information-aided SLAM methods are proposed. First, a heading angle-aided SLAM (H-aided SLAM method is proposed that supplies the heading angle from GNSS/INS to SLAM. Field test results show that the horizontal positioning accuracy of an entire trajectory of 800 m is 0.13 m and is significantly improved (by 70% compared to that

  2. Utilizing a Multi-Source Forest Inventory Technique, MODIS Data and Landsat TM Images in the Production of Forest Cover and Volume Maps for the Terai Physiographic Zone in Nepal

    Directory of Open Access Journals (Sweden)

    Kalle Eerikäinen

    2012-12-01

    Full Text Available An approach based on the nearest neighbors techniques is presented for producing thematic maps of forest cover (forest/non-forest and total stand volume for the Terai region in southern Nepal. To create the forest cover map, we used a combination of Landsat TM satellite data and visual interpretation data, i.e., a sample grid of visual interpretation plots for which we obtained the land use classification according to the FAO standard. These visual interpretation plots together with the field plots for volume mapping originate from an operative forest inventory project, i.e., the Forest Resource Assessment of Nepal (FRA Nepal project. The field plots were also used in checking the classification accuracy. MODIS satellite data were used as a reference in a local correction approach conducted for the relative calibration of Landsat TM images. This study applied a non-parametric k-nearest neighbor technique (k-NN to the forest cover and volume mapping. A tree height prediction approach based on a nonlinear, mixed-effects (NLME modeling procedure is presented in the Appendix. The MODIS image data performed well as reference data for the calibration approach applied to make the Landsat image mosaic. The agreement between the forest cover map and the field observed values of forest cover was substantial in Western Terai (KHAT 0.745 and strong in Eastern Terai (KHAT 0.825. The forest cover and volume maps that were estimated using the k-NN method and the inventory data from the FRA Nepal project are already appropriate and valuable data for research purposes and for the planning of forthcoming forest inventories. Adaptation of the methods and techniques was carried out using Open Source software tools.

  3. Family Structure, Maternal Dating, and Sexual Debut: Extending the Conceptualization of Instability.

    Science.gov (United States)

    Zito, Rena Cornell; De Coster, Stacy

    2016-05-01

    Family structure influences the risk of early onset of sexual intercourse. This study proposes that the family structures associated with risk-single-mother, step-parent, and cohabiting-influence early sexual debut due to family instability, including shifts in family structure and maternal dating, which can undermine parental control and transmit messages about the acceptability of nonmarital sex. Previous research has not considered maternal dating as a component of family instability, assuming single mothers who date and those who do not date experience comparable levels of family disruption and transmit similar messages about the acceptability of nonmarital sex. Hypotheses are assessed using logistic regression models predicting the odds of early onset of sexual intercourse among 9959 respondents (53 % female, 47 % male) from the National Longitudinal Study of Adolescent to Adult Health. Respondents were ages 12-17 at the first wave of data collection and 18-26 at the third wave, when respondents reported the age at which they first had sexual intercourse. Results show that maternal dating is a source of family instability with repercussions for early sexual debut. Parental control and permissive attitudes towards teenage sex and pregnancy link at-risk family structures and maternal dating to early sexual initiation among females, though these variables do not fully explain family structure and maternal dating effects. Among males, the influence of maternal dating on early sexual debut is fully explained by the learning of permissive sexual attitudes.

  4. Selection of imagery data and classifiers for mapping Brazilian semideciduous Atlantic forests

    NARCIS (Netherlands)

    Carvalho, L.M.T.; Clevers, J.G.P.W.; Skidmore, A.K.; Jong, de S.M.

    2004-01-01

    This paper presents a case study on the use of features derived from remote sensing data for mapping the highly fragmented semideciduous Atlantic forest in Brazil. Innovative aspects of this research include the evaluation of different feature sets in order to improve land cover mapping. The feature

  5. UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis

    Directory of Open Access Journals (Sweden)

    Quanlong Feng

    2015-01-01

    Full Text Available Unmanned aerial vehicle (UAV remote sensing has great potential for vegetation mapping in complex urban landscapes due to the ultra-high resolution imagery acquired at low altitudes. Because of payload capacity restrictions, off-the-shelf digital cameras are widely used on medium and small sized UAVs. The limitation of low spectral resolution in digital cameras for vegetation mapping can be reduced by incorporating texture features and robust classifiers. Random Forest has been widely used in satellite remote sensing applications, but its usage in UAV image classification has not been well documented. The objectives of this paper were to propose a hybrid method using Random Forest and texture analysis to accurately differentiate land covers of urban vegetated areas, and analyze how classification accuracy changes with texture window size. Six least correlated second-order texture measures were calculated at nine different window sizes and added to original Red-Green-Blue (RGB images as ancillary data. A Random Forest classifier consisting of 200 decision trees was used for classification in the spectral-textural feature space. Results indicated the following: (1 Random Forest outperformed traditional Maximum Likelihood classifier and showed similar performance to object-based image analysis in urban vegetation classification; (2 the inclusion of texture features improved classification accuracy significantly; (3 classification accuracy followed an inverted U relationship with texture window size. The results demonstrate that UAV provides an efficient and ideal platform for urban vegetation mapping. The hybrid method proposed in this paper shows good performance in differentiating urban vegetation mapping. The drawbacks of off-the-shelf digital cameras can be reduced by adopting Random Forest and texture analysis at the same time.

  6. Regional mapping of forest canopy water content and biomass using AIRSAR images over BOREAS study area

    Science.gov (United States)

    Saatchi, Sasan; Rignot, Eric; Vanzyl, Jakob

    1995-01-01

    In recent years, monitoring vegetation biomass over various climate zones has become the primary focus of several studies interested in assessing the role of the ecosystem responses to climate change and human activities. Airborne and spaceborne Synthetic Aperture Radar (SAR) systems provide a useful tool to directly estimate biomass due to its sensitivity to structural and moisture characteristics of vegetation canopies. Even though the sensitivity of SAR data to total aboveground biomass has been successfully demonstrated in many controlled experiments over boreal forests and forest plantations, so far, no biomass estimation algorithm has been developed. This is mainly due to the fact that the SAR data, even at lowest frequency (P-band) saturates at biomass levels of about 200 tons/ha, and the structure and moisture information in the SAR signal forces the estimation algorithm to be forest type dependent. In this paper, we discuss the development of a hybrid forest biomass algorithm which uses a SAR derived land cover map in conjunction with a forest backscatter model and an inversion algorithm to estimate forest canopy water content. It is shown that unlike the direct biomass estimation from SAR data, the estimation of water content does not depend on the seasonal and/or environmental conditions. The total aboveground biomass can then be derived from canopy water content for each type of forest by incorporating other ecological information. Preliminary results from this technique over several boreal forest stands indicate that (1) the forest biomass can be estimated with reasonable accuracy, and (2) the saturation level of the SAR signal can be enhanced by separating the crown and trunk biomass in the inversion algorithm. We have used the JPL AIRSAR data over BOREAS southern study area to test the algorithm and to generate regional scale water content and biomass maps. The results are compared with ground data and the sources of errors are discussed. Several SAR

  7. Next-generation forest change mapping across the United States: the landscape change monitoring system (LCMS)

    Science.gov (United States)

    Sean P. Healey; Warren B. Cohen; Yang Zhiqiang; Ken Brewer; Evan Brooks; Noel Gorelick; Mathew Gregory; Alexander Hernandez; Chengquan Huang; Joseph Hughes; Robert Kennedy; Thomas Loveland; Kevin Megown; Gretchen Moisen; Todd Schroeder; Brian Schwind; Stephen Stehman; Daniel Steinwand; James Vogelmann; Curtis Woodcock; Limin Yang; Zhe. Zhu

    2015-01-01

    Forest change information is critical in forest planning, ecosystem modeling, and in updating forest condition maps. The Landsat satellite platform has provided consistent observations of the world’s ecosystems since 1972. A number of innovative change detection algorithms have been developed to use the Landsat archive to identify and characterize forest change. The...

  8. Assessment of Above-Ground Biomass of Borneo Forests through a New Data-Fusion Approach Combining Two Pan-Tropical Biomass Maps

    Directory of Open Access Journals (Sweden)

    Andreas Langner

    2015-08-01

    Full Text Available This study investigates how two existing pan-tropical above-ground biomass (AGB maps (Saatchi 2011, Baccini 2012 can be combined to derive forest ecosystem specific carbon estimates. Several data-fusion models which combine these AGB maps according to their local correlations with independent datasets such as the spectral bands of SPOT VEGETATION imagery are analyzed. Indeed these spectral bands convey information about vegetation type and structure which can be related to biomass values. Our study area is the island of Borneo. The data-fusion models are evaluated against a reference AGB map available for two forest concessions in Sabah. The highest accuracy was achieved by a model which combines the AGB maps according to the mean of the local correlation coefficients calculated over different kernel sizes. Combining the resulting AGB map with a new Borneo land cover map (whose overall accuracy has been estimated at 86.5% leads to average AGB estimates of 279.8 t/ha and 233.1 t/ha for forests and degraded forests respectively. Lowland dipterocarp and mangrove forests have the highest and lowest AGB values (305.8 t/ha and 136.5 t/ha respectively. The AGB of all natural forests amounts to 10.8 Gt mainly stemming from lowland dipterocarp (66.4%, upper dipterocarp (10.9% and peat swamp forests (10.2%. Degraded forests account for another 2.1 Gt of AGB. One main advantage of our approach is that, once the best fitting data-fusion model is selected, no further AGB reference dataset is required for implementing the data-fusion process. Furthermore, the local harmonization of AGB datasets leads to more spatially precise maps. This approach can easily be extended to other areas in Southeast Asia which are dominated by lowland dipterocarp forest, and can be repeated when newer or more accurate AGB maps become available.

  9. A simple algorithm for large-scale mapping of evergreen forests in tropical America, Africa and Asia

    Science.gov (United States)

    Xiangming Xiao; Chandrashekhar M. Biradar; Christina Czarnecki; Tunrayo Alabi; Michael Keller

    2009-01-01

    The areal extent and spatial distribution of evergreen forests in the tropical zones are important for the study of climate, carbon cycle and biodiversity. However, frequent cloud cover in the tropical regions makes mapping evergreen forests a challenging task. In this study we developed a simple and novel mapping algorithm that is based on the temporal profile...

  10. Cartographic standards to improve maps produced by the Forest Inventory and Analysis program

    Science.gov (United States)

    Charles H. (Hobie) Perry; Mark D. Nelson

    2009-01-01

    The Forest Service, U.S. Department of Agriculture's Forest Inventory and Analysis (FIA) program is incorporating an increasing number of cartographic products in reports, publications, and presentations. To create greater quality and consistency within the national FIA program, a Geospatial Standards team developed cartographic design standards for FIA map...

  11. Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010

    OpenAIRE

    Yuanwei Qin; Xiangming Xiao; Jinwei Dong; Geli Zhang; Partha Sarathi Roy; Pawan Kumar Joshi; Hammad Gilani; Manchiraju Sri Ramachandra Murthy; Cui Jin; Jie Wang; Yao Zhang; Bangqian Chen; Michael Angelo Menarguez; Chandrashekhar M. Biradar; Rajen Bajgain

    2016-01-01

    Extensive forest changes have occurred in monsoon Asia, substantially affecting climate, carbon cycle and biodiversity. Accurate forest cover maps at fine spatial resolutions are required to qualify and quantify these effects. In this study, an algorithm was developed to map forests in 2010, with the use of structure and biomass information from the Advanced Land Observation System (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) mosaic dataset and the phenological information fro...

  12. Age at sexual debut in South Africa | Bakilana | African Journal of ...

    African Journals Online (AJOL)

    It is important to understand the age at which sexual relations start in designing HIV prevention strategies. Most studies on age of sexual activity of young people provide estimated percentages of those that are sexually active in specific age groups, and tend analysing data concerning sexual debut. This study considers the ...

  13. An Effort to Map and Monitor Baldcypress Forest Areas in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

    Science.gov (United States)

    Spruce, Joseph P.; Sader, Steve; Smoot, James

    2012-01-01

    This presentation discusses a collaborative project to develop, test, and demonstrate baldcypress forest mapping and monitoring products for aiding forest conservation and restoration in coastal Louisiana. Low lying coastal forests in the region are being negatively impacted by multiple factors, including subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, annual insect-induced forest defoliation, timber harvesting, and conversion to urban land uses. Coastal baldcypress forests provide invaluable ecological services in terms of wildlife habitat, forest products, storm buffers, and water quality benefits. Before this project, current maps of baldcypress forest concentrations and change did not exist or were out of date. In response, this project was initiated to produce: 1) current maps showing the extent and location of baldcypress dominated forests; and 2) wetland forest change maps showing temporary and persistent disturbance and loss since the early 1970s. Project products are being developed collaboratively with multiple state and federal agencies. Products are being validated using available reference data from aerial, satellite, and field survey data. Results include Landsat TM- based classifications of baldcypress in terms of cover type and percent canopy cover. Landsat MSS data was employed to compute a circa 1972 classification of swamp and bottomland hardwood forest types. Landsat data for 1972-2010 was used to compute wetland forest change products. MODIS-based change products were applied to view and assess insect-induced swamp forest defoliation. MODIS, Landsat, and ASTER satellite data products were used to help assess hurricane and flood impacts to coastal wetland forests in the region.

  14. Mapping Fuels on the Okanogan and Wenatchee National Forests

    Science.gov (United States)

    Crystal L. Raymond; Lara-Karena B. Kellogg; Donald McKenzie

    2006-01-01

    Resource managers need spatially explicit fuels data to manage fire hazard and evaluate the ecological effects of wildland fires and fuel treatments. For this study, fuels were mapped on the Okanogan and Wenatchee National Forests (OWNF) using a rule-based method and the Fuels Characteristic Classification System (FCCS). The FCCS classifies fuels based on their...

  15. Mapping Distinct Forest Types Improves Overall Forest Identification Based on Multi-Spectral Landsat Imagery for Myanmar’s Tanintharyi Region

    Directory of Open Access Journals (Sweden)

    Grant Connette

    2016-10-01

    Full Text Available We investigated the use of multi-spectral Landsat OLI imagery for delineating mangrove, lowland evergreen, upland evergreen and mixed deciduous forest types in Myanmar’s Tanintharyi Region and estimated the extent of degraded forest for each unique forest type. We mapped a total of 16 natural and human land use classes using both a Random Forest algorithm and a multivariate Gaussian model while considering scenarios with all natural forest classes grouped into a single intact or degraded category. Overall, classification accuracy increased for the multivariate Gaussian model with the partitioning of intact and degraded forest into separate forest cover classes but slightly decreased based on the Random Forest classifier. Natural forest cover was estimated to be 80.7% of total area in Tanintharyi. The most prevalent forest types are upland evergreen forest (42.3% of area and lowland evergreen forest (21.6%. However, while just 27.1% of upland evergreen forest was classified as degraded (on the basis of canopy cover <80%, 66.0% of mangrove forest and 47.5% of the region’s biologically-rich lowland evergreen forest were classified as degraded. This information on the current status of Tanintharyi’s unique forest ecosystems and patterns of human land use is critical to effective conservation strategies and land-use planning.

  16. Quantifying and mapping spatial variability in simulated forest plots

    Science.gov (United States)

    Gavin R. Corral; Harold E. Burkhart

    2016-01-01

    We used computer simulations to test the efficacy of multivariate statistical methods to detect, quantify, and map spatial variability of forest stands. Simulated stands were developed of regularly-spaced plantations of loblolly pine (Pinus taeda L.). We assumed no affects of competition or mortality, but random variability was added to individual tree characteristics...

  17. Advancing the quantification of humid tropical forest cover loss with multi-resolution optical remote sensing data: Sampling & wall-to-wall mapping

    Science.gov (United States)

    Broich, Mark

    Humid tropical forest cover loss is threatening the sustainability of ecosystem goods and services as vast forest areas are rapidly cleared for industrial scale agriculture and tree plantations. Despite the importance of humid tropical forest in the provision of ecosystem services and economic development opportunities, the spatial and temporal distribution of forest cover loss across large areas is not well quantified. Here I improve the quantification of humid tropical forest cover loss using two remote sensing-based methods: sampling and wall-to-wall mapping. In all of the presented studies, the integration of coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data enable advances in quantifying forest cover loss in the humid tropics. Imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used as the source of coarse spatial resolution, high temporal resolution data and imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor are used as the source of moderate spatial, low temporal resolution data. In a first study, I compare the precision of different sampling designs for the Brazilian Amazon using the annual deforestation maps derived by the Brazilian Space Agency for reference. I show that sampling designs can provide reliable deforestation estimates; furthermore, sampling designs guided by MODIS data can provide more efficient estimates than the systematic design used for the United Nations Food and Agricultural Organization Forest Resource Assessment 2010. Sampling approaches, such as the one demonstrated, are viable in regions where data limitations, such as cloud contamination, limit exhaustive mapping methods. Cloud-contaminated regions experiencing high rates of change include Insular Southeast Asia, specifically Indonesia and Malaysia. Due to persistent cloud cover, forest cover loss in Indonesia has only been mapped at a 5-10 year interval using photo interpretation of single

  18. Mapping tropical forest trees using high-resolution aerial digital photographs

    NARCIS (Netherlands)

    Garzon-Lopez, C.X.; Bohlman, S.A.; Olff, H.; Jansen, P.A.

    2013-01-01

    The spatial arrangement of tree species is a key aspect of community ecology. Because tree species in tropical forests occur at low densities, it is logistically challenging to measure distributions across large areas. In this study, we evaluated the potential use of canopy tree crown maps, derived

  19. Evaluation of three classifiers in mapping forest stand types using ...

    African Journals Online (AJOL)

    EJIRO

    applied for classification of the image. Supervised classification technique using maximum likelihood algorithm is the most commonly and widely used method for land cover classification (Jia and Richards, 2006). In Australia, the maximum likelihood classifier was effectively used to map different forest stand types with high.

  20. Sex and sexual orientation disparities in adverse childhood experiences and early age at sexual debut in the United States: Results from a nationally representative sample☆

    OpenAIRE

    Brown, Monique J.; Masho, Saba W.; Perera, Robert A.; Mezuk, Briana; Cohen, Steven A.

    2015-01-01

    Adverse childhood experiences (ACEs) have been linked to early sexual debut, which has been found to be associated with multiple adverse health outcomes. Sexual minorities and men tend to have earlier sexual debut compared to heterosexual populations and women, respectively. However, studies examining the association between ACEs and early sexual debut among men and sexual minorities are lacking. The aim of this study was to examine the sex and sexual orientation disparities in the associatio...

  1. Sex and sexual orientation disparities in adverse childhood experiences and early age at sexual debut in the United States: Results from a nationally representative sample☆

    Science.gov (United States)

    Brown, Monique J.; Masho, Saba W.; Perera, Robert A.; Mezuk, Briana; Cohen, Steven A.

    2015-01-01

    Adverse childhood experiences (ACEs) have been linked to early sexual debut, which has been found to be associated with multiple adverse health outcomes. Sexual minorities and men tend to have earlier sexual debut compared to heterosexual populations and women, respectively. However, studies examining the association between ACEs and early sexual debut among men and sexual minorities are lacking. The aim of this study was to examine the sex and sexual orientation disparities in the association between ACEs and age at sexual debut. Data were obtained from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions. Logistic and linear regression model were used to obtain crude and adjusted estimates and 95% confidence intervals adjusting for age, race/ethnicity, income, education, insurance and marital status for the association between ACEs (neglect, physical/psychological abuse, sexual abuse, parental violence, and parental incarceration and psychopathology) and early sexual debut. Analyses were stratified by sex and sexual orientation. Larger effect estimates depicting the association between ACEs and sexual debut were seen for women compared to men, and among sexual minorities, particularly among men who have sex with men (MSM) and women who have sex with women (WSW), compared to heterosexuals. Sexual health education programs with a focus on delaying sexual debut among children and adolescents should also consider addressing ACEs, such as neglect, physical, psychological and sexual abuse, witnessing parental violence, and parental incarceration and psychopathology. Public health practitioners, researchers and sexual health education curriculum coordinators should consider these differences by sex and sexual orientation when designing these programs. PMID:25804435

  2. Mapping Forest Fire Susceptibility in Temperate Mountain Areas with Expert Knowledge. A Case Study from Iezer Mountains, Romanian Carpathians

    Science.gov (United States)

    Mihai, Bogdan; Savulescu, Ionut

    2014-05-01

    Forest fires in Romanian Carpathians became a frequent phenomenon during the last decade, although local climate and other environmental features did not create typical conditions. From 2004, forest fires affect in Romania more than 100 hectares/year of different forest types (deciduous and coniferous). Their magnitude and frequency are not known, since a historical forest fire inventory does not exist (only press papers and local witness for some selected events). Forest fires features the summer dry periods but there are dry autumns and early winter periods with events of different magnitudes. The application we propose is based on an empirical modeling of forest fire susceptibility in a typical mountain area from the Southern Carpathians, the Iezer Mountains (2462 m). The study area features almost all the altitudinal vegetation zones of the European temperate mountains, from the beech zone, to the coniferous zone, the subalpine and the alpine zones (Mihai et al., 2007). The analysis combines GIS and remote sensing models (Chuvieco et al., 2012), starting from the ideas that forest fires are featured by the ignition zones and then by the fire propagation zones. The first data layer (ignition zones) is the result of the crossing between the ignition factors: lightning - points of multitemporal occurence and anthropogenic activities (grazing, tourism and traffic) and the ignition zones (forest fuel zonation - forest stands, soil cover and topoclimatic factor zonation). This data is modelled from different sources: the MODIS imagery fire product (Hantson et al., 2012), detailed topographic maps, multitemporal orthophotos at 0.5 m resolution, Landsat multispectral imagery, forestry cadastre maps, detailed soil maps, meteorological data (the WorldClim digital database) as well as the field survey (mapping using GPS and local observation). The second data layer (fire propagation zones) is the result of the crossing between the forest fuel zonation, obtained with the

  3. Acute external otitis as debut of acute myeloid leukemia - A case and review of the literature.

    Science.gov (United States)

    Slengerik-Hansen, Joachim; Ovesen, Therese

    2018-03-01

    Acute leukemia is a well known childhood cancer. The relation between leukemia and otological symptoms has long been established but is highly rare as a debut symptom of leukemia. External otitis is a common condition affecting many children, and most cases are successively treated with topical medicine. Here we present a child with acute external otitis later shown to be the debut symptom of acute myeloid leukemia, to our knowledge the first specific case described. We have reviewed the literature to find red flags for suspicion of severe disease in case of acute external otitis. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Rapid Land Cover Map Updates Using Change Detection and Robust Random Forest Classifiers

    Directory of Open Access Journals (Sweden)

    Konrad J. Wessels

    2016-10-01

    Full Text Available The paper evaluated the Landsat Automated Land Cover Update Mapping (LALCUM system designed to rapidly update a land cover map to a desired nominal year using a pre-existing reference land cover map. The system uses the Iteratively Reweighted Multivariate Alteration Detection (IRMAD to identify areas of change and no change. The system then automatically generates large amounts of training samples (n > 1 million in the no-change areas as input to an optimized Random Forest classifier. Experiments were conducted in the KwaZulu-Natal Province of South Africa using a reference land cover map from 2008, a change mask between 2008 and 2011 and Landsat ETM+ data for 2011. The entire system took 9.5 h to process. We expected that the use of the change mask would improve classification accuracy by reducing the number of mislabeled training data caused by land cover change between 2008 and 2011. However, this was not the case due to exceptional robustness of Random Forest classifier to mislabeled training samples. The system achieved an overall accuracy of 65%–67% using 22 detailed classes and 72%–74% using 12 aggregated national classes. “Water”, “Plantations”, “Plantations—clearfelled”, “Orchards—trees”, “Sugarcane”, “Built-up/dense settlement”, “Cultivation—Irrigated” and “Forest (indigenous” had user’s accuracies above 70%. Other detailed classes (e.g., “Low density settlements”, “Mines and Quarries”, and “Cultivation, subsistence, drylands” which are required for operational, provincial-scale land use planning and are usually mapped using manual image interpretation, could not be mapped using Landsat spectral data alone. However, the system was able to map the 12 national classes, at a sufficiently high level of accuracy for national scale land cover monitoring. This update approach and the highly automated, scalable LALCUM system can improve the efficiency and update rate of regional land

  5. Mapping Forest Species Composition Using Imaging Spectrometry and Airborne Laser Scanner Data

    Science.gov (United States)

    Torabzadeh, H.; Morsdorf, F.; Leiterer, R.; Schaepman, M. E.

    2013-09-01

    Accurate mapping of forest species composition is an important aspect of monitoring and management planning related to ecosystem functions and services associated with water refinement, carbon sequestration, biodiversity, and wildlife habitats. Although different vegetation species often have unique spectral signatures, mapping based on spectral reflectance properties alone is often an ill-posed problem, since the spectral signature is as well influenced by age, canopy gaps, shadows and background characteristics. Thus, reducing the unknown variation by knowing the structural parameters of different species should improve determination procedures. In this study we combine imaging spectrometry (IS) and airborne laser scanning (ALS) data of a mixed needle and broadleaf forest to differentiate tree species more accurately as single-instrument data could do. Since forest inventory data in dense forests involve uncertainties, we tried to refine them by using individual tree crowns (ITC) position and shape, which derived from ALS data. Comparison of the extracted spectra from original field data and the modified one shows how ALS-derived shape and position of ITCs can improve separablity of the different species. The spatially explicit information layers containing both the spectral and structural components from the IS and ALS datasets were then combined by using a non-parametric support vector machine (SVM) classifier.

  6. Mapping the Holocene forest formations with the use of key climate indicators – heat and moisture

    Directory of Open Access Journals (Sweden)

    S. K. Farber

    2017-12-01

    Full Text Available The article deals with the methodology of mapping the Holocene forest formations on the basis of the DEM and the key indicators of the climate – heat and moisture. The work is carried out by means of GIS. The test site is located within the boundaries of the axial West Sayan district of mountain taiga forests, which ensures homogeneity of natural and climatic conditions. Stages of the method: creation of rasters on groups of absolute heights, exposures and inclinations with their subsequent combination into a single Combine raster; obtaining the regularities of spatial distribution of heat and moisture and their representation in the form of rasters (digital models; and interactive mapping of the Holocene forests with various combinations of heat and moisture. The use of Combine raster makes it possible to refuse to use any other contours as – landscape, geomorphological, forest inventory. To determine parameters of climatic boundaries of forest formations, the types of forests are linked to the heat and moisture indicators. As a result of linking, a graphic image is produced, where forest formations and their productivity are located in a certain order. The mapping technique involves creating a dBASE table with a field containing information about forest formations. The row-wise change in the records of forest formations as they move to other values of heat and moisture is performed interactively. Each next combination of heat and moisture on maps corresponds to a certain distribution of forest formations and site productivity (bonitet classes. (1900 ± 65 years ago the river valleys were treeless, flat meadows occupied meadows, and the slopes were steppes. As the hypsometric level increases, larch stands, spruce-Siberian stone pine with an admixture of larch, Siberian stone pine-larch with an admixture of fir, and the Siberian stone pine formations appear. (2200 ± 100 years ago the tundra prevailed. Larch forests of V–Va classes of

  7. Snow-covered Landsat time series stacks improve automated disturbance mapping accuracy in forested landscapes

    Science.gov (United States)

    Kirk M. Stueve; Ian W. Housman; Patrick L. Zimmerman; Mark D. Nelson; Jeremy B. Webb; Charles H. Perry; Robert A. Chastain; Dale D. Gormanson; Chengquan Huang; Sean P. Healey; Warren B. Cohen

    2011-01-01

    Accurate landscape-scale maps of forests and associated disturbances are critical to augment studies on biodiversity, ecosystem services, and the carbon cycle, especially in terms of understanding how the spatial and temporal complexities of damage sustained from disturbances influence forest structure and function. Vegetation change tracker (VCT) is a highly automated...

  8. Sex and sexual orientation disparities in adverse childhood experiences and early age at sexual debut in the United States: results from a nationally representative sample.

    Science.gov (United States)

    Brown, Monique J; Masho, Saba W; Perera, Robert A; Mezuk, Briana; Cohen, Steven A

    2015-08-01

    Adverse childhood experiences (ACEs) have been linked to early sexual debut, which has been found to be associated with multiple adverse health outcomes. Sexual minorities and men tend to have earlier sexual debut compared to heterosexual populations and women, respectively. However, studies examining the association between ACEs and early sexual debut among men and sexual minorities are lacking. The aim of this study was to examine the sex and sexual orientation disparities in the association between ACEs and age at sexual debut. Data were obtained from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions. Logistic and linear regression models were used to obtain crude and adjusted estimates and 95% confidence intervals adjusting for age, race/ethnicity, income, education, insurance and marital status for the association between ACEs (neglect, physical/psychological abuse, sexual abuse, parental violence, and parental incarceration and psychopathology) and early sexual debut. Analyses were stratified by sex and sexual orientation. Larger effect estimates depicting the association between ACEs and sexual debut were seen for women compared to men, and among sexual minorities, particularly among men who have sex with men (MSM) and women who have sex with women (WSW), compared to heterosexuals. Sexual health education programs with a focus on delaying sexual debut among children and adolescents should also consider addressing ACEs, such as neglect, physical, psychological and sexual abuse, witnessing parental violence, and parental incarceration and psychopathology. Public health practitioners, researchers and sexual health education curriculum coordinators should consider these differences by sex and sexual orientation when designing these programs. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Relasphone—Mobile and Participative In Situ Forest Biomass Measurements Supporting Satellite Image Mapping

    Directory of Open Access Journals (Sweden)

    Matthieu Molinier

    2016-10-01

    Full Text Available Due to the high cost of traditional forest plot measurements, the availability of up-to-date in situ forest inventory data has been a bottleneck for remote sensing image analysis in support of the important global forest biomass mapping. Capitalizing on the proliferation of smartphones, citizen science is a promising approach to increase spatial and temporal coverages of in situ forest observations in a cost-effective way. Digital cameras can be used as a relascope device to measure basal area, a forest density variable that is closely related to biomass. In this paper, we present the Relasphone mobile application with extensive accuracy assessment in two mixed forest sites from different biomes. Basal area measurements in Finland (boreal zone were in good agreement with reference forest inventory plot data on pine ( R 2 = 0 . 75 , R M S E = 5 . 33 m 2 /ha, spruce ( R 2 = 0 . 75 , R M S E = 6 . 73 m 2 /ha and birch ( R 2 = 0 . 71 , R M S E = 4 . 98 m 2 /ha, with total relative R M S E ( % = 29 . 66 % . In Durango, Mexico (temperate zone, Relasphone stem volume measurements were best for pine ( R 2 = 0 . 88 , R M S E = 32 . 46 m 3 /ha and total stem volume ( R 2 = 0 . 87 , R M S E = 35 . 21 m 3 /ha. Relasphone data were then successfully utilized as the only reference data in combination with optical satellite images to produce biomass maps. The Relasphone concept has been validated for future use by citizens in other locations.

  10. North American forest disturbance mapped from a decadal Landsat record

    Science.gov (United States)

    Jeffrey G. Masek; Chengquan Huang; Robert Wolfe; Warren Cohen; Forrest Hall; Jonathan Kutler; Peder. Nelson

    2008-01-01

    Forest disturbance and recovery are critical ecosystem processes, but the spatial pattern of disturbance has never been mapped across North America. The LEDAPS (Landsat Ecosystem Disturbance Adaptive Processing System) project has assembled a wall-to-wall record of stand-clearing disturbance (clearcut harvest, fire) for the United States and Canada for the period 1990-...

  11. Potential of Pest and Host Phenological Data in the Attribution of Regional Forest Disturbance Detection Maps According to Causal Agent

    Science.gov (United States)

    Spruce, Joseph; Hargrove, William; Norman Steve; Christie, William

    2014-01-01

    Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced since 2010 for the conterminous U.S., as part of the on-line ForWarn national forest threat early warning system. The latter has been used by the forest health community to identify and track many regional forest disturbances caused by multiple biotic and abiotic damage agents. Attribution of causal agents for detected disturbances has been a goal since project initiation in 2006. Combined with detailed cover type maps, geospatial pest phenology data offer a potential means for narrowing the candidate causal agents responsible for a given biotic disturbance. U.S. Aerial Detection Surveys (ADS) employ such phenology data. Historic ADS products provide general locational data on recent insect-induced forest type specific disturbances that may help in determining candidate causal agents for MODIS-based disturbance maps, especially when combined with other historic geospatial disturbance data (e.g., wildfire burn scars and drought maps). Historic ADS disturbance detection polygons can show severe and extensive regional forest disturbances, though they also can show polygons with sparsely scattered or infrequent disturbances. Examples will be discussed that use various historic disturbance data to help determine potential causes of MODIS-detected regional forest disturbance anomalies.

  12. DEVELOPING AN INDEX FOR FOREST PRODUCTIVITY MAPPING - A CASE STUDY FOR MARITIME PINE PRODUCTION REGULATION IN PORTUGAL

    Directory of Open Access Journals (Sweden)

    Susana Mestre

    2018-02-01

    Full Text Available ABSTRACT Productivity is very dependent on the environmental and biotic factors present at the site where the forest species of interest is present. Forest site productivity is usually assessed using empirical models applied to inventory data providing discrete predictions. While the use of GIS-based models enables building a site productivity distribution map. Therefore, the aim of this study was to derive a productivity index using multivariate statistics and coupled GIS-geostatistics to obtain a forest productivity map. To that end, a study area vastly covered by naturally regenerated forests of maritime pine in central Portugal was used. First, a productivity index (PI was built based on Factorial Correspondence Analysis (FCA by incorporating a classical site index for the species and region (Sh25 - height index model and GIS-derived environmental variables (slope and aspect. After, the PI map was obtained by multi-Gaussian kriging and used as a GIS layer to evaluate maritime pine areas by productivity class (e.g., low, intermediate and high. In the end, the area control method was applied to assess the size and the number of compartments to establish by productivity class. The management compartments of equal productivity were digitized as GIS layer and organized in a temporal progression of stands’ age regularly available for cutting each year during a 50-year schedule. The methodological approach developed in this study proved that can be used to build forest productivity maps which are crucial tools to support forest production regulation.

  13. Forest mapping and change analysis, using satellite imagery in Zagros mountain Iran, Islamic Republic o

    International Nuclear Information System (INIS)

    Torahi, A.A.

    2013-01-01

    A methodology to map and monitor land cover change using multi temporal Landsat Thematic Mapper (TM) and ASTER data in Zagros mountains of Iran for 1990, 1998, and 2006 was developed. Land- use/cover mapping is achieved through interpretation of Landsat TM satellite images of 1990, 1998 and TERRA-ASTER image of 2006 using ENVI 4.3. Basedon the Anderson land-use/cover classification system, land-use and land-covers are classified as forest land, range land, water bodies, agricultural land and residential land.The unsupervised image classification method was carried out prior to field visit, in order to determine strata for ground truth. Fieldwork was carried out to collect data for training and validating land use/cover interpretation from satellite image of 2006, and for qualitative description of the characteristics of each land use/cover class. The land - use/cover maps of 1990,1998 and 2006 were produced by using supervised image classification technique based on the Maximum Likelihood Classifier (MLC) and 132 training samples. Error matrices as cross-tabulations of the mapped class vs. the reference class were used to assess classification accuracy. Overall accuracy, users and produce accuracies, and the Kappa statistic were then derived from the error matrices. A multi-date post-classification comparison change detection algorithm was used to determine changes in land cover in three intervals, 1990,1998, 1998, 2006 and 1990, 2006.To evaluate the maps change for the 1990 to 2006 interval, areas classified as change and no-change were randomly sampled and checked whether they were correctly classified. The maps showed that between 1990 and 2006 the amount of forest land decreased from 67% to 38.5% of the total area, while rangelands, agriculture, settlement and surface water increased from 30.8% to 45%, 1.2% to.0%, 0.3% to 7.5% and 0.6% to 1.8%, respectively.In 1990,1998 and 2006, the area was dominated by dense forest (35.9%, 28.9%, 29.3%), open forest and

  14. Mapping Plant Diversity and Composition Across North Carolina Piedmont Forest Landscapes Using Lidar-Hyperspectral Remote Sensing

    Science.gov (United States)

    Hakkenberg, Christopher R.

    Forest modification, from local stress to global change, has given rise to efforts to model, map, and monitor critical properties of forest communities like structure, composition, and diversity. Predictive models based on data from spatially-nested field plots and LiDAR-hyperspectral remote sensing systems are one particularly effective means towards the otherwise prohibitively resource-intensive task of consistently characterizing forest community dynamics at landscape scales. However, to date, most predictive models fail to account for actual (rather than idealized) species and community distributions, are unsuccessful in predicting understory components in structurally and taxonomically heterogeneous forests, and may suffer from diminished predictive accuracy due to incongruity in scale and precision between field plot samples, remotely-sensed data, and target biota of varying size and density. This three-part study addresses these and other concerns in the modeling and mapping of emergent properties of forest communities by shifting the scope of prediction from the individual or taxon to the whole stand or community. It is, after all, at the stand scale where emergent properties like functional processes, biodiversity, and habitat aggregate and manifest. In the first study, I explore the relationship between forest structure (a proxy for successional demographics and resource competition) and tree species diversity in the North Carolina Piedmont, highlighting the empirical basis and potential for utilizing forest structure from LiDAR in predictive models of tree species diversity. I then extend these conclusions to map landscape pattern in multi-scale vascular plant diversity as well as turnover in community-continua at varying compositional resolutions in a North Carolina Piedmont landscape using remotely-sensed LiDAR-hyperspectral estimates of topography, canopy structure, and foliar biochemistry. Recognizing that the distinction between correlation and

  15. Gis-Based Multi-Criteria Decision Analysis for Forest Fire Risk Mapping

    Science.gov (United States)

    Akay, A. E.; Erdoğan, A.

    2017-11-01

    The forested areas along the coastal zone of the Mediterranean region in Turkey are classified as first-degree fire sensitive areas. Forest fires are major environmental disaster that affects the sustainability of forest ecosystems. Besides, forest fires result in important economic losses and even threaten human lives. Thus, it is critical to determine the forested areas with fire risks and thereby minimize the damages on forest resources by taking necessary precaution measures in these areas. The risk of forest fire can be assessed based on various factors such as forest vegetation structures (tree species, crown closure, tree stage), topographic features (slope and aspect), and climatic parameters (temperature, wind). In this study, GIS-based Multi-Criteria Decision Analysis (MCDA) method was used to generate forest fire risk map. The study was implemented in the forested areas within Yayla Forest Enterprise Chiefs at Dursunbey Forest Enterprise Directorate which is classified as first degree fire sensitive area. In the solution process, "extAhp 2.0" plug-in running Analytic Hierarchy Process (AHP) method in ArcGIS 10.4.1 was used to categorize study area under five fire risk classes: extreme risk, high risk, moderate risk, and low risk. The results indicated that 23.81 % of the area was of extreme risk, while 25.81 % was of high risk. The result indicated that the most effective criterion was tree species, followed by tree stages. The aspect had the least effective criterion on forest fire risk. It was revealed that GIS techniques integrated with MCDA methods are effective tools to quickly estimate forest fire risk at low cost. The integration of these factors into GIS can be very useful to determine forested areas with high fire risk and also to plan forestry management after fire.

  16. Integrating Landsat-derived disturbance maps with FIA inventory data: Applications for state-Level forest resource assessments

    Science.gov (United States)

    Sonja Oswalt; Chengquan Huang; Hua Shi; James Vogelmann; Zhiliang Zhu; Samuel N. Goward; John Coulston

    2009-01-01

    Landsat images have been widely used for assessing forest characteristics and dynamics. Recently, significant progress has been made towards indepth exploration of the rich Landsat archive kept by the U.S. Geological Survey to improve our under standing of forest disturbance and recovery processes. In this study, we used Landsat images to map forest disturbances at...

  17. Large-Scale Mapping of Carbon Stocks in Riparian Forests with Self-Organizing Maps and the k-Nearest-Neighbor Algorithm

    Directory of Open Access Journals (Sweden)

    Leonhard Suchenwirth

    2014-07-01

    Full Text Available Among the machine learning tools being used in recent years for environmental applications such as forestry, self-organizing maps (SOM and the k-nearest neighbor (kNN algorithm have been used successfully. We applied both methods for the mapping of organic carbon (Corg in riparian forests due to their considerably high carbon storage capacity. Despite the importance of floodplains for carbon sequestration, a sufficient scientific foundation for creating large-scale maps showing the spatial Corg distribution is still missing. We estimated organic carbon in a test site in the Danube Floodplain based on RapidEye remote sensing data and additional geodata. Accordingly, carbon distribution maps of vegetation, soil, and total Corg stocks were derived. Results were compared and statistically evaluated with terrestrial survey data for outcomes with pure remote sensing data and for the combination with additional geodata using bias and the Root Mean Square Error (RMSE. Results show that SOM and kNN approaches enable us to reproduce spatial patterns of riparian forest Corg stocks. While vegetation Corg has very high RMSEs, outcomes for soil and total Corg stocks are less biased with a lower RMSE, especially when remote sensing and additional geodata are conjointly applied. SOMs show similar percentages of RMSE to kNN estimations.

  18. Mapping Deforestation in North Korea Using Phenology-Based Multi-Index and Random Forest

    Directory of Open Access Journals (Sweden)

    Yihua Jin

    2016-12-01

    Full Text Available Phenology-based multi-index with the random forest (RF algorithm can be used to overcome the shortcomings of traditional deforestation mapping that involves pixel-based classification, such as ISODATA or decision trees, and single images. The purpose of this study was to investigate methods to identify specific types of deforestation in North Korea, and to increase the accuracy of classification, using phenological characteristics extracted with multi-index and random forest algorithms. The mapping of deforestation area based on RF was carried out by merging phenology-based multi-indices (i.e., normalized difference vegetation index (NDVI, normalized difference water index (NDWI, and normalized difference soil index (NDSI derived from MODIS (Moderate Resolution Imaging Spectroradiometer products and topographical variables. Our results showed overall classification accuracy of 89.38%, with corresponding kappa coefficients of 0.87. In particular, for forest and farm land categories with similar phenological characteristic (e.g., paddy, plateau vegetation, unstocked forest, hillside field, this approach improved the classification accuracy in comparison with pixel-based methods and other classes. The deforestation types were identified by incorporating point data from high-resolution imagery, outcomes of image classification, and slope data. Our study demonstrated that the proposed methodology could be used for deciding on the restoration priority and monitoring the expansion of deforestation areas.

  19. Mapping host-species abundance of three major exotic forest pests

    Science.gov (United States)

    Randall S. Morin; Andrew M. Liebhold; Eugene R. Luzader; Andrew J. Lister; Kurt W. Gottschalk; Daniel B. Twardus

    2005-01-01

    Periodically over the last century, forests of the Eastern United States devastated by invasive pests. We used existing data to predict the geographical extent of future damage from beech bark disease (BBD), hemlock woolly adelgid (HWA), and gypsy moth. The distributions of host species of these alien pests were mapped in 1-km2 cells by interpolating host basal area/ha...

  20. A forest map of Southern Africa with the aid of LANDSAT imagery

    CSIR Research Space (South Africa)

    Van der Zel, DW

    1988-01-01

    Full Text Available Even after 300 years of indigenous forest protection as well as 100 years of plantation forestry, no forestry map of South Africa was available. The development and availability of LANDSAT images in the early 1970s opened possibility to use...

  1. Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

    Science.gov (United States)

    Montesano, P. M.; Cook, B. D.; Sun, G.; Simard, M.; Zhang, Z.; Nelson, R. F.; Ranson, K. J.; Lutchke, S.; Blair, J. B.

    2012-01-01

    The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized

  2. Mapping regional patterns of large forest fires in Wildland-Urban Interface areas in Europe.

    Science.gov (United States)

    Modugno, Sirio; Balzter, Heiko; Cole, Beth; Borrelli, Pasquale

    2016-05-01

    Over recent decades, Land Use and Cover Change (LUCC) trends in many regions of Europe have reconfigured the landscape structures around many urban areas. In these areas, the proximity to landscape elements with high forest fuels has increased the fire risk to people and property. These Wildland-Urban Interface areas (WUI) can be defined as landscapes where anthropogenic urban land use and forest fuel mass come into contact. Mapping their extent is needed to prioritize fire risk control and inform local forest fire risk management strategies. This study proposes a method to map the extent and spatial patterns of the European WUI areas at continental scale. Using the European map of WUI areas, the hypothesis is tested that the distance from the nearest WUI area is related to the forest fire probability. Statistical relationships between the distance from the nearest WUI area, and large forest fire incidents from satellite remote sensing were subsequently modelled by logistic regression analysis. The first European scale map of the WUI extent and locations is presented. Country-specific positive and negative relationships of large fires and the proximity to the nearest WUI area are found. A regional-scale analysis shows a strong influence of the WUI zones on large fires in parts of the Mediterranean regions. Results indicate that the probability of large burned surfaces increases with diminishing WUI distance in touristic regions like Sardinia, Provence-Alpes-Côte d'Azur, or in regions with a strong peri-urban component as Catalunya, Comunidad de Madrid, Comunidad Valenciana. For the above regions, probability curves of large burned surfaces show statistical relationships (ROC value > 0.5) inside a 5000 m buffer of the nearest WUI. Wise land management can provide a valuable ecosystem service of fire risk reduction that is currently not explicitly included in ecosystem service valuations. The results re-emphasise the importance of including this ecosystem service

  3. Type of primary education is associated with condom use at sexual debut among Chilean adolescents.

    Science.gov (United States)

    Huneeus, Andrea; Deardorff, Julianna; Lahiff, Maureen; Guendelman, Sylvia

    2014-05-01

    Although condom use in adolescence is related to higher lifetime educational attainment, the association between primary education (from kindergarten to eighth grade) and adolescent sexual behavior is not well understood. This study examined the association between type of school in which primary education was completed-public, charter, or private-and condom use at sexual debut among Chilean adolescents. Drawing on the 2009 Chilean National Youth Survey, a population-based sample of general community youth aged 15 to 29 years, we conducted a study of the 4217 participants who reported onset of sexual activity during adolescence. Bivariate and multple logistic regression was used to examine the relationship between type of primary school attended (60.1% public, 30.3% charter, and 9.6% private) and condom use at sexual debut while controlling for sociodemographic characteristics and sexual behavior. Compared with students who completed their primary education in private or charter schools, students who completed their primary education in public schools had 1.85 (95% confidence interval, 1.12-3.04) and 1.67 (95% confidence interval, 1.26-2.23) higher odds, respectively, of not using condoms at sexual debut. Odds were similar for students living in urban settings, whereas there were too few students attending private schools in rural areas to allow meaningful estimates. Independent of household income, primary schooling is associated with sexual health behaviors among Chilean adolescents living in urban areas and can serve as a target for public health interventions designed to prevent sexually transmitted infections in adolescence.

  4. Mapping tropical dry forest habitats integrating landsat NDVI, Ikonos imagery, and topographic information in the Caribbean island of Mona.

    Science.gov (United States)

    Martinuzzi, Sebastiáin; Gould, William A; Ramos Gonzalez, Olga M; Martinez Robles, Alma; Calle Maldonado, Paulina; Pérez-Buitrago, Néstor; Fumero Caban, José J

    2008-06-01

    Assessing the status of tropical dry forest habitats using remote sensing technologies is one of the research priorities for Neotropical forests. We developed a simple method for mapping vegetation and habitats in a tropical dry forest reserve, Mona Island, Puerto Rico, by integrating the Normalized Difference Vegetation Index (NDVI) from Landsat, topographic information, and high-resolution Ikonos imagery. The method was practical for identifying vegetation types in areas with a great variety of plant communities and complex relief, and can be adapted to other dry forest habitats of the Caribbean Islands. NDVI was useful for identifying the distribution of forests, woodlands, and shrubland, providing a natural representation of the vegetation patterns on the island. The use of Ikonos imagery allowed increasing the number of land cover classes. As a result, sixteen land-cover types were mapped over the 5500 ha area, with a kappa coefficient of accuracy equal to 79%. This map is a central piece for modeling vertebrate species distribution and biodiversity patterns by the Puerto Rico Gap Analysis Project, and it is of great value for assisting research and management actions in the island.

  5. Land use, forest density, soil mapping, erosion, drainage, salinity limitations

    Science.gov (United States)

    Yassoglou, N. J. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. The results of analyses show that it is possible to obtain information of practical significance as follows: (1) A quick and accurate estimate of the proper use of the valuable land can be made on the basis of temporal and spectral characteristics of the land features. (2) A rather accurate delineation of the major forest formations in the test areas was achieved on the basis of spatial and spectral characteristics of the studied areas. The forest stands were separated into two density classes; dense forest, and broken forest. On the basis of ERTS-1 data and the existing ground truth information a rather accurate mapping of the major vegetational forms of the mountain ranges can be made. (3) Major soil formations are mapable from ERTS-1 data: recent alluvial soils; soil on quarternary deposits; severely eroded soil and lithosol; and wet soils. (4) An estimation of cost benefits cannot be made accurately at this stage of the investigation. However, a rough estimate of the ratio of the cost for obtaining the same amount information from ERTS-1 data and from conventional operations would be approximately 1:6 to 1:10, in favor of the ERTS-1.

  6. An Automated Approach to Map the History of Forest Disturbance from Insect Mortality and Harvest with Landsat Time-Series Data

    Directory of Open Access Journals (Sweden)

    Christopher S.R. Neigh

    2014-03-01

    Full Text Available Forests contain a majority of the aboveground carbon (C found in ecosystems, and understanding biomass lost from disturbance is essential to improve our C-cycle knowledge. Our study region in the Wisconsin and Minnesota Laurentian Forest had a strong decline in Normalized Difference Vegetation Index (NDVI from 1982 to 2007, observed with the National Ocean and Atmospheric Administration’s (NOAA series of Advanced Very High Resolution Radiometer (AVHRR. To understand the potential role of disturbances in the terrestrial C-cycle, we developed an algorithm to map forest disturbances from either harvest or insect outbreak for Landsat time-series stacks. We merged two image analysis approaches into one algorithm to monitor forest change that included: (1 multiple disturbance index thresholds to capture clear-cut harvest; and (2 a spectral trajectory-based image analysis with multiple confidence interval thresholds to map insect outbreak. We produced 20 maps and evaluated classification accuracy with air-photos and insect air-survey data to understand the performance of our algorithm. We achieved overall accuracies ranging from 65% to 75%, with an average accuracy of 72%. The producer’s and user’s accuracy ranged from a maximum of 32% to 70% for insect disturbance, 60% to 76% for insect mortality and 82% to 88% for harvested forest, which was the dominant disturbance agent. Forest disturbances accounted for 22% of total forested area (7349 km2. Our algorithm provides a basic approach to map disturbance history where large impacts to forest stands have occurred and highlights the limited spectral sensitivity of Landsat time-series to outbreaks of defoliating insects. We found that only harvest and insect mortality events can be mapped with adequate accuracy with a non-annual Landsat time-series. This limited our land cover understanding of NDVI decline drivers. We demonstrate that to capture more subtle disturbances with spectral trajectories

  7. An Automated Approach to Map the History of Forest Disturbance from Insect Mortality and Harvest with Landsat Time-Series Data

    Science.gov (United States)

    Rudasill-Neigh, Christopher S.; Bolton, Douglas K.; Diabate, Mouhamad; Williams, Jennifer J.; Carvalhais, Nuno

    2014-01-01

    Forests contain a majority of the aboveground carbon (C) found in ecosystems, and understanding biomass lost from disturbance is essential to improve our C-cycle knowledge. Our study region in the Wisconsin and Minnesota Laurentian Forest had a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 2007, observed with the National Ocean and Atmospheric Administration's (NOAA) series of Advanced Very High Resolution Radiometer (AVHRR). To understand the potential role of disturbances in the terrestrial C-cycle, we developed an algorithm to map forest disturbances from either harvest or insect outbreak for Landsat time-series stacks. We merged two image analysis approaches into one algorithm to monitor forest change that included: (1) multiple disturbance index thresholds to capture clear-cut harvest; and (2) a spectral trajectory-based image analysis with multiple confidence interval thresholds to map insect outbreak. We produced 20 maps and evaluated classification accuracy with air-photos and insect air-survey data to understand the performance of our algorithm. We achieved overall accuracies ranging from 65% to 75%, with an average accuracy of 72%. The producer's and user's accuracy ranged from a maximum of 32% to 70% for insect disturbance, 60% to 76% for insect mortality and 82% to 88% for harvested forest, which was the dominant disturbance agent. Forest disturbances accounted for 22% of total forested area (7349 km2). Our algorithm provides a basic approach to map disturbance history where large impacts to forest stands have occurred and highlights the limited spectral sensitivity of Landsat time-series to outbreaks of defoliating insects. We found that only harvest and insect mortality events can be mapped with adequate accuracy with a non-annual Landsat time-series. This limited our land cover understanding of NDVI decline drivers. We demonstrate that to capture more subtle disturbances with spectral trajectories, future observations

  8. MODIS snow cover mapping accuracy in a small mountain catchment – comparison between open and forest sites

    Directory of Open Access Journals (Sweden)

    G. Blöschl

    2012-07-01

    Full Text Available Numerous global and regional validation studies have examined MODIS snow mapping accuracy by using measurements at climate stations, which are mainly at open sites. MODIS accuracy in alpine and forested regions is, however, still not well understood. The main objective of this study is to evaluate MODIS (MOD10A1 and MYD10A1 snow cover products in a small experimental catchment by using extensive snow course measurements at open and forest sites. The MODIS accuracy is tested in the Jalovecky creek catchment (northern Slovakia in the period 2000–2011. The results show that the combined Terra and Aqua images enable snow mapping at an overall accuracy of 91.5%. The accuracies at forested, open and mixed land uses at the Červenec sites are 92.7%, 98.3% and 81.8%, respectively. The use of a 2-day temporal filter enables a significant reduction in the number of days with cloud coverage and an increase in overall snow mapping accuracy. In total, the 2-day temporal filter decreases the number of cloudy days from 61% to 26% and increases the snow mapping accuracy to 94%. The results indicate three possible factors leading to misclassification of snow as land: patchy snow cover, limited MODIS geolocation accuracy and mapping algorithm errors. Out of a total of 27 misclassification cases, patchy snow cover, geolocation issues and mapping errors occur in 12, 12 and 3 cases, respectively.

  9. Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US

    Science.gov (United States)

    Schleeweis, Karen; Goward, Samuel N.; Huang, Chengquan; Dwyer, John L.; Dungan, Jennifer L.; Lindsey, Mary A.; Michaelis, Andrew; Rishmawi, Khaldoun; Masek, Jeffery G.

    2016-01-01

    Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.

  10. Fuzzy rule-based landslide susceptibility mapping in Yığılca Forest District (Northwest of Turkey

    Directory of Open Access Journals (Sweden)

    Abdurrahim Aydın

    2016-07-01

    Full Text Available Landslide susceptibility map of Yığılca Forest District was formed based on developed fuzzy rules using GIS-based FuzzyCell software. An inventory of 315 landslides was updated through fieldworks after inventory map previously generated by the authors. Based on the landslide susceptibility mapping study previously made in the same area, for the comparison of two maps, same 8 landslide conditioning parameters were selected and then fuzzified for the landslide susceptibility mapping: land use, lithology, elevation, slope, aspect, distance to streams, distance to roads, and plan curvature. Mamdani model was selected as fuzzy inference system. After fuzzy rules definition, Center of Area (COA was selected as defuzzification method in model. The output of developed model was normalized between 0 and 1, and then divided five classes such as very low, low, moderate, high, and very high. According to developed model based 8 conditioning parameters, landslide susceptibility in Yığılca Forest District varies between 32 and 67 (in range of 0-100 with 0.703 Area Under the Curve (AUC value. According to classified landslide susceptibility map, in Yığılca Forest District, 32.89% of the total area has high and very high susceptibility while 29.59% of the area has low and very low susceptibility and the rest located in moderate susceptibility. The result of developed fuzzy rule based model compared with previously generated landslide map with logistic regression (LR. According to comparison of the results of two studies, higher differences exist in terms of AUC value and dispersion of susceptibility classes. This is because fuzzy rule based model completely depends on how parameters are classified and fuzzified and also depends on how truly the expert composed the rules. Even so, GIS-based fuzzy applications provide very valuable facilities for reasoning, which makes it possible to take into account inaccuracies and uncertainties.

  11. Mapping carbon sequestration in forests at the regional scale - a climate biomonitoring approach by example of Germany

    Energy Technology Data Exchange (ETDEWEB)

    Schroeder, Winfried; Pesch, Roland [University of Vechta, Chair of Landscape Ecology, PO Box. 1553, Vechta (Germany)

    2011-12-15

    The United Nations Framework Convention on Climate Change recognizes carbon (C) fixation in forests as an important contribution for the reduction of atmospheric pollution in terms of greenhouse gases. Spatial differentiation of C sequestration in forests either at the national or at the regional scale is therefore needed for forest planning purposes. Hence, within the framework of the Forest Focus regulation, the aim of this investigation was to statistically analyse factors influencing the C fixation and to use the corresponding associations in terms of a predictive mapping approach at the regional scale by example of the German federal state North Rhine-Westphalia. The results of the methodical scheme outlined in this article should be compared with an already-published approach applied to the same data which were used in the investigation at hand. Site-specific data on C sequestration in humus, forest trees/dead wood and soil from two forest monitoring networks were intersected with available surface information on topography, soil, climate and forestal growing areas and districts. Next, the association between the C sequestration and the influence factors were examined and modelled by linear regression analyses. The resulting regression equations were applied on the surface data to predicatively map the C sequestration for the entire study area. The computations yielded an estimation of 146.7 mio t C sequestered in the forests of North Rhine-Westphalia corresponding to 168.6 t/ha. The calculated values correspond well to according specifications given by the literature. Furthermore, the results are almost identical to those of another pilot study where a different statistical methodology was applied on the same database. Nevertheless, the underlying regression models contribute only a low degree of explanation to the overall variance of the C fixation. This might mainly be due to data quality aspects and missing influence factors in the analyses. In another

  12. Implementation of forest cover and carbon mapping in the Greater Mekong subregion and Malaysia project - A case study of Thailand

    Science.gov (United States)

    Pungkul, S.; Suraswasdi, C.; Phonekeo, V.

    2014-02-01

    The Great Mekong Subregion (GMS) contains one of the world's largest tropical forests and plays a vital role in sustainable development and provides a range of economic, social and environmental benefits, including essential ecosystem services such as climate change mitigation and adaptation. However, the forest in this Subregion is experiencing deforestation rates at high level due to human activities. The reduction of the forest area has negative influence to the environmental and natural resources issues, particularly, more severe disasters have occurred due to global warming and the release of the greenhouse gases. Therefore, in order to conduct forest management in the Subregion efficiently, the Forest Cover and Carbon Mapping in Greater Mekong Subregion and Malaysia project was initialized by the Asia-Pacific Network for Sustainable Forest Management and Rehabilitation (APFNet) with the collaboration of various research institutions including Institute of Forest Resource Information Technique (IFRIT), Chinese Academy of Forestry (CAF) and the countries in Sub region and Malaysia comprises of Cambodia, the People's Republic of China (Yunnan province and Guangxi province), Lao People's Democratic Republic, Malaysia, Myanmar, Thailand, and Viet Nam. The main target of the project is to apply the intensive use of recent satellite remote sensing technology, establishing regional forest cover maps, documenting forest change processes and estimating carbon storage in the GMS and Malaysia. In this paper, the authors present the implementation of the project in Thailand and demonstrate the result of forest cover mapping in the whole country in 2005 and 2010. The result of the project will contribute towards developing efficient tools to support decision makers to clearly understand the dynamic change of the forest cover which could benefit sustainable forest resource management in Thailand and the whole Subregion.

  13. Single-edition quadrangle maps

    Science.gov (United States)

    ,

    1998-01-01

    In August 1993, the U.S. Geological Survey's (USGS) National Mapping Division and the U.S. Department of Agriculture's Forest Service signed an Interagency Agreement to begin a single-edition joint mapping program. This agreement established the coordination for producing and maintaining single-edition primary series topographic maps for quadrangles containing National Forest System lands. The joint mapping program saves money by eliminating duplication of effort by the agencies and results in a more frequent revision cycle for quadrangles containing national forests. Maps are revised on the basis of jointly developed standards and contain normal features mapped by the USGS, as well as additional features required for efficient management of National Forest System lands. Single-edition maps look slightly different but meet the content, accuracy, and quality criteria of other USGS products. The Forest Service is responsible for the land management of more than 191 million acres of land throughout the continental United States, Alaska, and Puerto Rico, including 155 national forests and 20 national grasslands. These areas make up the National Forest System lands and comprise more than 10,600 of the 56,000 primary series 7.5-minute quadrangle maps (15-minute in Alaska) covering the United States. The Forest Service has assumed responsibility for maintaining these maps, and the USGS remains responsible for printing and distributing them. Before the agreement, both agencies published similar maps of the same areas. The maps were used for different purposes, but had comparable types of features that were revised at different times. Now, the two products have been combined into one so that the revision cycle is stabilized and only one agency revises the maps, thus increasing the number of current maps available for National Forest System lands. This agreement has improved service to the public by requiring that the agencies share the same maps and that the maps meet a

  14. Social-value maps for Arapaho, Roosevelt, Medicine Bow, Routt, and White River National Forests, Colorado and Wyoming

    Science.gov (United States)

    Ancona, Zachary H.; Semmens, Darius J.; Sherrouse, Benson C.

    2016-03-25

    Executive SummaryThe continued pressures of population growth on the life-sustaining, economic, and cultural ecosystem services provided by our national forests, particularly those located near rapidly growing urban areas, present ongoing challenges to forest managers. Achieving an effective assessment of these ecosystem services includes a proper accounting of the ecological, economic, and social values attributable to them. However, assessments of ecosystem goods and services notably lack information describing the spatial distribution and relative intensity of social values—the perceived, nonmarket values derived particularly from cultural ecosystem services. A geographic information system (GIS) tool developed to fill this need, Social Values for Ecosystem Services (SolVES; http://solves.cr.usgs.gov), now provides the capability to generate social-value maps at a range of spatial scales. This report presents some of the methods behind SolVES, procedures needed to apply the tool, the first formal map products resulting from its application at a regional scale, and a discussion of the management implications associated with this type of information.In this study, we use SolVES to identify the location and relative intensity of social values as derived from survey responses gathered from residents living in counties adjacent to Arapaho, Roosevelt, Medicine Bow, Routt, and White River National Forests. The results, presented as a series of social-value maps, represent the first publicly available spatial data on social-value intensity for the southern Rocky Mountain region. Our analysis identified high-value areas for social values including aesthetic, biodiversity, and life sustaining within wilderness areas. Other values, like recreation, show high-value areas both within wilderness and throughout the general forest areas, which can be attributed to people using the forests for a diverse set of recreational activities. The economic social-value type was lower

  15. Estimation and Mapping Forest Attributes Using “k Nearest Neighbor” Method on IRS-P6 LISS III Satellite Image Data

    Directory of Open Access Journals (Sweden)

    Amir Eslam Bonyad

    2015-06-01

    Full Text Available In this study, we explored the utility of k Nearest Neighbor (kNN algorithm to integrate IRS-P6 LISS III satellite imagery data and ground inventory data for application in forest attributes (DBH, trees height, volume, basal area, density and forest cover type estimation and mapping. The ground inventory data was based on a systematic-random sampling grid and the numbers of sampling plots were 408 circular plots in a plantation in Guilan province, north of Iran. We concluded that kNN method was useful tool for mapping at a fine accuracy between 80% and 93.94%. Values of k between 5 and 8 seemed appropriate. The best distance metrics were found Euclidean, Fuzzy and Mahalanobis. Results showed that kNN was accurate enough for practical applicability for mapping forest areas.

  16. Conflict resolution efforts through stakeholder mapping in Labanan Research Forest, Berau, East Kalimantan, Indonesia

    Science.gov (United States)

    Wiati, C. B.; Indriyanti, S. Y.; Maharani, R.; Subarudi

    2018-04-01

    Conflict resolution in Labanan Research Forest (LRF) by the Dipterocarps Forest Ecosystem Research and Development Center (Balai Besar Penelitian dan Pengembangan Ekosistem Hutan Dipterokarpa – B2P2EHD) needs support from other parties that are also interested in such forest management. This paper aimed to presented conflict resolution in LRF through stakeholder mapping for its engagement. This research was conducted for seven months (June to December 2015) with interviews and literature study as its data collection. Collected data were analysed by a stakeholder analysis and matrix based on their interest and power levels. Two important findings were: (1) There are 19 parties having interests in the existence of LRF should be engaged; (2) Conflict resolution of LRF can be achieved: (a) ensuring key stakeholders which have high interest and high power level has same perception in existence and management of LRF, (b) establishing a partnership with primary stakeholders which have high interest and high power levels; (c) building partnerships between primary stakeholders which have high interest but low power levels, (d) building partnerships between key and secondary stakeholders which have low interest but high power levels and (e) gaining support from primary and secondary stakeholders which have low interest and low power levels. Stakeholder mapping is an important tool for tenure conflict resolution through mapping the power and interest of the conflicted parties and finding the proper parties to be approached.

  17. Comparison of Stem Map Developed from Crown Geometry Allometry Linked Census Data to Airborne and Terrestrial Lidar at Harvard Forest, MA

    Science.gov (United States)

    Sullivan, F.; Palace, M. W.; Ducey, M. J.; David, O.; Cook, B. D.; Lepine, L. C.

    2014-12-01

    Harvard Forest in Petersham, MA, USA is the location of one of the temperate forest plots established by the Center for Tropical Forest Science (CTFS) as a joint effort with Harvard Forest and the Smithsonian Institute's Forest Global Earth Observatory (ForestGEO) to characterize ecosystem processes and forest dynamics. Census of a 35 ha plot on Prospect Hill was completed during the winter of 2014 by researchers at Harvard Forest. Census data were collected according to CTFS protocol; measured variables included species, stem diameter, and relative X-Y locations. Airborne lidar data were collected over the censused plot using the high spatial resolution Goddard LiDAR, Hyperspectral, and Thermal sensor package (G-LiHT) during June 2012. As part of a separate study, 39 variable radius plots (VRPs) were randomly located and sampled within and throughout the Prospect Hill CTFS/ForestGEO plot during September and October 2013. On VRPs, biometric properties of trees were sampled, including species, stem diameter, total height, crown base height, crown radii, and relative location to plot centers using a 20 Basal Area Factor prism. In addition, a terrestrial-based lidar scanner was used to collect one lidar scan at plot center for 38 of the 39 VRPs. Leveraging allometric equations of crown geometry and tree height developed from 374 trees and 16 different species sampled on 39 VRPs, a 3-dimensional stem map will be created using the Harvard Forest ForestGEO Prospect Hill census. Vertical and horizontal structure of 3d field-based stem maps will be compared to terrestrial and airborne lidar scan data. Furthermore, to assess the quality of allometric equations, a 2d canopy height raster of the field-based stem map will be compared to a G-LiHT derived canopy height model for the 35 ha census plot. Our automated crown delineation methods will be applied to the 2d representation of the census stem map and the G-LiHT canopy height model. For future work related to this study

  18. Early sexual debut in Norwegian youth with epilepsy: A population-based study.

    Science.gov (United States)

    Lossius, Morten I; Alfstad, Kristin Å; Van Roy, Betty; Mowinckel, Petter; Clench-Aas, Jocelyne; Gjerstad, Leif; Nakken, Karl O

    2016-03-01

    In comparison with controls, youth with epilepsy (YWE) have greater psychosocial problems. However, information about their sexual behavior is sparse. We have performed a large, population-based questionnaire study to examine differences in sexual behavior between YWE and controls. A randomly chosen cohort of youth (13-19 years) from Akershus county, Norway (n=19,995) was asked to complete a questionnaire anonymously with questions on epilepsy and sexual activity. The response rate was 85%. Two hundred forty-seven participants reported having or having had epilepsy, i.e., a lifetime epilepsy prevalence of 1.2%. Compared with controls, a higher proportion of YWE reported having had sexual intercourse (43.6% vs. 35.3%, p=0.009). The mean age at sexual debut was significantly lower in YWE than in controls (14.0 years vs. 15.0 years, pcontraceptives at their last sexual intercourse compared with controls (31.6% vs. 22.3%, p=0.03). Ten percent of YWE, compared with 2% of the controls, reported that they had been forced into their first sexual intercourse. In YWE, some aspects of sexual behavior differ from those of their peers, with earlier sexual debut and less frequent use of contraceptives. More attention should be directed toward this subject, aiming at avoiding unwanted pregnancies and potential emotional traumas in this already vulnerable patient group. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. Implementation of forest cover and carbon mapping in the Greater Mekong subregion and Malaysia project – A case study of Thailand

    International Nuclear Information System (INIS)

    Pungkul, S; Suraswasdi, C; Phonekeo, V

    2014-01-01

    The Great Mekong Subregion (GMS) contains one of the world's largest tropical forests and plays a vital role in sustainable development and provides a range of economic, social and environmental benefits, including essential ecosystem services such as climate change mitigation and adaptation. However, the forest in this Subregion is experiencing deforestation rates at high level due to human activities. The reduction of the forest area has negative influence to the environmental and natural resources issues, particularly, more severe disasters have occurred due to global warming and the release of the greenhouse gases. Therefore, in order to conduct forest management in the Subregion efficiently, the Forest Cover and Carbon Mapping in Greater Mekong Subregion and Malaysia project was initialized by the Asia-Pacific Network for Sustainable Forest Management and Rehabilitation (APFNet) with the collaboration of various research institutions including Institute of Forest Resource Information Technique (IFRIT), Chinese Academy of Forestry (CAF) and the countries in Sub region and Malaysia comprises of Cambodia, the People's Republic of China (Yunnan province and Guangxi province), Lao People's Democratic Republic, Malaysia, Myanmar, Thailand, and Viet Nam. The main target of the project is to apply the intensive use of recent satellite remote sensing technology, establishing regional forest cover maps, documenting forest change processes and estimating carbon storage in the GMS and Malaysia. In this paper, the authors present the implementation of the project in Thailand and demonstrate the result of forest cover mapping in the whole country in 2005 and 2010. The result of the project will contribute towards developing efficient tools to support decision makers to clearly understand the dynamic change of the forest cover which could benefit sustainable forest resource management in Thailand and the whole Subregion

  20. Sex, lies, and videos in rural China: a qualitative study of women's sexual debut and risky sexual behavior.

    Science.gov (United States)

    Wang, Bo; Davidson, Pamela

    2006-08-01

    This paper attempts to understand the sexual behaviors of young, unmarried women living in rural China with a special focus on sexual debut, sexual risk-taking behaviors, and reproductive health consequences. The analysis is based on forty in-depth interviews with young women who had undergone induced abortion as well as information from focus group discussions. Study participants identified pornographic videos and parents' tacit approval and even encouragement as factors instigating their sexual debut. Reasons for unprotected intercourse include spontaneous sexual activity, misconceptions about fertility and the effective use of contraceptives, and the lack of negotiation skills. The results indicate the importance of making reproductive health education more accessible to rural populations in China, a group usually considered to be more traditional and less likely to engage in premarital sex.

  1. A Spectral Mapping Signature for the Rapid Ohia Death (ROD Pathogen in Hawaiian Forests

    Directory of Open Access Journals (Sweden)

    Gregory P. Asner

    2018-03-01

    Full Text Available Pathogenic invasions are a major source of change in both agricultural and natural ecosystems. In forests, fungal pathogens can kill habitat-generating plant species such as canopy trees, but methods for remote detection, mapping and monitoring of such outbreaks are poorly developed. Two novel species of the fungal genus Ceratocystis have spread rapidly across humid and mesic forests of Hawaiʻi Island, causing widespread mortality of the keystone endemic canopy tree species, Metrosideros polymorpha (common name: ʻōhiʻa. The process, known as Rapid Ohia Death (ROD, causes browning of canopy leaves in weeks to months following infection by the pathogen. An operational mapping approach is needed to track the spread of the disease. We combined field studies of leaf spectroscopy with laboratory chemical studies and airborne remote sensing to develop a spectral signature for ROD. We found that close to 80% of ROD-infected plants undergo marked decreases in foliar concentrations of chlorophyll, water and non-structural carbohydrates, which collectively result in strong consistent changes in leaf spectral reflectance in the visible (400–700 nm and shortwave-infrared (1300–2500 nm wavelength regions. Leaf-level results were replicated at the canopy level using airborne laser-guided imaging spectroscopy, with quantitative spectral separability of normal green-leaf canopies from suspected ROD-infected brown-leaf canopies in the visible and shortwave-infrared spectrum. Our results provide the spectral–chemical basis for detection, mapping and monitoring of the spread of ROD in native Hawaiian forests.

  2. Mapping growing stock volume and forest live biomass: a case study of the Polissya region of Ukraine

    Science.gov (United States)

    Bilous, Andrii; Myroniuk, Viktor; Holiaka, Dmytrii; Bilous, Svitlana; See, Linda; Schepaschenko, Dmitry

    2017-10-01

    Forest inventory and biomass mapping are important tasks that require inputs from multiple data sources. In this paper we implement two methods for the Ukrainian region of Polissya: random forest (RF) for tree species prediction and k-nearest neighbors (k-NN) for growing stock volume and biomass mapping. We examined the suitability of the five-band RapidEye satellite image to predict the distribution of six tree species. The accuracy of RF is quite high: ~99% for forest/non-forest mask and 89% for tree species prediction. Our results demonstrate that inclusion of elevation as a predictor variable in the RF model improved the performance of tree species classification. We evaluated different distance metrics for the k-NN method, including Euclidean or Mahalanobis distance, most similar neighbor (MSN), gradient nearest neighbor, and independent component analysis. The MSN with the four nearest neighbors (k = 4) is the most precise (according to the root-mean-square deviation) for predicting forest attributes across the study area. The k-NN method allowed us to estimate growing stock volume with an accuracy of 3 m3 ha-1 and for live biomass of about 2 t ha-1 over the study area.

  3. Development of remote sensing technology in New Zealand, part 1. Seismotectonic, structural, volcanologic and geomorphic study of New Zealand, part 2. Indigenous forest assessment, part 3. Mapping land use and environmental studies in New Zealand, part 4. New Zealand forest service LANDSAT projects, part 5. Vegetation map and landform map of Aupouri Peninsula, Northland, part 6. Geographical applications of LANDSAT mapping, part 7

    Science.gov (United States)

    Probine, M. C.; Suggate, R. P.; Mcgreevy, M. G.; Stirling, I. F. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. Inspection of pixels obtained from LANDSAT of New Zealand revealed that not only can ships and their wakes be detected, but that information on the size, state of motion, and direction of movement was inferred by calculating the total number of pixels occupied by the vessel and wake, the orientation of these pixels, and the sum of their radiance values above the background level. Computer enhanced images showing the Waimihia State Forest and much of Kaingaroa State Forest on 22 December 1975 were examined. Most major forest categories were distinguished on LANDSAT imagery. However, the LANDSAT imagery seemed to be most useful for updating and checking existing forest maps, rather than making new maps with many forest categories. Snow studies were performed using two basins: Six Mile Creek and Mt. Robert. The differences in radiance levels indicated that a greater areal snow cover in Six Mile Creek Basin with the effect of lower radiance values from vegetation/snow regions. A comparison of the two visible bands (MSS 4 and 5) demonstrate this difference for the two basins.

  4. A Spectral Mapping Signature for the Rapid Ohia Death (ROD) Pathogen in Hawaiian Forests

    Science.gov (United States)

    Pathogenic invasions are a major disruptive source of change in both agricultural and natural ecosystems. In forests, fungal pathogens can kill habitat-generating plant species such as canopy trees, but methods for remote detection, mapping and monitoring of such outbreaks are poorly developed. Cera...

  5. Using IKONOS and Aerial Videography to Validate Landsat Land Cover Maps of Central African Tropical Rain Forests

    Science.gov (United States)

    Lin, T.; Laporte, N. T.

    2003-12-01

    Compared to the traditional validation methods, aerial videography is a relatively inexpensive and time-efficient approach to collect "field" data for validating satellite-derived land cover map over large areas. In particular, this approach is valuable in remote and inaccessible locations. In the Sangha Tri-National Park region of Central Africa, where road access is limited to industrial logging sites, we are using IKONOS imagery and aerial videography to assess the accuracy of Landsat-derived land cover maps. As part of a NASA Land Cover Land Use Change project (INFORMS) and in collaboration with the Wildlife Conservation Society in the Republic of Congo, over 1500km of aerial video transects were collected in the Spring of 2001. The use of MediaMapper software combined with a VMS 200 video mapping system enabled the collection of aerial transects to be registered with geographic locations from a Geographic Positioning System. Video frame were extracted, visually interpreted, and compared to land cover types mapped by Landsat. We addressed the limitations of accuracy assessment using aerial-base data and its potential for improving vegetation mapping in tropical rain forests. The results of the videography and IKONOS image analysis demonstrate the utility of very high resolution imagery for map validation and forest resource assessment.

  6. Mapping biomass for a northern forest ecosystem using multi-frequency SAR data

    Science.gov (United States)

    Ranson, K. J.; Sun, Guoqing

    1992-01-01

    Image processing methods for mapping standing biomass for a forest in Maine, using NASA/JPL airborne synthetic aperture radar (AIRSAR) polarimeter data, are presented. By examining the dependence of backscattering on standing biomass, it is determined that the ratio of HV backscattering from a longer wavelength (P- or L-band) to a shorter wavelength (C) is a good combination for mapping total biomass. This ratio enhances the correlation of the image signature to the standing biomass and compensates for a major part of the variations in backscattering attributed to radar incidence angle. The image processing methods used include image calibration, ratioing, filtering, and segmentation. The image segmentation algorithm uses both means and variances of the image, and it is combined with the image filtering process. Preliminary assessment of the resultant biomass maps suggests that this is a promising method.

  7. Forgotten forests--issues and prospects in biome mapping using Seasonally Dry Tropical Forests as a case study.

    Science.gov (United States)

    Särkinen, Tiina; Iganci, João R V; Linares-Palomino, Reynaldo; Simon, Marcelo F; Prado, Darién E

    2011-11-24

    South America is one of the most species diverse continents in the world. Within South America diversity is not distributed evenly at both local and continental scales and this has led to the recognition of various areas with unique species assemblages. Several schemes currently exist which divide the continental-level diversity into large species assemblages referred to as biomes. Here we review five currently available biome maps for South America, including the WWF Ecoregions, the Americas basemap, the Land Cover Map of South America, Morrone's Biogeographic regions of Latin America, and the Ecological Systems Map. The comparison is performed through a case study on the Seasonally Dry Tropical Forest (SDTF) biome using herbarium data of habitat specialist species. Current biome maps of South America perform poorly in depicting SDTF distribution. The poor performance of the maps can be attributed to two main factors: (1) poor spatial resolution, and (2) poor biome delimitation. Poor spatial resolution strongly limits the use of some of the maps in GIS applications, especially for areas with heterogeneous landscape such as the Andes. Whilst the Land Cover Map did not suffer from poor spatial resolution, it showed poor delimitation of biomes. The results highlight that delimiting structurally heterogeneous vegetation is difficult based on remote sensed data alone. A new refined working map of South American SDTF biome is proposed, derived using the Biome Distribution Modelling (BDM) approach where georeferenced herbarium data is used in conjunction with bioclimatic data. Georeferenced specimen data play potentially an important role in biome mapping. Our study shows that herbarium data could be used as a way of ground-truthing biome maps in silico. The results also illustrate that herbarium data can be used to model vegetation maps through predictive modelling. The BDM approach is a promising new method in biome mapping, and could be particularly useful for mapping

  8. Accuracy Assessment of Timber Volume Maps Using Forest Inventory Data and LiDAR Canopy Height Models

    Directory of Open Access Journals (Sweden)

    Andreas Hill

    2014-09-01

    Full Text Available Maps of standing timber volume provide valuable decision support for forest managers and have therefore been the subject of recent studies. For map production, field observations are commonly combined with area-wide remote sensing data in order to formulate prediction models, which are then applied over the entire inventory area. The accuracy of such maps has frequently been described by parameters such as the root mean square error of the prediction model. The aim of this study was to additionally address the accuracy of timber volume classes, which are used to better represent the map predictions. However, the use of constant class intervals neglects the possibility that the precision of the underlying prediction model may not be constant across the entire volume range, resulting in pronounced gradients between class accuracies. This study proposes an optimization technique that automatically identifies a classification scheme which accounts for the properties of the underlying model and the implied properties of the remote sensing support information. We demonstrate the approach in a mountainous study site in Eastern Switzerland covering a forest area of 2000 hectares using a multiple linear regression model approach. A LiDAR-based canopy height model (CHM provided the auxiliary information; timber volume observations from the latest forest inventory were used for model calibration and map validation. The coefficient of determination (R2 = 0.64 and the cross-validated root mean square error (RMSECV = 123.79 m3 ha−1 were only slightly smaller than those of studies in less steep and heterogeneous landscapes. For a large set of pre-defined number of classes, the optimization model successfully identified those classification schemes that achieved the highest possible accuracies for each class.

  9. Forest resources of the Nez Perce National Forest

    Science.gov (United States)

    Michele Disney

    2010-01-01

    As part of a National Forest System cooperative inventory, the Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service conducted a forest resource inventory on the Nez Perce National Forest using a nationally standardized mapped-plot design (for more details see the section "Inventory methods"). This report presents highlights...

  10. The Potential of Sentinel Satellites for Burnt Area Mapping and Monitoring in the Congo Basin Forests

    Directory of Open Access Journals (Sweden)

    Astrid Verhegghen

    2016-11-01

    Full Text Available In this study, the recently launched Sentinel-2 (S2 optical satellite and the active radar Sentinel-1 (S1 satellite supported by active fire data from the MODIS sensor were used to detect and monitor forest fires in the Congo Basin. In the context of a very strong El Niño event, an unprecedented outbreak of fires was observed during the first months of 2016 in open forests formations in the north of the Republic of Congo. The anomalies of the recent fires and meteorological situation compared to historical data show the severity of the drought. Burnt areas mapped by the S1 SAR and S2 Multi Spectral Instrument (MSI sensors highlight that the fires occurred mainly in Marantaceae forests, characterized by open tree canopy cover and an extensive tall herbaceous layer. The maps show that the origin of the fires correlates with accessibility to the forest, suggesting an anthropogenic origin. The combined use of the two independent and fundamentally different satellite systems of S2 and S1 captured an extent of 36,000 ha of burnt areas, with each sensor compensating for the weakness (cloud perturbations for S2, and sensitivity to ground moisture for S1 of the other.

  11. Mapping the Dabus Wetlands, Ethiopia, Using Random Forest Classification of Landsat, PALSAR and Topographic Data

    Directory of Open Access Journals (Sweden)

    Pierre Dubeau

    2017-10-01

    Full Text Available The Dabus Wetland complex in the highlands of Ethiopia is within the headwaters of the Nile Basin and is home to significant ecological communities and rare or endangered species. Its many interrelated wetland types undergo seasonal and longer-term changes due to weather and climate variations as well as anthropogenic land use such as grazing and burning. Mapping and monitoring of these wetlands has not been previously undertaken due primarily to their relative isolation and lack of resources. This study investigated the potential of remote sensing based classification for mapping the primary vegetation groups in the Dabus Wetlands using a combination of dry and wet season data, including optical (Landsat spectral bands and derived vegetation and wetness indices, radar (ALOS PALSAR L-band backscatter, and elevation (SRTM derived DEM and other terrain metrics as inputs to the non-parametric Random Forest (RF classifier. Eight wetland types and three terrestrial/upland classes were mapped using field samples of observed plant community composition and structure groupings as reference information. Various tests to compare results using different RF input parameters and data types were conducted. A combination of multispectral optical, radar and topographic variables provided the best overall classification accuracy, 94.4% and 92.9% for the dry and wet season, respectively. Spectral and topographic data (radar data excluded performed nearly as well, while accuracies using only radar and topographic data were 82–89%. Relatively homogeneous classes such as Papyrus Swamps, Forested Wetland, and Wet Meadow yielded the highest accuracies while spatially complex classes such as Emergent Marsh were more difficult to accurately classify. The methods and results presented in this paper can serve as a basis for development of long-term mapping and monitoring of these and other non-forested wetlands in Ethiopia and other similar environmental settings.

  12. MAPPING DISTURBANCE DYNAMICS IN WET SCLEROPHYLL FORESTS USING TIME SERIES LANDSAT

    Directory of Open Access Journals (Sweden)

    A. Haywood

    2016-06-01

    Full Text Available In this study, we characterised the temporal-spectral patterns associated with identifying acute-severity disturbances and low-severity disturbances between 1985 and 2011 with the objective to test whether different disturbance agents within these categories can be identified with annual Landsat time series data. We analysed a representative State forest within the Central Highlands which has been exposed to a range of disturbances over the last 30 years, including timber harvesting (clearfell, selective and thinning and fire (wildfire and prescribed burning. We fitted spectral time series models to annual normal burn ratio (NBR and Tasseled Cap Indices (TCI, from which we extracted a range of disturbance and recovery metrics. With these metrics, three hierarchical random forest models were trained to 1 distinguish acute-severity disturbances from low-severity disturbances; 2a attribute the disturbance agents most likely within the acute-severity class; 2b and attribute the disturbance agents most likely within the low-severity class. Disturbance types (acute severity and low-severity were successfully mapped with an overall accuracy of 72.9 %, and the individual disturbance types were successfully attributed with overall accuracies ranging from 53.2 % to 64.3 %. Low-severity disturbance agents were successfully mapped with an overall accuracy of 80.2 %, and individual agents were successfully attributed with overall accuracies ranging from 25.5 % to 95.1. Acute-severity disturbance agents were successfully mapped with an overall accuracy of 95.4 %, and individual agents were successfully attributed with overall accuracies ranging from 94.2 % to 95.2 %. Spectral metrics describing the disturbance magnitude were more important for distinguishing the disturbance agents than the post-disturbance response slope. Spectral changes associated with planned burning disturbances had generally lower magnitudes than selective harvesting

  13. A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform

    Science.gov (United States)

    Chen, Bangqian; Xiao, Xiangming; Li, Xiangping; Pan, Lianghao; Doughty, Russell; Ma, Jun; Dong, Jinwei; Qin, Yuanwei; Zhao, Bin; Wu, Zhixiang; Sun, Rui; Lan, Guoyu; Xie, Guishui; Clinton, Nicholas; Giri, Chandra

    2017-09-01

    Due to rapid losses of mangrove forests caused by anthropogenic disturbances and climate change, accurate and contemporary maps of mangrove forests are needed to understand how mangrove ecosystems are changing and establish plans for sustainable management. In this study, a new classification algorithm was developed using the biophysical characteristics of mangrove forests in China. More specifically, these forests were mapped by identifying: (1) greenness, canopy coverage, and tidal inundation from time series Landsat data, and (2) elevation, slope, and intersection-with-sea criterion. The annual mean Normalized Difference Vegetation Index (NDVI) was found to be a key variable in determining the classification thresholds of greenness, canopy coverage, and tidal inundation of mangrove forests, which are greatly affected by tide dynamics. In addition, the integration of Sentinel-1A VH band and modified Normalized Difference Water Index (mNDWI) shows great potential in identifying yearlong tidal and fresh water bodies, which is related to mangrove forests. This algorithm was developed using 6 typical Regions of Interest (ROIs) as algorithm training and was run on the Google Earth Engine (GEE) cloud computing platform to process 1941 Landsat images (25 Path/Row) and 586 Sentinel-1A images circa 2015. The resultant mangrove forest map of China at 30 m spatial resolution has an overall/users/producer's accuracy greater than 95% when validated with ground reference data. In 2015, China's mangrove forests had a total area of 20,303 ha, about 92% of which was in the Guangxi Zhuang Autonomous Region, Guangdong, and Hainan Provinces. This study has demonstrated the potential of using the GEE platform, time series Landsat and Sentine-1A SAR images to identify and map mangrove forests along the coastal zones. The resultant mangrove forest maps are likely to be useful for the sustainable management and ecological assessments of mangrove forests in China.

  14. The Influence of DEM Quality on Mapping Accuracy of Coniferous- and Deciduous-Dominated Forest Using TerraSAR‑X Images

    Directory of Open Access Journals (Sweden)

    Gerald Kändler

    2012-03-01

    Full Text Available Climate change is a factor that largely contributes to the increase of forest areas affected by natural damages. Therefore, the development of methodologies for forest monitoring and rapid assessment of affected areas is required. Space-borne synthetic aperture radar (SAR imagery with high resolution is now available for large-scale forest mapping and forest monitoring applications. However, a correct interpretation of SAR images requires an adequate preprocessing of the data consisting of orthorectification and radiometric calibration. The resolution and quality of the digital elevation model (DEM used as reference is crucial for this purpose. Therefore, the primary aim of this study was to analyze the influence of the DEM quality used in the preprocessing of the SAR data on the mapping accuracy of forest types. In order to examine TerraSAR-X images to map forest dominated by deciduous and coniferous trees, High Resolution SpotLight images were acquired for two study sites in southern Germany. The SAR images were preprocessed with a Shuttle Radar Topography Mission (SRTM DEM (resolution approximately 90 m, an airborne laser scanning (ALS digital terrain model (DTM (5 m resolution, and an ALS digital surface model (DSM (5 m resolution. The orthorectification of the SAR images using high resolution ALS DEMs was found to be important for the reduction of errors in pixel location and to increase the classification accuracy of forest types. SAR images preprocessed with ALS DTMs resulted in the highest classification accuracies, with kappa coefficients of 0.49 and 0.41, respectively. SAR images preprocessed with ALS DTMs resulted in greater accuracy than those preprocessed with ALS DSMs in most cases. The classification accuracy of forest types using SAR images preprocessed with the SRTM DEM was fair, with kappa coefficients of 0.23 and 0.32, respectively.Analysis of the radar backscatter indicated that sample plots dominated by coniferous trees

  15. Forgotten forests - issues and prospects in biome mapping using Seasonally Dry Tropical Forests as a case study

    Directory of Open Access Journals (Sweden)

    Särkinen Tiina

    2011-11-01

    Full Text Available Abstract Background South America is one of the most species diverse continents in the world. Within South America diversity is not distributed evenly at both local and continental scales and this has led to the recognition of various areas with unique species assemblages. Several schemes currently exist which divide the continental-level diversity into large species assemblages referred to as biomes. Here we review five currently available biome maps for South America, including the WWF Ecoregions, the Americas basemap, the Land Cover Map of South America, Morrone's Biogeographic regions of Latin America, and the Ecological Systems Map. The comparison is performed through a case study on the Seasonally Dry Tropical Forest (SDTF biome using herbarium data of habitat specialist species. Results Current biome maps of South America perform poorly in depicting SDTF distribution. The poor performance of the maps can be attributed to two main factors: (1 poor spatial resolution, and (2 poor biome delimitation. Poor spatial resolution strongly limits the use of some of the maps in GIS applications, especially for areas with heterogeneous landscape such as the Andes. Whilst the Land Cover Map did not suffer from poor spatial resolution, it showed poor delimitation of biomes. The results highlight that delimiting structurally heterogeneous vegetation is difficult based on remote sensed data alone. A new refined working map of South American SDTF biome is proposed, derived using the Biome Distribution Modelling (BDM approach where georeferenced herbarium data is used in conjunction with bioclimatic data. Conclusions Georeferenced specimen data play potentially an important role in biome mapping. Our study shows that herbarium data could be used as a way of ground-truthing biome maps in silico. The results also illustrate that herbarium data can be used to model vegetation maps through predictive modelling. The BDM approach is a promising new method in

  16. Forgotten forests - issues and prospects in biome mapping using Seasonally Dry Tropical Forests as a case study

    Science.gov (United States)

    2011-01-01

    Background South America is one of the most species diverse continents in the world. Within South America diversity is not distributed evenly at both local and continental scales and this has led to the recognition of various areas with unique species assemblages. Several schemes currently exist which divide the continental-level diversity into large species assemblages referred to as biomes. Here we review five currently available biome maps for South America, including the WWF Ecoregions, the Americas basemap, the Land Cover Map of South America, Morrone's Biogeographic regions of Latin America, and the Ecological Systems Map. The comparison is performed through a case study on the Seasonally Dry Tropical Forest (SDTF) biome using herbarium data of habitat specialist species. Results Current biome maps of South America perform poorly in depicting SDTF distribution. The poor performance of the maps can be attributed to two main factors: (1) poor spatial resolution, and (2) poor biome delimitation. Poor spatial resolution strongly limits the use of some of the maps in GIS applications, especially for areas with heterogeneous landscape such as the Andes. Whilst the Land Cover Map did not suffer from poor spatial resolution, it showed poor delimitation of biomes. The results highlight that delimiting structurally heterogeneous vegetation is difficult based on remote sensed data alone. A new refined working map of South American SDTF biome is proposed, derived using the Biome Distribution Modelling (BDM) approach where georeferenced herbarium data is used in conjunction with bioclimatic data. Conclusions Georeferenced specimen data play potentially an important role in biome mapping. Our study shows that herbarium data could be used as a way of ground-truthing biome maps in silico. The results also illustrate that herbarium data can be used to model vegetation maps through predictive modelling. The BDM approach is a promising new method in biome mapping, and could be

  17. Comparison of Data Fusion Methods Using Crowdsourced Data in Creating a Hybrid Forest Cover Map

    Directory of Open Access Journals (Sweden)

    Myroslava Lesiv

    2016-03-01

    Full Text Available Data fusion represents a powerful way of integrating individual sources of information to produce a better output than could be achieved by any of the individual sources on their own. This paper focuses on the data fusion of different land cover products derived from remote sensing. In the past, many different methods have been applied, without regard to their relative merit. In this study, we compared some of the most commonly-used methods to develop a hybrid forest cover map by combining available land cover/forest products and crowdsourced data on forest cover obtained through the Geo-Wiki project. The methods include: nearest neighbour, naive Bayes, logistic regression and geographically-weighted logistic regression (GWR, as well as classification and regression trees (CART. We ran the comparison experiments using two data types: presence/absence of forest in a grid cell; percentage of forest cover in a grid cell. In general, there was little difference between the methods. However, GWR was found to perform better than the other tested methods in areas with high disagreement between the inputs.

  18. An enhanced forest classification scheme for modeling vegetation-climate interactions based on national forest inventory data

    Science.gov (United States)

    Majasalmi, Titta; Eisner, Stephanie; Astrup, Rasmus; Fridman, Jonas; Bright, Ryan M.

    2018-01-01

    Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning and in turn the surface-atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related lookup table (LUT) of key forest structural attributes (i.e., maximum growing season leaf area index (LAImax), basal-area-weighted mean tree height, tree crown length, and total stem volume) was developed, and the classification was applied for multisource NFI (MS-NFI) maps from Norway, Sweden, and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Initiative Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7). Comparison of the ESA LC and our enhanced LC products (https://doi.org/10.21350/7zZEy5w3) showed that forest extent notably (κ = 0.55, accuracy 0.64) differed between the two products. To demonstrate the potential of our enhanced LC product to improve the description of the maximum growing season LAI (LAImax) of managed forests in Fennoscandia, we compared our LAImax map with reference LAImax maps created using the ESA LC product (and related cross-walking table) and PFT-dependent LAImax values used in three leading land models. Comparison of the LAImax maps showed that our product provides a spatially more realistic description of LAImax in managed Fennoscandian forests compared to reference maps. This study presents an approach to account for the transient nature of forest structural attributes due to human intervention in different land models.

  19. LYα FOREST TOMOGRAPHY FROM BACKGROUND GALAXIES: THE FIRST MEGAPARSEC-RESOLUTION LARGE-SCALE STRUCTURE MAP AT z > 2

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Khee-Gan; Hennawi, Joseph F.; Eilers, Anna-Christina [Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany); Stark, Casey; White, Martin [Department of Astronomy, University of California at Berkeley, B-20 Hearst Field Annex 3411, Berkeley, CA 94720 (United States); Prochaska, J. Xavier [Department of Astronomy and Astrophysics, University of California, 1156 High Street, Santa Cruz, CA 95064 (United States); Schlegel, David J. [University of California Observatories, Lick Observatory, 1156 High Street, Santa Cruz, CA 95064 (United States); Arinyo-i-Prats, Andreu [Institut de Ciències del Cosmos, Universitat de Barcelona (IEEC-UB), Martí Franquès 1, E-08028 Barcelona (Spain); Suzuki, Nao [Kavli Institute for the Physics and Mathematics of the Universe (IPMU), The University of Tokyo, Kashiwano-ha 5-1-5, Kashiwa-shi, Chiba (Japan); Croft, Rupert A. C. [Department of Physics, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 (United States); Caputi, Karina I. [Kapteyn Astronomical Institute, University of Groningen, P.O. Box 800, 9700-AV Groningen (Netherlands); Cassata, Paolo [Instituto de Fisica y Astronomia, Facultad de Ciencias, Universidad de Valparaiso, Av. Gran Bretana 1111, Casilla 5030, Valparaiso (Chile); Ilbert, Olivier; Le Brun, Vincent; Le Fèvre, Olivier [Aix Marseille Université, CNRS, LAM (Laboratoire d' Astrophysique de Marseille) UMR 7326, F-13388 Marseille (France); Garilli, Bianca [INAF-IASF, Via Bassini 15, I-20133, Milano (Italy); Koekemoer, Anton M. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Maccagni, Dario [INAF-Osservatorio Astronomico di Bologna, Via Ranzani,1, I-40127 Bologna (Italy); Nugent, Peter, E-mail: lee@mpia.de [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 (United States); and others

    2014-11-01

    We present the first observations of foreground Lyα forest absorption from high-redshift galaxies, targeting 24 star-forming galaxies (SFGs) with z ∼ 2.3-2.8 within a 5' × 14' region of the COSMOS field. The transverse sightline separation is ∼2 h {sup –1} Mpc comoving, allowing us to create a tomographic reconstruction of the three-dimensional (3D) Lyα forest absorption field over the redshift range 2.20 ≤ z ≤ 2.45. The resulting map covers 6 h {sup –1} Mpc × 14 h {sup –1} Mpc in the transverse plane and 230 h {sup –1} Mpc along the line of sight with a spatial resolution of ≈3.5 h {sup –1} Mpc, and is the first high-fidelity map of a large-scale structure on ∼Mpc scales at z > 2. Our map reveals significant structures with ≳ 10 h {sup –1} Mpc extent, including several spanning the entire transverse breadth, providing qualitative evidence for the filamentary structures predicted to exist in the high-redshift cosmic web. Simulated reconstructions with the same sightline sampling, spectral resolution, and signal-to-noise ratio recover the salient structures present in the underlying 3D absorption fields. Using data from other surveys, we identified 18 galaxies with known redshifts coeval with our map volume, enabling a direct comparison with our tomographic map. This shows that galaxies preferentially occupy high-density regions, in qualitative agreement with the same comparison applied to simulations. Our results establish the feasibility of the CLAMATO survey, which aims to obtain Lyα forest spectra for ∼1000 SFGs over ∼1 deg{sup 2} of the COSMOS field, in order to map out the intergalactic medium large-scale structure at (z) ∼ 2.3 over a large volume (100 h {sup –1} Mpc){sup 3}.

  20. Using widely spaced observations of land use, forest attributes, and intrusions to map resource potential and human impact probability

    Science.gov (United States)

    Victor A. Rudis

    2000-01-01

    Scant information exists about the spatial extent of human impact on forest resource supplies, i.e., depreciative and nonforest uses. I used observations of ground-sampled land use and intrusions on forest land to map the probability of resource use and human impact for broad areas. Data came from a seven State survey region (Alabama, Arkansas, Louisiana, Mississippi,...

  1. Using widely spaced observations of land use, forest attributes, and intrusions to map resource potential and human impact probability

    Science.gov (United States)

    Victor A. Rudis

    2000-01-01

    Scant information exists about the spatial extent of human impact on forest resource supplies, i.e., depreciative and nonforest uses. I used observations of ground-sampled land use and intrusions on forest land to map the probability of resource use and human impact for broad areas. Data came from a seven-state survey region (Alabama, Arkansas, Louisiana, Mississippi,...

  2. Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies

    Science.gov (United States)

    Devaney, John; Barrett, Brian; Barrett, Frank; Redmond, John; O`Halloran, John

    2015-01-01

    Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1–98.5%), with differences between the two classifiers being minimal (forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting. PMID:26262681

  3. Mapping and Analysis of Forest and Land Fire Potential Using Geospatial Technology and Mathematical Modeling

    International Nuclear Information System (INIS)

    Suliman, M D H; Mahmud, M; Reba, M N M; S, L W

    2014-01-01

    Forest and land fire can cause negative implications for forest ecosystems, biodiversity, air quality and soil structure. However, the implications involved can be minimized through effective disaster management system. Effective disaster management mechanisms can be developed through appropriate early warning system as well as an efficient delivery system. This study tried to focus on two aspects, namely by mapping the potential of forest fire and land as well as the delivery of information to users through WebGIS application. Geospatial technology and mathematical modeling used in this study for identifying, classifying and mapping the potential area for burning. Mathematical models used is the Analytical Hierarchy Process (AHP), while Geospatial technologies involved include remote sensing, Geographic Information System (GIS) and digital field data collection. The entire Selangor state was chosen as our study area based on a number of cases have been reported over the last two decades. AHP modeling to assess the comparison between the three main criteria of fuel, topography and human factors design. Contributions of experts directly involved in forest fire fighting operations and land comprising officials from the Fire and Rescue Department Malaysia also evaluated in this model. The study found that about 32.83 square kilometers of the total area of Selangor state are the extreme potential for fire. Extreme potential areas identified are in Bestari Jaya and Kuala Langat High Ulu. Continuity of information and terrestrial forest fire potential was displayed in WebGIS applications on the internet. Display information through WebGIS applications is a better approach to help the decision-making process at a high level of confidence and approximate real conditions. Agencies involved in disaster management such as Jawatankuasa Pengurusan Dan Bantuan Bencana (JPBB) of District, State and the National under the National Security Division and the Fire and Rescue

  4. Mapping and Analysis of Forest and Land Fire Potential Using Geospatial Technology and Mathematical Modeling

    Science.gov (United States)

    Suliman, M. D. H.; Mahmud, M.; Reba, M. N. M.; S, L. W.

    2014-02-01

    Forest and land fire can cause negative implications for forest ecosystems, biodiversity, air quality and soil structure. However, the implications involved can be minimized through effective disaster management system. Effective disaster management mechanisms can be developed through appropriate early warning system as well as an efficient delivery system. This study tried to focus on two aspects, namely by mapping the potential of forest fire and land as well as the delivery of information to users through WebGIS application. Geospatial technology and mathematical modeling used in this study for identifying, classifying and mapping the potential area for burning. Mathematical models used is the Analytical Hierarchy Process (AHP), while Geospatial technologies involved include remote sensing, Geographic Information System (GIS) and digital field data collection. The entire Selangor state was chosen as our study area based on a number of cases have been reported over the last two decades. AHP modeling to assess the comparison between the three main criteria of fuel, topography and human factors design. Contributions of experts directly involved in forest fire fighting operations and land comprising officials from the Fire and Rescue Department Malaysia also evaluated in this model. The study found that about 32.83 square kilometers of the total area of Selangor state are the extreme potential for fire. Extreme potential areas identified are in Bestari Jaya and Kuala Langat High Ulu. Continuity of information and terrestrial forest fire potential was displayed in WebGIS applications on the internet. Display information through WebGIS applications is a better approach to help the decision-making process at a high level of confidence and approximate real conditions. Agencies involved in disaster management such as Jawatankuasa Pengurusan Dan Bantuan Bencana (JPBB) of District, State and the National under the National Security Division and the Fire and Rescue

  5. Mapping forested wetlands in the Great Zhan River Basin through integrating optical, radar, and topographical data classification techniques.

    Science.gov (United States)

    Na, X D; Zang, S Y; Wu, C S; Li, W L

    2015-11-01

    Knowledge of the spatial extent of forested wetlands is essential to many studies including wetland functioning assessment, greenhouse gas flux estimation, and wildlife suitable habitat identification. For discriminating forested wetlands from their adjacent land cover types, researchers have resorted to image analysis techniques applied to numerous remotely sensed data. While with some success, there is still no consensus on the optimal approaches for mapping forested wetlands. To address this problem, we examined two machine learning approaches, random forest (RF) and K-nearest neighbor (KNN) algorithms, and applied these two approaches to the framework of pixel-based and object-based classifications. The RF and KNN algorithms were constructed using predictors derived from Landsat 8 imagery, Radarsat-2 advanced synthetic aperture radar (SAR), and topographical indices. The results show that the objected-based classifications performed better than per-pixel classifications using the same algorithm (RF) in terms of overall accuracy and the difference of their kappa coefficients are statistically significant (pwetlands based on the per-pixel classifications using the RF algorithm. As for the object-based image analysis, there were also statistically significant differences (pwetlands and omissions for agriculture land. This research proves that the object-based classification with RF using optical, radar, and topographical data improved the mapping accuracy of land covers and provided a feasible approach to discriminate the forested wetlands from the other land cover types in forestry area.

  6. What makes segmentation good? A case study in boreal forest habitat mapping

    OpenAIRE

    Räsänen, Aleksi; Rusanen, Antti; Kuitunen, Markku; Lensu, Anssi

    2013-01-01

    Segmentation goodness evaluation is a set of approaches meant for deciding which segmentation is good. In this study, we tested different supervised segmentation evaluation measures and visual interpretation in the case of boreal forest habitat mapping in Southern Finland. The data used were WorldView-2 satellite imagery, a lidar digital elevation model (DEM), and a canopy height model (CHM) in 2 m resolution. The segmentation methods tested were the fractal net evolution approach (FNEA) and ...

  7. Mapping Burned Areas in Tropical Forests Using a Novel Machine Learning Framework

    OpenAIRE

    Varun Mithal; Guruprasad Nayak; Ankush Khandelwal; Vipin Kumar; Ramakrishna Nemani; Nikunj C. Oza

    2018-01-01

    This paper presents an application of a novel machine-learning framework on MODIS (moderate-resolution imaging spectroradiometer) data to map burned areas over tropical forests of South America and South-east Asia. The RAPT (RAre Class Prediction in the absence of True labels) framework is able to build data adaptive classification models using noisy training labels. It is particularly suitable when expert annotated training samples are difficult to obtain as in the case of wild fires in the ...

  8. The cross-correlation between 21 cm intensity mapping maps and the Lyα forest in the post-reionization era

    Energy Technology Data Exchange (ETDEWEB)

    Carucci, Isabella P. [SISSA—International School for Advanced Studies, Via Bonomea 265, 34136 Trieste (Italy); Villaescusa-Navarro, Francisco [Center for Computational Astrophysics, 160 5th Avenue, New York, NY, 10010 (United States); Viel, Matteo, E-mail: ipcarucci@sissa.it, E-mail: fvillaescusa@simonsfoundation.org, E-mail: viel@oats.inaf.it [INAF—Osservatorio Astronomico di Trieste, Via Tiepolo 11, 34143, Trieste (Italy)

    2017-04-01

    We investigate the cross-correlation signal between 21cm intensity mapping maps and the Lyα forest in the fully non-linear regime using state-of-the-art hydrodynamic simulations. The cross-correlation signal between the Lyα forest and 21cm maps can provide a coherent and comprehensive picture of the neutral hydrogen (HI) content of our Universe in the post-reionization era, probing both its mass content and volume distribution. We compute the auto-power spectra of both fields together with their cross-power spectrum at z = 2.4 and find that on large scales the fields are completely anti-correlated. This anti-correlation arises because regions with high (low) 21cm emission, such as those with a large (low) concentration of damped Lyα systems, will show up as regions with low (high) transmitted flux. We find that on scales smaller than k ≅ 0.2 h Mpc{sup −1} the cross-correlation coefficient departs from −1, at a scale where non-linearities show up. We use the anisotropy of the power spectra in redshift-space to determine the values of the bias and of the redshift-space distortion parameters of both fields. We find that the errors on the value of the cosmological and astrophysical parameters could decrease by 30% when adding data from the cross-power spectrum, in a conservative analysis. Our results point out that linear theory is capable of reproducing the shape and amplitude of the cross-power up to rather non-linear scales. Finally, we find that the 21cm-Lyα cross-power spectrum can be detected by combining data from a BOSS-like survey together with 21cm intensity mapping observations by SKA1-MID with a S/N ratio higher than 3 in k element of [0.06,1] h Mpc{sup −1}. We emphasize that while the shape and amplitude of the 21cm auto-power spectrum can be severely affected by residual foreground contamination, cross-power spectra will be less sensitive to that and therefore can be used to identify systematics in the 21cm maps.

  9. Increasing the Accuracy of Mapping Urban Forest Carbon Density by Combining Spatial Modeling and Spectral Unmixing Analysis

    Directory of Open Access Journals (Sweden)

    Hua Sun

    2015-11-01

    Full Text Available Accurately mapping urban vegetation carbon density is challenging because of complex landscapes and mixed pixels. In this study, a novel methodology was proposed that combines a linear spectral unmixing analysis (LSUA with a linear stepwise regression (LSR, a logistic model-based stepwise regression (LMSR and k-Nearest Neighbors (kNN, to map the forest carbon density of Shenzhen City of China, using Landsat 8 imagery and sample plot data collected in 2014. The independent variables that contributed to statistically significantly improving the fit of a model to data and reducing the sum of squared errors were first selected from a total of 284 spectral variables derived from the image bands. The vegetation fraction from LSUA was then added as an independent variable. The results obtained using cross-validation showed that: (1 Compared to the methods without the vegetation information, adding the vegetation fraction increased the accuracy of mapping carbon density by 1%–9.3%; (2 As the observed values increased, the LSR and kNN residuals showed overestimates and underestimates for the smaller and larger observations, respectively, while LMSR improved the systematical over and underestimations; (3 LSR resulted in illogically negative and unreasonably large estimates, while KNN produced the greatest values of root mean square error (RMSE. The results indicate that combining the spatial modeling method LMSR and the spectral unmixing analysis LUSA, coupled with Landsat imagery, is most promising for increasing the accuracy of urban forest carbon density maps. In addition, this method has considerable potential for accurate, rapid and nondestructive prediction of urban and peri-urban forest carbon stocks with an acceptable level of error and low cost.

  10. Evidence and mapping of extinction debts for global forest-dwelling reptiles, amphibians and mammals

    Science.gov (United States)

    Chen, Youhua; Peng, Shushi

    2017-03-01

    Evidence of extinction debts for the global distributions of forest-dwelling reptiles, mammals and amphibians was tested and the debt magnitude was estimated and mapped. By using different correlation tests and variable importance analysis, the results showed that spatial richness patterns for the three forest-dwelling terrestrial vertebrate groups had significant and stronger correlations with past forest cover area and other variables in the 1500 s, implying the evidence for extinction debts. Moreover, it was likely that the extinction debts have been partially paid, given that their global richness patterns were also significantly correlated with contemporary forest variables in the 2000 s (but the absolute magnitudes of the correlation coefficients were usually smaller than those calculated for historical forest variables). By utilizing species-area relationships, spatial extinction-debt magnitudes for the three vertebrate groups at the global scale were estimated and the hotspots of extinction debts were identified. These high-debt hotspots were generally situated in areas that did not spatially overlap with hotspots of species richness or high extinction-risk areas based on IUCN threatened status to a large extent. This spatial mismatch pattern suggested that necessary conservation efforts should be directed toward high-debt areas that are still overlooked.

  11. Remote Sensing for Mapping RAMSAR Heritage Site at Sungai Pulai Mangrove Forest Reserve, Johor, Malaysia

    International Nuclear Information System (INIS)

    Hasmadi, I.M.; Pakhriazad, H.Z.; Norlida, K.

    2011-01-01

    The Sungai Pulai Mangrove Forest Reserve (SPMFR) is the largest reverin mangrove system in Johore. In 2003 about 9,126 ha of the Sungai Pulai mangrove was designated as a RAMSAR site. RAMSAR sites are wetland areas that are deemed to have international importance and are included in the List of Wetlands of International Importance. The SPMFR plays a significant socio-economic role to the adjacent 38 villages. Satellite remote sensing is a useful source of information where it provides timely and complete coverage for vegetation mapping especially in mangroves where the accessibility is difficult. This study was carried out to identify and map land cover types using SPOT-4 imagery at the Sungai Pulai-RAMSAR site and its surrounding areas. Through unsupervised classification technique a total of seven classes of land cover type were mapped, where about 90 % mapping accuracy was gained from the accuracy assessment. Later, vegetation densities were classified into five levels namely very high, high, medium, low and very low based on crown density scale using vegetation indices model such as NDVI, AVI and OSAVI. Results from NDVI and OSAVI model were almost similar but AVI model detected more on medium vegetation which did not show the real ground condition. The study concludes that SPOT-4 imagery was able to discriminate mangrove area clearly from other land covers type. Vegetation indices model can be used as a tool for mapping vegetation density level in the SPMFR and its surrounding area. Therefore VIs models from remote sensing are useful to monitor and manage the mangrove forest for sustainable management and preserve the SPMFR as a RAMSAR site in Peninsular Malaysia. (author)

  12. Forest baseline and deforestation map of the Dominican Republic through the analysis of time series of MODIS data

    Directory of Open Access Journals (Sweden)

    Florencia Sangermano

    2015-09-01

    Full Text Available Deforestation is one of the major threats to habitats in the Dominican Republic. In this work we present a forest baseline for the year 2000 and a deforestation map for the year 2011. Maps were derived from Moderate Resolution Imaging Radiometer (MODIS products at 250 m resolution. The vegetation continuous fields product (MOD44B for the year 2000 was used to produce the forest baseline, while the vegetation indices product (MOD13Q1 was used to detect change between 2000 and 2011. Major findings based on the data presented here are reported in the manuscript “Habitat suitability and protection status of four species of amphibians in the Dominican Republic” (Sangermano et al., Appl. Geogr., [7].63, 2015, 55–65

  13. On the potential of long wavelength imaging radars for mapping vegetation types and woody biomass in tropical rain forests

    Science.gov (United States)

    Rignot, Eric J.; Zimmermann, Reiner; Oren, Ram

    1995-01-01

    In the tropical rain forests of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 100 kg/sq m in old, undisturbed floodplain stands, the P-band polarimetric radar data gathered in June of 1993 by the AIRSAR (Airborne Synthetic Aperture Radar) instrument separate most major vegetation formations and also perform better than expected in estimating woody biomass. The worldwide need for large scale, updated biomass estimates, achieved with a uniformly applied method, as well as reliable maps of land cover, justifies a more in-depth exploration of long wavelength imaging radar applications for tropical forests inventories.

  14. Mapping Forest Edge Using Aerial Lidar

    Science.gov (United States)

    MacLean, M. G.

    2014-12-01

    Slightly more than 60% of Massachusetts is covered with forest and this land cover type is invaluable for the protection and maintenance of our natural resources and is a carbon sink for the state. However, Massachusetts is currently experiencing a decline in forested lands, primarily due to the expansion of human development (Thompson et al., 2011). Of particular concern is the loss of "core areas" or the areas within forests that are not influenced by other land cover types. These areas are of significant importance to native flora and fauna, since they generally are not subject to invasion by exotic species and are more resilient to the effects of climate change (Campbell et al., 2009). However, the expansion of development has reduced the amount of this core area, but the exact amount is still unknown. Current methods of estimating core area are not particularly precise, since edge, or the area of the forest that is most influenced by other land cover types, is quite variable and situation dependent. Therefore, the purpose of this study is to devise a new method for identifying areas that could qualify as "edge" within the Harvard Forest, in Petersham MA, using new remote sensing techniques. We sampled along eight transects perpendicular to the edge of an abandoned golf course within the Harvard Forest property. Vegetation inventories as well as Photosynthetically Active Radiation (PAR) at different heights within the canopy were used to determine edge depth. These measurements were then compared with small-footprint waveform aerial LiDAR datasets and imagery to model edge depths within Harvard Forest.

  15. Mapping post-fire forest regeneration and vegetation recovery using a combination of very high spatial resolution and hyperspectral satellite imagery

    Science.gov (United States)

    Mitri, George H.; Gitas, Ioannis Z.

    2013-02-01

    Careful evaluation of forest regeneration and vegetation recovery after a fire event provides vital information useful in land management. The use of remotely sensed data is considered to be especially suitable for monitoring ecosystem dynamics after fire. The aim of this work was to map post-fire forest regeneration and vegetation recovery on the Mediterranean island of Thasos by using a combination of very high spatial (VHS) resolution (QuickBird) and hyperspectral (EO-1 Hyperion) imagery and by employing object-based image analysis. More specifically, the work focused on (1) the separation and mapping of three major post-fire classes (forest regeneration, other vegetation recovery, unburned vegetation) existing within the fire perimeter, and (2) the differentiation and mapping of the two main forest regeneration classes, namely, Pinus brutia regeneration, and Pinus nigra regeneration. The data used in this study consisted of satellite images and field observations of homogeneous regenerated and revegetated areas. The methodology followed two main steps: a three-level image segmentation, and, a classification of the segmented images. The process resulted in the separation of classes related to the aforementioned objectives. The overall accuracy assessment revealed very promising results (approximately 83.7% overall accuracy, with a Kappa Index of Agreement of 0.79). The achieved accuracy was 8% higher when compared to the results reported in a previous work in which only the EO-1 Hyperion image was employed in order to map the same classes. Some classification confusions involving the classes of P. brutia regeneration and P. nigra regeneration were observed. This could be attributed to the absence of large and dense homogeneous areas of regenerated pine trees in the study area.

  16. Large-Scale Mixed Temperate Forest Mapping at the Single Tree Level using Airborne Laser Scanning

    Science.gov (United States)

    Scholl, V.; Morsdorf, F.; Ginzler, C.; Schaepman, M. E.

    2017-12-01

    Monitoring vegetation on a single tree level is critical to understand and model a variety of processes, functions, and changes in forest systems. Remote sensing technologies are increasingly utilized to complement and upscale the field-based measurements of forest inventories. Airborne laser scanning (ALS) systems provide valuable information in the vertical dimension for effective vegetation structure mapping. Although many algorithms exist to extract single tree segments from forest scans, they are often tuned to perform well in homogeneous coniferous or deciduous areas and are not successful in mixed forests. Other methods are too computationally expensive to apply operationally. The aim of this study was to develop a single tree detection workflow using leaf-off ALS data for the canton of Aargau in Switzerland. Aargau covers an area of over 1,400km2 and features mixed forests with various development stages and topography. Forest type was classified using random forests to guide local parameter selection. Canopy height model-based treetop maxima were detected and maintained based on the relationship between tree height and window size, used as a proxy to crown diameter. Watershed segmentation was used to generate crown polygons surrounding each maximum. The location, height, and crown dimensions of single trees were derived from the ALS returns within each polygon. Validation was performed through comparison with field measurements and extrapolated estimates from long-term monitoring plots of the Swiss National Forest Inventory within the framework of the Swiss Federal Institute for Forest, Snow, and Landscape Research. This method shows promise for robust, large-scale single tree detection in mixed forests. The single tree data will aid ecological studies as well as forest management practices. Figure description: Height-normalized ALS point cloud data (top) and resulting single tree segments (bottom) on the Laegeren mountain in Switzerland.

  17. Forest loss maps from regional satellite monitoring systematically underestimate deforestation in two rapidly changing parts of the Amazon

    Science.gov (United States)

    Milodowski, D. T.; Mitchard, E. T. A.; Williams, M.

    2017-09-01

    Accurate, consistent reporting of changing forest area, stratified by forest type, is required for all countries under their commitments to the Paris Agreement (UNFCCC 2015 Adoption of the Paris Agreement (Paris: UNFCCC)). Such change reporting may directly impact on payments through comparisons to national Reference (Emissions) Levels under the Reducing Emissions from Deforestation and forest Degradation (REDD+) framework. The emergence of global, satellite-based forest monitoring systems, including Global Forest Watch (GFW) and FORMA, have great potential in aiding this endeavour. However, the accuracy of these systems has been questioned and their uncertainties are poorly constrained, both in terms of the spatial extent of forest loss and timing of change. Here, using annual time series of 5 m optical imagery at two sites in the Brazilian Amazon, we demonstrate that GFW more accurately detects forest loss than the coarser-resolution FORMA or Brazil’s national-level PRODES product, though all underestimate the rate of loss. We conclude GFW provides robust indicators of forest loss, at least for larger-scale forest change, but under-predicts losses driven by small-scale disturbances (< 2 ha), even though these are much larger than its minimum mapping unit (0.09 ha).

  18. Soil map disaggregation improved by soil-landscape relationships, area-proportional sampling and random forest implementation

    DEFF Research Database (Denmark)

    Møller, Anders Bjørn; Malone, Brendan P.; Odgers, Nathan

    implementation generally improved the algorithm’s ability to predict the correct soil class. The implementation of soil-landscape relationships and area-proportional sampling generally increased the calculation time, while the random forest implementation reduced the calculation time. In the most successful......Detailed soil information is often needed to support agricultural practices, environmental protection and policy decisions. Several digital approaches can be used to map soil properties based on field observations. When soil observations are sparse or missing, an alternative approach...... is to disaggregate existing conventional soil maps. At present, the DSMART algorithm represents the most sophisticated approach for disaggregating conventional soil maps (Odgers et al., 2014). The algorithm relies on classification trees trained from resampled points, which are assigned classes according...

  19. Mapping Congo Basin vegetation types from 300 m and 1 km multi-sensor time series for carbon stocks and forest areas estimation

    Directory of Open Access Journals (Sweden)

    A. Verhegghen

    2012-12-01

    Full Text Available This study aims to contribute to the understanding of the Congo Basin forests by delivering a detailed map of vegetation types with an improved spatial discrimination and coherence for the whole Congo Basin region. A total of 20 land cover classes were described with the standardized Land Cover Classification System (LCCS developed by the FAO. Based on a semi-automatic processing chain, the Congo Basin vegetation types map was produced by combining 19 months of observations from the Envisat MERIS full resolution products (300 m and 8 yr of daily SPOT VEGETATION (VGT reflectances (1 km. Four zones (north, south and two central were delineated and processed separately according to their seasonal and cloud cover specificities. The discrimination between different vegetation types (e.g. forest and savannas was significantly improved thanks to the MERIS sharp spatial resolution. A better discrimination was achieved in cloudy areas by taking advantage of the temporal consistency of the SPOT VGT observations. This resulted in a precise delineation of the spatial extent of the rural complex in the countries situated along the Atlantic coast. Based on this new map, more accurate estimates of the surface areas of forest types were produced for each country of the Congo Basin. Carbon stocks of the Basin were evaluated to a total of 49 360 million metric tons. The regional scale of the map was an opportunity to investigate what could be an appropriate tree cover threshold for a forest class definition in the Congo Basin countries. A 30% tree cover threshold was suggested. Furthermore, the phenology of the different vegetation types was illustrated systematically with EVI temporal profiles. This Congo Basin forest types map reached a satisfactory overall accuracy of 71.5% and even 78.9% when some classes are aggregated. The values of the Cohen's kappa coefficient, respectively 0.64 and 0.76 indicates a result significantly better than random.

  20. Forest Tree Species Distribution Mapping Using Landsat Satellite Imagery and Topographic Variables with the Maximum Entropy Method in Mongolia

    Science.gov (United States)

    Hao Chiang, Shou; Valdez, Miguel; Chen, Chi-Farn

    2016-06-01

    Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM) were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface reflectance coupled

  1. FOREST TREE SPECIES DISTRIBUTION MAPPING USING LANDSAT SATELLITE IMAGERY AND TOPOGRAPHIC VARIABLES WITH THE MAXIMUM ENTROPY METHOD IN MONGOLIA

    Directory of Open Access Journals (Sweden)

    S. H. Chiang

    2016-06-01

    Full Text Available Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface

  2. Community social capital on the timing of sexual debut and teen birth in Nicaragua: a multilevel approach.

    Science.gov (United States)

    Mendez Rojas, Bomar; Beogo, Idrissa; Owili, Patrick Opiyo; Adesanya, Oluwafunmilade; Chen, Chuan-Yu

    2016-09-15

    Community attributes have been gradually recognized as critical determinants shaping sexual behaviors in young population; nevertheless, most of the published studies were conducted in high income countries. The study aims to examine the association between community social capital with the time to sexual onset and to first birth in Central America. Building upon the 2011/12 Demographic and Health Survey conducted in Nicaragua, we identified a sample of 2766 community-dwelling female adolescents aged 15 to 19 years. Multilevel survival analyses were performed to estimate the risks linked with three domains of community social capital (i.e., norms, resource and social network). Higher prevalence of female sexual debut (norms) and higher proportion of secondary school or higher education (resource) in the community are associated with an earlier age of sexual debut by 47 % (p teen birth (p teen childbearing (p teen-onset sex and birth. The norm and resource aspects of social capital appeared differentially associated with adolescent sexual and reproductive behaviors. Interventions aiming to tackle unfavorable sexual and reproductive outcomes in young people should be devised and implemented with integration of social process.

  3. Preliminary Assessment of JERS-1 SAR to Discriminating Boreal Landscape Features for the Boreal Forest Mapping Project

    Science.gov (United States)

    McDonald, Kyle; Williams, Cynthia; Podest, Erika; Chapman, Bruce

    1999-01-01

    This paper presents an overview of the JERS-1 North American Boreal Forest Mapping Project and a preliminary assessment of JERS-1 SAR imagery for application to discriminating features applicable to boreal landscape processes. The present focus of the JERS-1 North American Boreal Forest Mapping Project is the production of continental scale wintertime and summertime SAR mosaics of the North American boreal forest for distribution to the science community. As part of this effort, JERS-1 imagery has been collected over much of Alaska and Canada during the 1997-98 winter and 1998 summer seasons. To complete the mosaics, these data will be augmented with data collected during previous years. These data will be made available to the scientific community via CD ROM containing these and similar data sets compiled from companion studies of Asia and Europe. Regional landscape classification with SAR is important for the baseline information it will provide about distribution of woodlands, positions of treeline, current forest biomass, distribution of wetlands, and extent of major rivercourses. As well as setting the stage for longer term change detection, comparisons across several years provides additional baseline information about short-term landscape change. Rapid changes, including those driven by fire, permafrost heat balance, flooding, and insect outbreaks can dominate boreal systems. We examine JERS-1 imagery covering selected sites in Alaska and Canada to assess quality and applicability to such relevant ecological and hydrological issues. The data are generally of high quality and illustrate many potential applications. A texture-based classification scheme is applied to selected regions to assess the applicability of these data for distinguishing distribution of such landcover types as wetland, tundra, woodland and forested landscapes.

  4. Temporal mapping of deforestation and forest degradation in Nepal: Applications to forest conservation

    NARCIS (Netherlands)

    Panta, M.; Kim, K.; Joshi, C.

    2008-01-01

    Deforestation and forest degradation are associated and progressive processes resulting in the conversion of forest area into a mosaic of mature forest fragments, pasture, and degraded habitat. Monitoring of forest landscape spatial structures has been recommended to detect degenerative trends in

  5. Integrating Expert Knowledge into Mapping Ecosystem Services Trade-offs for Sustainable Forest Management

    Directory of Open Access Journals (Sweden)

    Adrienne Grêt-Regamey

    2013-09-01

    Full Text Available Mountain ecosystems are highly sensitive to global change. In fact, the continued capacity of mountain regions to provide goods and services to society is threatened by the impact of environmental changes on ecosystems. Although mapping ecosystem services values is known to support sustainable resource management, the integration of spatially explicit local expert knowledge on ecosystem dynamics and social responses to global changes has not yet been integrated in the modeling process. This contribution demonstrates the importance of integrating local knowledge into the spatially explicit valuation of ecosystem services. Knowledge acquired by expert surveys flows into a GIS-based Bayesian Network for valuing forest ecosystem services under a land-use and a climate change scenario in a case study in the Swiss Alps. Results show that including expert knowledge in ecosystem services mapping not only reduces uncertainties considerably, but also has an important effect on the ecosystem services values. Particularly the iterative process between integrating expert knowledge into the modeling process and mapping ecosystem services guarantees a continuous improvement of ecosystem services values maps while opening a new way for mutual learning between scientists and stakeholders which might support adaptive resource management.

  6. Exploiting Growing Stock Volume Maps for Large Scale Forest Resource Assessment: Cross-Comparisons of ASAR- and PALSAR-Based GSV Estimates with Forest Inventory in Central Siberia

    Directory of Open Access Journals (Sweden)

    Christian Hüttich

    2014-07-01

    Full Text Available Growing stock volume is an important biophysical parameter describing the state and dynamics of the Boreal zone. Validation of growing stock volume (GSV maps based on satellite remote sensing is challenging due to the lack of consistent ground reference data. The monitoring and assessment of the remote Russian forest resources of Siberia can only be done by integrating remote sensing techniques and interdisciplinary collaboration. In this paper, we assess the information content of GSV estimates in Central Siberian forests obtained at 25 m from ALOS-PALSAR and 1 km from ENVISAT-ASAR backscatter data. The estimates have been cross-compared with respect to forest inventory data showing 34% relative RMSE for the ASAR-based GSV retrievals and 39.4% for the PALSAR-based estimates of GSV. Fragmentation analyses using a MODIS-based land cover dataset revealed an increase of retrieval error with increasing fragmentation of the landscape. Cross-comparisons of multiple SAR-based GSV estimates helped to detect inconsistencies in the forest inventory data and can support an update of outdated forest inventory stands.

  7. Mapping Rubber Plantations and Natural Forests in Xishuangbanna (Southwest China Using Multi-Spectral Phenological Metrics from MODIS Time Series

    Directory of Open Access Journals (Sweden)

    Sebastian van der Linden

    2013-05-01

    Full Text Available We developed and evaluated a new approach for mapping rubber plantations and natural forests in one of Southeast Asia’s biodiversity hot spots, Xishuangbanna in China. We used a one-year annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS, Enhanced Vegetation Index (EVI and short-wave infrared (SWIR reflectance data to develop phenological metrics. These phenological metrics were used to classify rubber plantations and forests with the Random Forest classification algorithm. We evaluated which key phenological characteristics were important to discriminate rubber plantations and natural forests by estimating the influence of each metric on the classification accuracy. As a benchmark, we compared the best classification with a classification based on the full, fitted time series data. Overall classification accuracies derived from EVI and SWIR time series alone were 64.4% and 67.9%, respectively. Combining the phenological metrics from EVI and SWIR time series improved the accuracy to 73.5%. Using the full, smoothed time series data instead of metrics derived from the time series improved the overall accuracy only slightly (1.3%, indicating that the phenological metrics were sufficient to explain the seasonal changes captured by the MODIS time series. The results demonstrate a promising utility of phenological metrics for mapping and monitoring rubber expansion with MODIS.

  8. Rokkashomura: debut of the nuclear fuel cycle business

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    Japan Nuclear Fuel Industries and local governments signed the safety agreement, and the work began to initiate the operation of a uranium enrichment plant. In this way, the national Rokkashomura project to be constructed with the total cost of 1.2 trillion yen marked the debut of nuclear fuel cycle business in Japan. The public hearing concerning the low level radioactive waste storage facility was finished. However, a fuel reprocessing plant has not advanced since the national government did not clarify the policy for the management of high level rad-waste from the plant. Gubernatorial election was the best thing to happen for the public acceptance, and the local opposition movement lost steam. The operation of the uranium enrichment plant is to begin next January, and the construction of the low level waste storage facility proceeds on schedule. Regarding the fuel reprocessing plant, the public hearing is to be held in autumn, but it faces difficulties. The siting of nuclear fuel cycle facilities has already produced benefits for the local economy. 18 business establishments representing 15 firms have so far decided to open in Aomori Prefecture. JNFI and JNFS began the specific study for merger. (K.I.)

  9. Using satellite image-based maps and ground inventory data to estimate the area of the remaining Atlantic forest in the Brazilian state of Santa Catarina

    Science.gov (United States)

    Alexander C. Vibrans; Ronald E. McRoberts; Paolo Moser; Adilson L. Nicoletti

    2013-01-01

    Estimation of large area forest attributes, such as area of forest cover, from remote sensing-based maps is challenging because of image processing, logistical, and data acquisition constraints. In addition, techniques for estimating and compensating for misclassification and estimating uncertainty are often unfamiliar. Forest area for the state of Santa Catarina in...

  10. Using indigenous knowledge to link hyper-temporal land cover mapping with land use in the Venezuelan Amazon: "The Forest Pulse".

    Science.gov (United States)

    Olivero, Jesús; Ferri, Francisco; Acevedo, Pelayo; Lobo, Jorge M; Fa, John E; Farfán, Miguel Á; Romero, David; Real, Raimundo

    2016-12-01

    Remote sensing and traditional ecological knowledge (TEK) can be combined to advance conservation of remote tropical regions, e.g. Amazonia, where intensive in situ surveys are often not possible. Integrating TEK into monitoring and management of these areas allows for community participation, as well as for offering novel insights into sustainable resource use. In this study, we developed a 250 m resolution land-cover map of the Western Guyana Shield (Venezuela) based on remote sensing, and used TEK to validate its relevance for indigenous livelihoods and land uses. We first employed a hyper-temporal remotely sensed vegetation index to derive a land classification system. During a 1 300 km, eight day fluvial expedition in roadless areas in the Amazonas State (Venezuela), we visited six indigenous communities who provided geo-referenced data on hunting, fishing and farming activities. We overlaid these TEK data onto the land classification map, to link land classes with indigenous use. We characterized land classes using patterns of greenness temporal change and topo-hydrological information, and proposed 12 land-cover types, grouped into five main landscapes: 1) water bodies; 2) open lands/forest edges; 3) evergreen forests; 4) submontane semideciduous forests, and 5) cloud forests. Each land cover class was identified with a pulsating profile describing temporal changes in greenness, hence we labelled our map as "The Forest Pulse". These greenness profiles showed a slightly increasing trend, for the period 2000 to 2009, in the land classes representing grassland and scrubland, and a slightly decreasing trend in the classes representing forests. This finding is consistent with a gain in carbon in grassland as a consequence of climate warming, and also with some loss of vegetation in the forests. Thus, our classification shows potential to assess future effects of climate change on landscape. Several classes were significantly connected with agriculture, fishing

  11. High-resolution mapping of time since disturbance and forest carbon flux from remote sensing and inventory data to assess harvest, fire, and beetle disturbance legacies in the Pacific Northwest

    Directory of Open Access Journals (Sweden)

    H. Gu

    2016-11-01

    Full Text Available Accurate assessment of forest carbon storage and uptake is central to policymaking aimed at mitigating climate change and understanding the role forests play in the global carbon cycle. Disturbances have highly diverse impacts on forest carbon dynamics, making them a challenge to quantify and report. Time since disturbance is a key intermediate determinant that aids the assessment of disturbance-driven carbon emissions and removals legacies. We propose a new methodology of quantifying time since disturbance and carbon flux across forested landscapes in the Pacific Northwest (PNW at a fine scale (30 m by combining remote sensing (RS-based disturbance year, disturbance type, and above-ground biomass with forest inventory data. When a recent disturbance is detected, time since disturbance can be directly determined by combining three RS-derived disturbance products, or time since the last stand clearing can be inferred from a RS-derived 30 m biomass map and field inventory-derived species-specific biomass accumulation curves. Net ecosystem productivity (NEP is further mapped based on carbon stock and flux trajectories derived from the Carnegie-Ames-Stanford Approach (CASA model in our prior work that described how NEP changes with time following harvest, fire, or bark beetle disturbances of varying severity. Uncertainties from biomass map and forest inventory data were propagated by probabilistic sampling to provide a statistical distribution of stand age and NEP for each forest pixel. We mapped mean, standard deviation, and statistical distribution of stand age and NEP at 30 m in the PNW region. Our map indicated a net ecosystem productivity of 5.9 Tg C yr−1 for forestlands circa 2010 in the study area, with net uptake in relatively mature (> 24 years old forests (13.6 Tg C yr−1 overwhelming net negative NEP from tracts that had recent harvests (−6.4 Tg C yr−1, fires (−0.5 Tg C yr−1, and bark beetle

  12. Aboveground biomass mapping of African forest mosaics using canopy texture analysis: toward a regional approach.

    Science.gov (United States)

    Bastin, Jean-François; Barbier, Nicolas; Couteron, Pierre; Adams, Benoît; Shapiro, Aurélie; Bogaert, Jan; De Cannière, Charles

    In the context of the reduction of greenhouse gas emissions caused by deforestation and forest degradation (the REDD+ program), optical very high resolution (VHR) satellite images provide an opportunity to characterize forest canopy structure and to quantify aboveground biomass (AGB) at less expense than methods based on airborne remote sensing data. Among the methods for processing these VHR images, Fourier textural ordination (FOTO) presents a good method to detect forest canopy structural heterogeneity and therefore to predict AGB variations. Notably, the method does not saturate at intermediate AGB values as do pixelwise processing of available space borne optical and radar signals. However, a regional-scale application requires overcoming two difficulties: (1) instrumental effects due to variations in sun–scene–sensor geometry or sensor-specific responses that preclude the use of wide arrays of images acquired under heterogeneous conditions and (2) forest structural diversity including monodominant or open canopy forests, which are of particular importance in Central Africa. In this study, we demonstrate the feasibility of a rigorous regional study of canopy texture by harmonizing FOTO indices of images acquired from two different sensors (Geoeye-1 and QuickBird-2) and different sun–scene–sensor geometries and by calibrating a piecewise biomass inversion model using 26 inventory plots (1 ha) sampled across very heterogeneous forest types. A good agreement was found between observed and predicted AGB (residual standard error [RSE] = 15%; R2 = 0.85; P biomass map (100-m pixels) was produced for a 400-km2 area, and predictions obtained from both imagery sources were consistent with each other (r = 0.86; slope = 1.03; intercept = 12.01 Mg/ha). These results highlight the horizontal structure of forest canopy as a powerful descriptor of the entire forest stand structure and heterogeneity. In particular, we show that quantitative metrics resulting from such

  13. Forest report 2013; Waldzustandsbericht 2013

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2013-07-01

    This forest report of Lower Saxony (Germany) contains the following topics: weather and climate, forest protection, crown defoliation, infiltrated substances, environmental monitoring, insects and fungi, forest soil survey and forest site mapping, and nutritional status of beech on loess.

  14. Tropical Forest Fire Susceptibility Mapping at the Cat Ba National Park Area, Hai Phong City, Vietnam, Using GIS-Based Kernel Logistic Regression

    Directory of Open Access Journals (Sweden)

    Dieu Tien Bui

    2016-04-01

    Full Text Available The Cat Ba National Park area (Vietnam with its tropical forest is recognized as being part of the world biodiversity conservation by the United Nations Educational, Scientific and Cultural Organization (UNESCO and is a well-known destination for tourists, with around 500,000 travelers per year. This area has been the site for many research projects; however, no project has been carried out for forest fire susceptibility assessment. Thus, protection of the forest including fire prevention is one of the main concerns of the local authorities. This work aims to produce a tropical forest fire susceptibility map for the Cat Ba National Park area, which may be helpful for the local authorities in forest fire protection management. To obtain this purpose, first, historical forest fires and related factors were collected from various sources to construct a GIS database. Then, a forest fire susceptibility model was developed using Kernel logistic regression. The quality of the model was assessed using the Receiver Operating Characteristic (ROC curve, area under the ROC curve (AUC, and five statistical evaluation measures. The usability of the resulting model is further compared with a benchmark model, the support vector machine (SVM. The results show that the Kernel logistic regression model has a high level of performance in both the training and validation dataset, with a prediction capability of 92.2%. Since the Kernel logistic regression model outperforms the benchmark model, we conclude that the proposed model is a promising alternative tool that should also be considered for forest fire susceptibility mapping in other areas. The results of this study are useful for the local authorities in forest planning and management.

  15. Investigating the Capability of IRS-P6-LISS IV Satellite Image for Pistachio Forests Density Mapping (case Study: Northeast of Iran)

    Science.gov (United States)

    Hoseini, F.; Darvishsefat, A. A.; Zargham, N.

    2012-07-01

    In order to investigate the capability of satellite images for Pistachio forests density mapping, IRS-P6-LISS IV data were analyzed in an area of 500 ha in Iran. After geometric correction, suitable training areas were determined based on fieldwork. Suitable spectral transformations like NDVI, PVI and PCA were performed. A ground truth map included of 34 plots (each plot 1 ha) were prepared. Hard and soft supervised classifications were performed with 5 density classes (0-5%, 5-10%, 10-15%, 15-20% and > 20%). Because of low separability of classes, some classes were merged and classifications were repeated with 3 classes. Finally, the highest overall accuracy and kappa coefficient of 70% and 0.44, respectively, were obtained with three classes (0-5%, 5-20%, and > 20%) by fuzzy classifier. Considering the low kappa value obtained, it could be concluded that the result of the classification was not desirable. Therefore, this approach is not appropriate for operational mapping of these valuable Pistachio forests.

  16. Stratifying FIA Ground Plots Using A 3-Year Old MRLC Forest Cover Map and Current TM Derived Variables Selected By "Decision Tree" Classification

    Science.gov (United States)

    Michael Hoppus; Stan Arner; Andrew Lister

    2001-01-01

    A reduction in variance for estimates of forest area and volume in the state of Connecticut was accomplished by stratifying FIA ground plots using raw, transformed and classified Landsat Thematic Mapper (TM) imagery. A US Geological Survey (USGS) Multi-Resolution Landscape Characterization (MRLC) vegetation cover map for Connecticut was used to produce a forest/non-...

  17. Mapping discourses using Q methodology in Matang Mangrove Forest, Malaysia.

    Science.gov (United States)

    Hugé, Jean; Vande Velde, Katherine; Benitez-Capistros, Francisco; Japay, Jan Harold; Satyanarayana, Behara; Nazrin Ishak, Mohammad; Quispe-Zuniga, Melissa; Mohd Lokman, Bin Husain; Sulong, Ibrahim; Koedam, Nico; Dahdouh-Guebas, Farid

    2016-12-01

    The sustainable management of natural resources requires the consideration of multiple stakeholders' perspectives and knowledge claims, in order to inform complex and possibly contentious decision-making dilemmas. Hence, a better understanding of why people in particular contexts do manage natural resources in a particular way is needed. Focusing on mangroves, highly productive tropical intertidal forests, this study's first aim is to map the diversity of subjective viewpoints among a range of stakeholders on the management of Matang Mangrove Forest in peninsular Malaysia. Secondly, this study aims to feed the reflection on the possible consequences of the diversity of perspectives for the future management of mangroves in Malaysia and beyond. The use of the semi-quantitative Q methodology allowed us to identify three main discourses on mangrove management: i. the optimization discourse, stressing the need to improve the current overall satisfactory management regime; ii. the 'change for the better' discourse, which focuses on increasingly participatory management and on ecotourism; and iii. the conservative 'business as usual' discourse. The existence of common points of connection between the discourses and their respective supporters provides opportunities for modifications of mangrove management regimes. Acknowledging this diversity of viewpoints, reflecting how different stakeholders see and talk about mangrove management, highlights the need to develop pro-active and resilient natural resource management approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Polarimetric data for tropical forest monitoring : studies at the Colombian Amazon

    NARCIS (Netherlands)

    Quiñones Fernández, M.

    2002-01-01



    An urgent need exists for accurate data on the actual tropical forest extent, deforestation, forest structure, regeneration and diversity. The availability of accurate land cover maps and tropical forest type maps, and the possibility to update these maps frequently, is of

  19. Mapping multi-scale vascular plant richness in a forest landscape with integrated LiDAR and hyperspectral remote-sensing.

    Science.gov (United States)

    Hakkenberg, C R; Zhu, K; Peet, R K; Song, C

    2018-02-01

    The central role of floristic diversity in maintaining habitat integrity and ecosystem function has propelled efforts to map and monitor its distribution across forest landscapes. While biodiversity studies have traditionally relied largely on ground-based observations, the immensity of the task of generating accurate, repeatable, and spatially-continuous data on biodiversity patterns at large scales has stimulated the development of remote-sensing methods for scaling up from field plot measurements. One such approach is through integrated LiDAR and hyperspectral remote-sensing. However, despite their efficiencies in cost and effort, LiDAR-hyperspectral sensors are still highly constrained in structurally- and taxonomically-heterogeneous forests - especially when species' cover is smaller than the image resolution, intertwined with neighboring taxa, or otherwise obscured by overlapping canopy strata. In light of these challenges, this study goes beyond the remote characterization of upper canopy diversity to instead model total vascular plant species richness in a continuous-cover North Carolina Piedmont forest landscape. We focus on two related, but parallel, tasks. First, we demonstrate an application of predictive biodiversity mapping, using nonparametric models trained with spatially-nested field plots and aerial LiDAR-hyperspectral data, to predict spatially-explicit landscape patterns in floristic diversity across seven spatial scales between 0.01-900 m 2 . Second, we employ bivariate parametric models to test the significance of individual, remotely-sensed predictors of plant richness to determine how parameter estimates vary with scale. Cross-validated results indicate that predictive models were able to account for 15-70% of variance in plant richness, with LiDAR-derived estimates of topography and forest structural complexity, as well as spectral variance in hyperspectral imagery explaining the largest portion of variance in diversity levels. Importantly

  20. Satellite-Based Derivation of High-Resolution Forest Information Layers for Operational Forest Management

    Directory of Open Access Journals (Sweden)

    Johannes Stoffels

    2015-06-01

    Full Text Available A key factor for operational forest management and forest monitoring is the availability of up-to-date spatial information on the state of forest resources. Earth observation can provide valuable contributions to these information needs. The German federal state of Rhineland-Palatinate transferred its inherited forest information system to a new architecture that is better able to serve the needs of centralized inventory and planning services, down to the level of forest districts. During this process, a spatially adaptive classification approach was developed to derive high-resolution forest information layers (e.g., forest type, tree species distribution, development stages based on multi-temporal satellite data. This study covers the application of the developed approach to a regional scale (federal state level and the further adaptation of the design to meet the information needs of the state forest service. The results confirm that the operational requirements for mapping accuracy can, in principle, be fulfilled. However, the state-wide mapping experiment also revealed that the ability to meet the required level of accuracy is largely dependent on the availability of satellite observations within the optimum phenological time-windows.

  1. Estimating forest carbon stocks in tropical dry forests of Zimbabwe ...

    African Journals Online (AJOL)

    Estimation and mapping of forest dendrometric characteristics such as carbon stocks using remote sensing techniques is fundamental for improved understanding of the role of forests in the carbon cycle and climate change. In this study, we tested whether and to what extent spectral transforms, i.e. vegetation indices ...

  2. Spatial mapping and analysis of aerosols during a forest fire using computational mobile microscopy

    Science.gov (United States)

    Wu, Yichen; Shiledar, Ashutosh; Luo, Yi; Wong, Jeffrey; Chen, Cheng; Bai, Bijie; Zhang, Yibo; Tamamitsu, Miu; Ozcan, Aydogan

    2018-02-01

    Forest fires are a major source of particulate matter (PM) air pollution on a global scale. The composition and impact of PM are typically studied using only laboratory instruments and extrapolated to real fire events owing to a lack of analytical techniques suitable for field-settings. To address this and similar field test challenges, we developed a mobilemicroscopy- and machine-learning-based air quality monitoring platform called c-Air, which can perform air sampling and microscopic analysis of aerosols in an integrated portable device. We tested its performance for PM sizing and morphological analysis during a recent forest fire event in La Tuna Canyon Park by spatially mapping the PM. The result shows that with decreasing distance to the fire site, the PM concentration increases dramatically, especially for particles smaller than 2 µm. Image analysis from the c-Air portable device also shows that the increased PM is comparatively strongly absorbing and asymmetric, with an aspect ratio of 0.5-0.7. These PM features indicate that a major portion of the PM may be open-flame-combustion-generated element carbon soot-type particles. This initial small-scale experiment shows that c-Air has some potential for forest fire monitoring.

  3. 78 FR 17632 - Caribou-Targhee National Forest; Idaho and Wyoming; Amendment to the Targhee Revised Forest Plan...

    Science.gov (United States)

    2013-03-22

    ...; Amendment to the Targhee Revised Forest Plan--Canada Lynx Habitat AGENCY: Forest Service, USDA. ACTION... Forest proposes to amend the Targhee Revised Forest Plan (1997) to include a map identifying specific... Administrative Review Process: The decision on this proposed plan amendment will be subject to the objection...

  4. Spaceborne Radar for Mapping Forest and Land Use Changes

    DEFF Research Database (Denmark)

    Joshi, Neha Pankaj

    Degradation (REDD+). The implementation and effectiveness of such mechanisms relies partially on continuous observations of forests using satellite technology and partially on ground-based measurements of forest aboveground volume/biomass (AGV/AGB), carbon density and changes therein. Together, these means...... of forest monitoring enable the development of policies and measures to alter current trends in global forest and biodiversity loss. This thesis investigates the use of long wavelength (~23 cm, L-band) spaceborne radar, which has all-weather and canopy-penetration capabilities, acquired by the Advanced Land...... Observing Satellite (ALOS) for forest monitoring. Using a combination of local expert knowledge, plot inventories, and data from lidar and optical sensors, it aims to understand (1) whether forest disturbance dynamics may be detected with radar, and (2) what physical and macroecological properties influence...

  5. Learning in Virtual Forest: A Forest Ecosystem in the Web-Based Learning Environment

    Science.gov (United States)

    Jussila, Terttu; Virtanen, Viivi

    2014-01-01

    Virtual Forest is a web-based, open-access learning environment about forests designed for primary-school pupils between the ages of 10 and 13 years. It is pedagogically designed to develop an understanding of ecology, to enhance conceptual development and to give a holistic view of forest ecosystems. Various learning tools, such as concept maps,…

  6. Regional Assessment of Remote Forests and Black Bear Habitat from Forest Resource Surveys

    Science.gov (United States)

    Victor A. Rudis; John B. Tansey

    1995-01-01

    We developed a spatially explicit modeling approach, using a county-scaled remote forest (i.e., forested area reserved from or having no direct human interference) assessment derived from 1984-1990 forest resource inventory data and a 1984 black bear (Ursus americantus) range map for 12 states in the southern United States.We defined minimum suitable and optimal black...

  7. Community social capital on the timing of sexual debut and teen birth in Nicaragua: a multilevel approach

    Directory of Open Access Journals (Sweden)

    Bomar Mendez Rojas

    2016-09-01

    Full Text Available Abstract Background Community attributes have been gradually recognized as critical determinants shaping sexual behaviors in young population; nevertheless, most of the published studies were conducted in high income countries. The study aims to examine the association between community social capital with the time to sexual onset and to first birth in Central America. Methods Building upon the 2011/12 Demographic and Health Survey conducted in Nicaragua, we identified a sample of 2766 community-dwelling female adolescents aged 15 to 19 years. Multilevel survival analyses were performed to estimate the risks linked with three domains of community social capital (i.e., norms, resource and social network. Results Higher prevalence of female sexual debut (norms and higher proportion of secondary school or higher education (resource in the community are associated with an earlier age of sexual debut by 47 % (p < 0.05 and 16 %, respectively (p < 0.001. Living in a community with a high proportion of females having a child increases the hazard of teen birth (p < 0.001 and resource is negatively associated with teen childbearing (p < 0.05. Residential stability and community religious composition (social network were not linked with teen-onset sex and birth. Conclusions The norm and resource aspects of social capital appeared differentially associated with adolescent sexual and reproductive behaviors. Interventions aiming to tackle unfavorable sexual and reproductive outcomes in young people should be devised and implemented with integration of social process.

  8. Mapping Spatial Distribution of Larch Plantations from Multi-Seasonal Landsat-8 OLI Imagery and Multi-Scale Textures Using Random Forests

    Directory of Open Access Journals (Sweden)

    Tian Gao

    2015-02-01

    Full Text Available The knowledge about spatial distribution of plantation forests is critical for forest management, monitoring programs and functional assessment. This study demonstrates the potential of multi-seasonal (spring, summer, autumn and winter Landsat-8 Operational Land Imager imageries with random forests (RF modeling to map larch plantations (LP in a typical plantation forest landscape in North China. The spectral bands and two types of textures were applied for creating 675 input variables of RF. An accuracy of 92.7% for LP, with a Kappa coefficient of 0.834, was attained using the RF model. A RF-based importance assessment reveals that the spectral bands and bivariate textural features calculated by pseudo-cross variogram (PC strongly promoted forest class-separability, whereas the univariate textural features influenced weakly. A feature selection strategy eliminated 93% of variables, and then a subset of the 47 most essential variables was generated. In this subset, PC texture derived from summer and winter appeared the most frequently, suggesting that this variability in growing peak season and non-growing season can effectively enhance forest class-separability. A RF classifier applied to the subset led to 91.9% accuracy for LP, with a Kappa coefficient of 0.829. This study provides an insight into approaches for discriminating plantation forests with phenological behaviors.

  9. Forests on the edge: evaluating contributions of and threats to America's private forest lands

    Science.gov (United States)

    Mark Hatfield; Ronald E. McRoberts; Dacia M. Meneguzzo; Mike Dechter; < i> et al< /i>

    2007-01-01

    The Forests on the Edge project, sponsored by the U.S. Department of Agriculture Forest Service, uses geographic information systems to construct and analyze maps depicting ecological, social, and economic contributions of America's private forest lands and threats to those contributions. Watersheds across the conterminous United States are ranked relative to the...

  10. Harmonizing estimates of forest land area from national-level forest inventory and satellite imagery

    Science.gov (United States)

    Bonnie Ruefenacht; Mark D. Nelson; Mark Finco

    2009-01-01

    Estimates of forest land area are derived both from national-level forest inventories and satellite image-based map products. These estimates can differ substantially within subregional extents (e.g., states or provinces) primarily due to differences in definitions of forest land between inventory- and image-based approaches. We present a geospatial modeling approach...

  11. The Influence of Forest Management Regimes on Deforestation in a Central Indian Dry Deciduous Forest Landscape

    OpenAIRE

    Shivani Agarwal; Harini Nagendra; Rucha Ghate

    2016-01-01

    This research examines the impact of forest management regimes, with various degrees of restriction, on forest conservation in a dry deciduous Indian forest landscape. Forest change is mapped using Landsat satellite images from 1977, 1990, 1999, and 2011. The landscape studied has lost 1478 km2 of dense forest cover between 1977 and 2011, with a maximum loss of 1002 km2 of dense forest between 1977 and 1990. The number of protected forest areas has increased, concomitant with an increase in r...

  12. Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery

    Science.gov (United States)

    Castillo, Jose Alan A.; Apan, Armando A.; Maraseni, Tek N.; Salmo, Severino G.

    2017-12-01

    The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82-0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8-28.5 Mg ha-1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement

  13. Regression modeling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral data

    Science.gov (United States)

    Andrew T. Hudak; Nicholas L. Crookston; Jeffrey S. Evans; Michael K. Falkowski; Alistair M. S. Smith; Paul E. Gessler; Penelope Morgan

    2006-01-01

    We compared the utility of discrete-return light detection and ranging (lidar) data and multispectral satellite imagery, and their integration, for modeling and mapping basal area and tree density across two diverse coniferous forest landscapes in north-central Idaho. We applied multiple linear regression models subset from a suite of 26 predictor variables derived...

  14. Threats to private forest lands in the U.S.A.: a forests on the edge study

    Science.gov (United States)

    Mark H. Hatfield; Ronald E. McRoberts; Dacia M. Meneguzzo; Sara. Comas

    2010-01-01

    The Forests on the Edge project, sponsored by the USDA Forest Service, uses geographic information systems to construct and analyze maps depicting threats to the contributions of America’s private forest lands. For this study, watersheds across the conterminous United States are evaluated with respect to the amount of their private forest land. Watersheds with at least...

  15. Participatory Resource Mapping for Livelihood Values Derived from the Forest in Ekondo-Titi Subregion, Cameroon: A Gender Analysis

    Directory of Open Access Journals (Sweden)

    Daniel B. Etongo

    2012-01-01

    Full Text Available Increasingly, the multiplicity of products, services, and values, and the diversity of interests from different resource users and groups, is being acknowledged as vital for sustainable use. This calls for a shift from protection to sustainable use and to resource-user focus. The aim of this study is to identify the spatial occurrence of livelihood values through participatory resource mapping, their changes over time and alternatives for sustainable management. A participatory resource mapping study was conducted with local community, including important stakeholders in Ekondo-Titi subregion of Cameroon. The research technique which focused on gender revealed different patterns of forest resources and changes on the landscape. The study concludes that the importance of resources varies between men and women in Ekondo-Titi subregion of Cameroon, implying that resources may have multipurpose functions, but its exact role depends on the needs of the user groups that utilize them. The divergence of opinion on certain resources is a clear indication of preferences that are gender motivated. The study also revealed that the greatest impact of land use change is the conversion of forest land into agriculture.

  16. Digital data collection in forest dynamics plots

    Science.gov (United States)

    Faith Inman-Narahari; Christian Giardina; Rebecca Ostertag; Susan Cordell; Lawren Sack

    2010-01-01

    Summary 1. Computers are widely used in all aspects of research but their application to in-field data collection for forest plots has rarely been evaluated. 2. We developed digital data collection methods using ESRI mapping software and ruggedized field computers to map and measure ~30 000 trees in two 4-ha forest dynamics plots in wet and dry...

  17. Web mapping: tools and solutions for creating interactive maps of forestry interest

    Directory of Open Access Journals (Sweden)

    Notarangelo G

    2011-12-01

    Full Text Available The spread of geobrowsers as tools for displaying geographically referenced information provides insights and opportunities to those who, not being specialists in Geographic Information Systems, want to take advantage from exploration and communication power offered by these software. Through the use of web services such as Google Maps and the use of suitable markup languages, one can create interactive maps starting from highly heterogeneous data and information. These interactive maps can also be easily distributed and shared with Internet users, because they do not need to use proprietary software nor special skills but only a web browser. Unlike the maps created with GIS, whose output usually is a static image, the interactive maps retain all their features to users advantage. This paper describes a web application that, using the Keyhole Markup Language and the free service of Google Maps, produces choropleth maps relating to some forest indicators estimated by the last Italian National Forest Inventory. The creation of a map is done through a simple and intuitive interface. The maps created by users can be downloaded as KML file and can be viewed or modified via the freeware application Google Earth or free and open source GIS software like Quantum GIS. The web application is free and available at www.ricercaforestale.it.

  18. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions.

    Directory of Open Access Journals (Sweden)

    Tomislav Hengl

    Full Text Available 80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS project was established in 2008. Over the period 2008-2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management--organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na. We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15-75% in Root Mean Squared Error (RMSE across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring

  19. Spatial Simulation Modelling of Future Forest Cover Change Scenarios in Luangprabang Province, Lao PDR

    Directory of Open Access Journals (Sweden)

    Khamma Homsysavath

    2011-08-01

    Full Text Available Taking Luangprabang province in Lao Peoples’s Democratic Republic (PDR as an example, we simulated future forest cover changes under the business-as-usual (BAU, pessimistic and optimistic scenarios based on the Markov-cellular automata (MCA model. We computed transition probabilities from satellite-derived forest cover maps (1993 and 2000 using the Markov chains, while the “weights of evidence” technique was used to generate transition potential maps. The initial forest cover map (1993, the transition potential maps and the 1993–2000 transition probabilities were used to calibrate the model. Forest cover simulations were then performed from 1993 to 2007 at an annual time-step. The simulated forest cover map for 2007 was compared to the observed (actual forest cover map for 2007 in order to test the accuracy of the model. Following the successful calibration and validation, future forest cover changes were simulated up to 2014 under different scenarios. The MCA simulations under the BAU and pessimistic scenarios projected that current forest areas would decrease, whereas unstocked forest areas would increase in the future. Conversely, the optimistic scenario projected that current forest areas would increase in the future if strict forestry laws enforcing conservation in protected forest areas are implemented. The three simulation scenarios provide a very good case study for simulating future forest cover changes at the subnational level (Luangprabang province. Thus, the future simulated forest cover changes can possibly be used as a guideline to set reference scenarios as well as undertake REDD/REDD+ preparedness activities within the study area.

  20. Spatio-temporal Change Patterns of Tropical Forests from 2000 to 2014 Using MOD09A1 Dataset

    Science.gov (United States)

    Qin, Y.; Xiao, X.; Dong, J.

    2016-12-01

    Large-scale deforestation and forest degradation in the tropical region have resulted in extensive carbon emissions and biodiversity loss. However, restricted by the availability of good-quality observations, large uncertainty exists in mapping the spatial distribution of forests and their spatio-temporal changes. In this study, we proposed a pixel- and phenology-based algorithm to identify and map annual tropical forests from 2000 to 2014, using the 8-day, 500-m MOD09A1 (v005) product, under the support of Google cloud computing (Google Earth Engine). A temporal filter was applied to reduce the random noises and to identify the spatio-temporal changes of forests. We then built up a confusion matrix and assessed the accuracy of the annual forest maps based on the ground reference interpreted from high spatial resolution images in Google Earth. The resultant forest maps showed the consistent forest/non-forest, forest loss, and forest gain in the pan-tropical zone during 2000 - 2014. The proposed algorithm showed the potential for tropical forest mapping and the resultant forest maps are important for the estimation of carbon emission and biodiversity loss.

  1. An Approach to Mapping Forest Growth Stages in Queensland, Australia through Integration of ALOS PALSAR and Landsat Sensor Data

    Directory of Open Access Journals (Sweden)

    João Carreiras

    2012-08-01

    Full Text Available Whilst extensive clearance of forests in the eastern Australian Brigalow Belt Bioregion (BBB has occurred since European settlement, appropriate management of those that are regenerating can facilitate restoration of biomass (carbon and biodiversity to levels typical of relatively undisturbed or remnant formations. However, maps of forests are different stages of regeneration are needed to facilitate restoration planning, including prevention of further re-clearing. Focusing on the Tara Downs subregion of the BBB and on forests with brigalow (Acacia harpophylla as a component, this research establishes a method for differentiating and mapping early, intermediate and remnant growth stages from Japan Aerospace Exploration Agency (JAXA Advanced Land Observing Satellite (ALOS Phased-Array L-band Synthetic Aperture Radar (PALSAR Fine Beam Dual (FBD L-band HH- and HV-polarisation backscatter and Landsat-derived Foliage Projective Cover (FPC. Using inventory data collected from 74 plots, located in the Tara Downs subregion, forests were assigned to one of three regrowth stages based on their height and cover relative to that of undisturbed stands. The image data were then segmented into objects with each assigned to a growth stage by comparing the distributions of L-band HV and HH polarisation backscatter and FPC to that of reference distributions using a z-test. Comparison with independent assessments of growth stage, based on time-series analysis of aerial photography and SPOT images, established an overall accuracy of > 70%, with this increasing to 90% when intermediate regrowth was excluded and only early-stage regrowth and remnant classes were considered. The proposed method can be adapted to respond to amendments to user-definitions of growth stage and, as regional mosaics of ALOS PALSAR and Landsat FPC are available for Queensland, has application across the state.

  2. Forest Dragon-3: Decadal Trends of Northeastern Forests in China from Earth Observation Synergy

    Science.gov (United States)

    Schmullius, C.; Balling, J.; Schratz, P.; Thiel, C.; Santoro, M.; Wegmuller, U.; Li, Z.; Yong, P.

    2016-08-01

    In Forest DRAGON 3, synergy of Earth Observation products to derive information of decadal trends of forest in northeast China was investigated. Following up the results of Forest-DRAGON 1 and 2, Growing Stock Volume (GSV) products from different years were investigated to derive information on vegetational in north- east China. The BIOMASAR maps of 2005 and 2010, produced within the previous DRAGON projects, set the base for all analyses. We took a closer look at scale problems regarding GSV derivation, which are introduced by differing landcover within one pixel, to investigate differences throughout pixel classes with varying landcover class percentages. We developed an approach to select pixels containing forest only with the aim of undertaking a detailed analysis on retrieved GSV values for such pixels for the years 2005 and 2010. Using existing land cover products at different scales, the plausibility of changes in the BIOMASAR maps were checked.

  3. Utilizing random forests imputation of forest plot data for landscape-level wildfire analyses

    Science.gov (United States)

    Karin L. Riley; Isaac C. Grenfell; Mark A. Finney; Nicholas L. Crookston

    2014-01-01

    Maps of the number, size, and species of trees in forests across the United States are desirable for a number of applications. For landscape-level fire and forest simulations that use the Forest Vegetation Simulator (FVS), a spatial tree-level dataset, or “tree list”, is a necessity. FVS is widely used at the stand level for simulating fire effects on tree mortality,...

  4. Estimating and mapping forest biomass using regression models and Spot-6 images (case study: Hyrcanian forests of north of Iran).

    Science.gov (United States)

    Motlagh, Mohadeseh Ghanbari; Kafaky, Sasan Babaie; Mataji, Asadollah; Akhavan, Reza

    2018-05-21

    Hyrcanian forests of North of Iran are of great importance in terms of various economic and environmental aspects. In this study, Spot-6 satellite images and regression models were applied to estimate above-ground biomass in these forests. This research was carried out in six compartments in three climatic (semi-arid to humid) types and two altitude classes. In the first step, ground sampling methods at the compartment level were used to estimate aboveground biomass (Mg/ha). Then, by reviewing the results of other studies, the most appropriate vegetation indices were selected. In this study, three indices of NDVI, RVI, and TVI were calculated. We investigated the relationship between the vegetation indices and aboveground biomass measured at sample-plot level. Based on the results, the relationship between aboveground biomass values and vegetation indices was a linear regression with the highest level of significance for NDVI in all compartments. Since at the compartment level the correlation coefficient between NDVI and aboveground biomass was the highest, NDVI was used for mapping aboveground biomass. According to the results of this study, biomass values were highly different in various climatic and altitudinal classes with the highest biomass value observed in humid climate and high-altitude class.

  5. Forest resources of the United States, 1992

    Science.gov (United States)

    Douglas S. Powell; Joanne L. Faulkner; David R. Darr; Zhiliang Zhu; Douglas W. MacCleery

    1993-01-01

    The 1987 Resources Planning Act (RPA) Assessment forest resources statistics are updated to 1992, to provide current information on the Nation's forests. Resource tables present estimates of forest area, volume, mortality, growth, removals, and timber products output. Resource data are analyzed, and trends since 1987 are noted. A forest type map produced from...

  6. Global analysis of the protection status of the world's forests

    DEFF Research Database (Denmark)

    Schmitt, Christine B.; Burgess, Neil David; Coad, Lauren

    2009-01-01

    This study presents a global analysis of forest cover and forest protection. An updated Global Forest Map (using MODIS2005) provided a current assessment of forest cover within 20 natural forest types. This map was overlaid onto WWF realms and ecoregions to gain additional biogeographic information...... on forest distribution. Using the 2008 World Database on Protected Areas, percentage forest cover protection was calculated globally, within forest types, realms and ecoregions, and within selected areas of global conservation importance. At the 10% tree cover threshold, global forest cover was 39 million...... km2. Of this, 7.7% fell within protected areas under IUCN management categories I-IV. With the inclusion of IUCN categories V and VI, the level of global forest protection increased to 13.5%. Percentage forest protection (IUCN I-IV) varied greatly between realms from 5.5% (Palearctic) to 13...

  7. Automatic Mapping of Forest Stands Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning

    Directory of Open Access Journals (Sweden)

    Tim Ritter

    2017-07-01

    Full Text Available Mapping of exact tree positions can be regarded as a crucial task of field work associated with forest monitoring, especially on intensive research plots. We propose a two-stage density clustering approach for the automatic mapping of tree positions, and an algorithm for automatic tree diameter estimates based on terrestrial laser-scanning (TLS point cloud data sampled under limited sighting conditions. We show that our novel approach is able to detect tree positions in a mixed and vertically structured stand with an overall accuracy of 91.6%, and with omission- and commission error of only 5.7% and 2.7% respectively. Moreover, we were able to reproduce the stand’s diameter in breast height (DBH distribution, and to estimate single trees DBH with a mean average deviation of ±2.90 cm compared with tape measurements as reference.

  8. Mapping Canopy Damage from Understory Fires in Amazon Forests Using Annual Time Series of Landsat and MODIS Data

    Science.gov (United States)

    Morton, Douglas C.; DeFries, Ruth S.; Nagol, Jyoteshwar; Souza, Carlos M., Jr.; Kasischke, Eric S.; Hurtt, George C.; Dubayah, Ralph

    2011-01-01

    Understory fires in Amazon forests alter forest structure, species composition, and the likelihood of future disturbance. The annual extent of fire-damaged forest in Amazonia remains uncertain due to difficulties in separating burning from other types of forest damage in satellite data. We developed a new approach, the Burn Damage and Recovery (BDR) algorithm, to identify fire-related canopy damages using spatial and spectral information from multi-year time series of satellite data. The BDR approach identifies understory fires in intact and logged Amazon forests based on the reduction and recovery of live canopy cover in the years following fire damages and the size and shape of individual understory burn scars. The BDR algorithm was applied to time series of Landsat (1997-2004) and MODIS (2000-2005) data covering one Landsat scene (path/row 226/068) in southern Amazonia and the results were compared to field observations, image-derived burn scars, and independent data on selective logging and deforestation. Landsat resolution was essential for detection of burn scars less than 50 ha, yet these small burns contributed only 12% of all burned forest detected during 1997-2002. MODIS data were suitable for mapping medium (50-500 ha) and large (greater than 500 ha) burn scars that accounted for the majority of all fire-damaged forest in this study. Therefore, moderate resolution satellite data may be suitable to provide estimates of the extent of fire-damaged Amazon forest at a regional scale. In the study region, Landsat-based understory fire damages in 1999 (1508 square kilometers) were an order of magnitude higher than during the 1997-1998 El Nino event (124 square kilometers and 39 square kilometers, respectively), suggesting a different link between climate and understory fires than previously reported for other Amazon regions. The results in this study illustrate the potential to address critical questions concerning climate and fire risk in Amazon forests by

  9. The potential for LiDAR technology to map fire fuel hazard over large areas of Australian forest.

    Science.gov (United States)

    Price, Owen F; Gordon, Christopher E

    2016-10-01

    Fuel load is a primary determinant of fire spread in Australian forests. In east Australian forests, litter and canopy fuel loads and hence fire hazard are thought to be highest at and beyond steady-state fuel loads 15-20 years post-fire. Current methods used to predict fuel loads often rely on course-scale vegetation maps and simple time-since-fire relationships which mask fine-scale processes influencing fuel loads. Here we use Light Detecting and Remote Sensing technology (LiDAR) and field surveys to quantify post-fire mid-story and crown canopy fuel accumulation and fire hazard in Dry Sclerophyll Forests of the Sydney Basin (Australia) at fine spatial-scales (20 × 20 m cell resolution). Fuel cover was quantified in three strata important for crown fire propagation (0.5-4 m, 4-15 m, >15 m) over a 144 km(2) area subject to varying fire fuel ages. Our results show that 1) LiDAR provided a precise measurement of fuel cover in each strata and a less precise but still useful predictor of surface fuels, 2) cover varied greatly within a mapped vegetation class of the same fuel age, particularly for elevated fuel, 3) time-since-fire was a poor predictor of fuel cover and crown fire hazard because fuel loads important for crown fire propagation were variable over a range of fire fuel ages between 2 and 38 years post-fire, and 4) fuel loads and fire hazard can be high in the years immediately following fire. Our results show the benefits of spatially and temporally specific in situ fuel sampling methods such as LiDAR, and are widely applicable for fire management actions which aim to decrease human and environmental losses due to wildfire. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Regional forest and non-forest mapping using Envisat ASAR data

    NARCIS (Netherlands)

    Ling, F.; Li, Z.Y.; Chen, E.X.; Huang, Y.P.; Tian, X.; Schmullius, C.; Leiterer, R.; Reiche, J.; Maurizio, S.

    2012-01-01

    Envisat Advanced Synthetic Aperture Radar (ASAR) dual-polarization data are shown to be effective for regional forest monitoring. To this scope, an automatic SAR image preprocessing procedure was developed using SRTM DEM and Landsat TM image for geocoding in rugged terrain and smooth terrain areas,

  11. Uav-Based Photogrammetric Point Clouds and Hyperspectral Imaging for Mapping Biodiversity Indicators in Boreal Forests

    Science.gov (United States)

    Saarinen, N.; Vastaranta, M.; Näsi, R.; Rosnell, T.; Hakala, T.; Honkavaara, E.; Wulder, M. A.; Luoma, V.; Tommaselli, A. M. G.; Imai, N. N.; Ribeiro, E. A. W.; Guimarães, R. B.; Holopainen, M.; Hyyppä, J.

    2017-10-01

    Biodiversity is commonly referred to as species diversity but in forest ecosystems variability in structural and functional characteristics can also be treated as measures of biodiversity. Small unmanned aerial vehicles (UAVs) provide a means for characterizing forest ecosystem with high spatial resolution, permitting measuring physical characteristics of a forest ecosystem from a viewpoint of biodiversity. The objective of this study is to examine the applicability of photogrammetric point clouds and hyperspectral imaging acquired with a small UAV helicopter in mapping biodiversity indicators, such as structural complexity as well as the amount of deciduous and dead trees at plot level in southern boreal forests. Standard deviation of tree heights within a sample plot, used as a proxy for structural complexity, was the most accurately derived biodiversity indicator resulting in a mean error of 0.5 m, with a standard deviation of 0.9 m. The volume predictions for deciduous and dead trees were underestimated by 32.4 m3/ha and 1.7 m3/ha, respectively, with standard deviation of 50.2 m3/ha for deciduous and 3.2 m3/ha for dead trees. The spectral features describing brightness (i.e. higher reflectance values) were prevailing in feature selection but several wavelengths were represented. Thus, it can be concluded that structural complexity can be predicted reliably but at the same time can be expected to be underestimated with photogrammetric point clouds obtained with a small UAV. Additionally, plot-level volume of dead trees can be predicted with small mean error whereas identifying deciduous species was more challenging at plot level.

  12. Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping

    Directory of Open Access Journals (Sweden)

    Dimitris G. Stavrakoudis

    2014-07-01

    Full Text Available This study investigates the effectiveness of combining multispectral very high resolution (VHR and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM. The classification result from the hyperspectral image is then resampled to the multispectral’s spatial resolution and the two sources are combined using a simple yet efficient fusion operator. Thus, the complementary information provided from the two sources is effectively exploited, without having to resort to computationally demanding and time-consuming typical data fusion or vector stacking approaches. The effectiveness of the proposed methodology is validated in a complex Mediterranean forest landscape, comprising spectrally similar and spatially intermingled species. The decision fusion scheme resulted in an accuracy increase of 8% compared to the classification using only the multispectral imagery, whereas the increase was even higher compared to the classification using only the hyperspectral satellite image. Perhaps most importantly, its accuracy was significantly higher than alternative multisource fusion approaches, although the latter are characterized by much higher computation, storage, and time requirements.

  13. Generation of large-scale forest height and disturbance maps through the fusion of NISAR and GEDI along with TanDEM-X/L

    Science.gov (United States)

    Lei, Y.; Treuhaft, R. N.; Siqueira, P.; Torbick, N.; Lucas, R.; Keller, M. M.; Schmidt, M.; Ducey, M. J.; Salas, W.

    2017-12-01

    Large-scale products of forest height and disturbance are essential for understanding the global carbon distribution as well as its changes in response to natural events and human activities. Regarding this scientific need, both NASA's GEDI and NASA-ISRO's NISAR are going to be launched in the 2018-2021 timeframe in parallel with DLR's current TanDEM-X and/or the proposed TanDEM-L, which provides a lot of potential for global ecosystem mapping. A new simple and efficient method of forest height mapping has been developed for combining spaceborne repeat-pass InSAR and lidar missions (e.g. NISAR and GEDI) which estimates temporal decorrelation parameters of repeat-pass InSAR and uses the lidar data as training samples. An open-access Python-based software has been developed for automated processing. As a result, a mosaic of forest height was generated for US states of Maine and New Hampshire (11.6 million ha) using JAXA's ALOS-1 and ALOS-2 HV-pol InSAR data and a small piece of lidar training samples (44,000 ha) with the height estimates validated against airborne lidar and field inventory data over both flat and mountainous areas. In addition, through estimating and correcting for the temporal decorrelation effects in the spaceborne repeat-pass InSAR coherence data and also utilizing the spaceborne single-pass InSAR phase data, forest disturbance such as selective logging is not only detected but also quantified in subtropical forests of Australia using ALOS-1 HH-pol InSAR data (validated against NASA's Landsat), as well as in tropics of Brazil using TanDEM-X and ALOS-2 HH-pol InSAR data (validated against field inventory data). The operational simplicity and efficiency make these methods a potential observing/processing prototype for the fusion of NISAR, GEDI and TanDEM-X/L.

  14. Tropical Deforestation, Community Forests, and Protected Areas in the Maya Forest

    Directory of Open Access Journals (Sweden)

    David Barton. Bray

    2008-12-01

    Full Text Available Community forests and protected areas have each been proposed as strategies to stop deforestation. These management strategies should be regarded as hypotheses to be evaluated for their effectiveness in particular places. We evaluated the community-forestry hypothesis and the protected-area hypothesis in community forests with commercial timber production and strict protected areas in the Maya Forest of Guatemala and Mexico. From land-use and land cover change (LUCC maps derived from satellite images, we compared deforestation in 19 community forests and 11 protected areas in both countries in varying periods from 1988 to 2005. Deforestation rates were higher in protected areas than in community forests, but the differences were not significant. An analysis of human presence showed similar deforestation rates in inhabited protected areas and recently inhabited community forests, but the differences were not significant. There was also no significant difference in deforestation between uninhabited protected areas, uninhabited community forests, and long-inhabited community forests. A logistic regression analysis indicated that the factors correlated with deforestation varied by country. Distance to human settlements, seasonal wetlands, and degree and length of human residence were significant in Guatemala, and distance to previous deforestation and tropical semideciduous forest were significant in Mexico. Varying contexts and especially colonization histories are highlighted as likely factors that influence different outcomes. Poorly governed protected areas perform no better as a conservation strategy than poorly governed community forests with recent colonists in active colonization fronts. Long-inhabited extractive communities perform as well as uninhabited strict protected areas under low colonization pressure. A review of costs and benefits suggests that community forests may generate more local income with lower costs. Small sample sizes

  15. EXPERIENCE OF THE ADALIMUMAB APPLICATION FOR THE PATIENT WITH EARLY DEBUT OF JUVENILE IDIOPATHIC ARTHRITIS AND UVEITIS

    Directory of Open Access Journals (Sweden)

    K. B. Isaeva

    2014-01-01

    Full Text Available The case of early debut and heavy course of juvenile idiopathic arthritis in the patient at the age of 1 year and 8 months, associated with uveitis refractory to the therapy by methotrexate and nonsteroid antiinflammatory preparations is presented. The given clinical example shows high therapeutic efficiency of the adalimumab. To the 8th week of treatment inflammatory changes in conjunctiva were stopped, to the 12th week the stage of inactive illness was registered, i.e. the patient had no inflammatory changes in joints, uveitis activity signs, increase of laboratory indicators of illness activity. Duration of remission of articulate syndrome and uveitis made 9 months.

  16. A multicriteria framework for producing local, regional, and national insect and disease risk maps

    Science.gov (United States)

    Frank J. Jr. Krist; Frank J. Sapio

    2010-01-01

    The construction of the 2006 National Insect and Disease Risk Map, compiled by the USDA Forest Service, State and Private Forestry Area, Forest Health Protection Unit, resulted in the development of a GIS-based, multicriteria approach for insect and disease risk mapping that can account for regional variations in forest health concerns and threats. This risk mapping...

  17. Approximating prediction uncertainty for random forest regression models

    Science.gov (United States)

    John W. Coulston; Christine E. Blinn; Valerie A. Thomas; Randolph H. Wynne

    2016-01-01

    Machine learning approaches such as random forest have increased for the spatial modeling and mapping of continuous variables. Random forest is a non-parametric ensemble approach, and unlike traditional regression approaches there is no direct quantification of prediction error. Understanding prediction uncertainty is important when using model-based continuous maps as...

  18. New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis

    Science.gov (United States)

    L.R. Iverson; A.M. Prasad; A. Liaw

    2004-01-01

    More and better machine learning tools are becoming available for landscape ecologists to aid in understanding species-environment relationships and to map probable species occurrence now and potentially into the future. To thal end, we evaluated three statistical models: Regression Tree Analybib (RTA), Bagging Trees (BT) and Random Forest (RF) for their utility in...

  19. Racial differences in parenting dimensions and adolescent condom use at sexual debut.

    Science.gov (United States)

    Cox, Mary F

    2006-01-01

    Parenting style may be a determinant in reducing adolescent risk behavior. Previous studies have relied on a typological parenting approach, with classification into four groups: authoritative, authoritarian, permissive, and neglectful. In this study, two distinct parenting dimensions, demandingness and responsiveness, were examined as independent predictors of adolescent condom use. This study used a subsample of the National Longitudinal Study of Adolescent Health (Add Health) that included 153 adolescent-mother pairs. Maternal demandingness and responsiveness were measured using Wave I mother interviews. Logistic regression analyses were used to predict adolescent condom use at sexual debut at Wave II and to assess moderation by gender and race. (1) Maternal demandingness predicted increased likelihood of condom use in African American adolescents but decreased likelihood of condom use in White adolescents; (2) maternal responsiveness did not predict condom use; and (3) gender moderation was not present. To provide appropriate family counseling, public health nurses need to consider racial differences in contraceptive practices. Education regarding parental supervision practices should be considered as part of nursing interventions intended to increase condom use in African American adolescents.

  20. Factors associated with alcohol and/or drug use at sexual debut among sexually active university students: cross-sectional findings from Lebanon.

    Science.gov (United States)

    Ghandour, Lilian A; Mouhanna, Farah; Yasmine, Rola; El Kak, Faysal

    2014-07-01

    Sexual activity accompanied by substance use can impair youth decision-making and enhance risk-taking behaviors. Less is known, however, about the sexual values, perceptions and subsequent sexual practices of youth whose sexual debut occurs while using alcohol/drugs. A cross-sectional anonymous online survey was conducted in April-August 2012 among undergraduate and graduate university students (aged 18 to 30) attending the 4th largest private university in Beirut. Pearson's Chi-square and regression models were run using Stata/IC 10.0. 940 university students had engaged in oral, anal and/or vaginal sex, of whom 10% admitted to having had consumed alcohol or taken drugs at sexual debut, a behavior that was more common in the males, less religious, non-Arabs, students living alone or who had lived abroad. Students who used alcohol/drugs at sexual debut were twice as likely to have: their first oral and vaginal sex with an unfamiliar partner [odds ratio (OR) = 2.6, 95% confidence interval (CI): (1.6, 4.2) and OR = 2.1 (1.2, 3.5), respectively], controlling for sex, nationality, current relationship status, living abroad after the age of 12, and spirituality. Students who had sex the first time while using alcohol/drugs were three times as likely to report having had 11 or more subsequent sexual partners versus one or two [OR = 3.0 (1.5-6.0)]; and almost twice as likely to ever engage in something sexual they did not want to do [OR = 1.7 (1.1, 2.8)]. Perceived peer pressure to have sex by a certain age [OR = 1.8 (1.1, 2.9)], and perceived peer norms to consume alcohol/drugs before sex [OR = 4.8 (2.3, 9.9)] were also strong correlates of having sex for the first time while using alcohol and/or drugs. Findings stress the importance of sexuality education for youth, and the need to begin understanding the true interplay--beyond association--between youth sexual practices and substance use behaviors from a broader public health perspective.

  1. Mapping tropical dry forest habitats integrating Landsat NDVI, Ikonos imagery, and topographic information in the Caribbean Island of Mona

    Directory of Open Access Journals (Sweden)

    Sebastián Martinuzzi

    2008-06-01

    Full Text Available Assessing the status of tropical dry forest habitats using remote sensing technologies is one of the research priorities for Neotropical forests. We developed a simple method for mapping vegetation and habitats in a tropical dry forest reserve, Mona Island, Puerto Rico, by integrating the Normalized Difference vegetation Index (NDvI from Landsat, topographic information, and high-resolution Ikonos imagery. The method was practical for identifying vegetation types in areas with a great variety of plant communities and complex relief, and can be adapted to other dry forest habitats of the Caribbean Islands. NDvI was useful for identifying the distribution of forests, woodlands, and shrubland, providing a natural representation of the vegetation patterns on the island. The use of Ikonos imagery allowed increasing the number of land cover classes. As a result, sixteen land-cover types were mapped over the 5 500 ha area, with a kappa coefficient of accuracy equal to 79 %. This map is a central piece for modeling vertebrate species distribution and biodiversity patterns by the Puerto Rico Gap Analysis Project, and it is of great value for assisting research and management actions in the island. Rev. Biol. Trop. 56 (2: 625-639. Epub 2008 June 30.El estudio y evaluación de los bosques tropicales secos mediante herramientas de teledetección es una de las prioridades de investigación en los ambientes neotropicales. Desarrollamos una metodología simple para mapear la vegetación de la isla de Mona, Puerto Rico, mediante el uso del índice de vegetación normalizado (NDVI por sus siglas en inglés de Landsat, información topográfica, e imágenes auxiliares de alta resolución Ikonos. La metodología fue útil para identificar las clases de vegetación en un área de gran variedad de comunidades vegetales y relieve complejo, y puede ser adaptada a otras regiones de bosque seco de las islas del Caribe. El NDVI permitió identificar la distribución de

  2. Land cover mapping, fire regeneration, and scaling studies in the Canadian boreal forest with 1 km AVHRR and Landsat TM data

    Science.gov (United States)

    Steyaert, L.T.; Hall, F.G.; Loveland, Thomas R.

    1997-01-01

    A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km ?? 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within

  3. UAV-Borne Profiling Radar for Forest Research

    Directory of Open Access Journals (Sweden)

    Yuwei Chen

    2017-01-01

    Full Text Available Microwave Radar is an attractive solution for forest mapping and inventories because microwave signals penetrates into the forest canopy and the backscattering signal can provide information regarding the whole forest structure. Satellite-borne and airborne imaging radars have been used in forest resources mapping for many decades. However, their accuracy with respect to the main forest inventory attributes substantially varies depending on the wavelength and techniques used in the estimation. Systems providing canopy backscatter as a function of canopy height are, practically speaking, missing. Therefore, there is a need for a radar system that would enable the scientific community to better understand the radar backscatter response from the forest canopy. Consequently, we undertook a research study to develop an unmanned aerial vehicle (UAV-borne profiling (i.e., waveform radar that could be used to improve the understanding of the radar backscatter response for forestry mapping and inventories. A frequency modulation continuous waveform (FMCW profiling radar, termed FGI-Tomoradar, was introduced, designed and tested. One goal is the total weight of the whole system is less than 7 kg, including the radar system and georeferencing system, with centimetre-level positioning accuracy. Achieving this weight goal would enable the FGI-Tomoradar system to be installed on the Mini-UAV platform. The prototype system had all four linear polarization measuring capabilities, with bistatic configuration in Ku-band. In system performance tests in this study, FGI-Tomoradar was mounted on a manned helicopter together with a Riegl VQ-480-U laser scanner and tested in several flight campaigns performed at the Evo site, Finland. Airborne laser scanning data was simultaneously collected to investigate the differences and similarities of the outputs for the same target area for better understanding the penetration of the microwave signal into the forest canopy

  4. Biomass resilience of Neotropical secondary forests.

    Science.gov (United States)

    Poorter, Lourens; Bongers, Frans; Aide, T Mitchell; Almeyda Zambrano, Angélica M; Balvanera, Patricia; Becknell, Justin M; Boukili, Vanessa; Brancalion, Pedro H S; Broadbent, Eben N; Chazdon, Robin L; Craven, Dylan; de Almeida-Cortez, Jarcilene S; Cabral, George A L; de Jong, Ben H J; Denslow, Julie S; Dent, Daisy H; DeWalt, Saara J; Dupuy, Juan M; Durán, Sandra M; Espírito-Santo, Mario M; Fandino, María C; César, Ricardo G; Hall, Jefferson S; Hernandez-Stefanoni, José Luis; Jakovac, Catarina C; Junqueira, André B; Kennard, Deborah; Letcher, Susan G; Licona, Juan-Carlos; Lohbeck, Madelon; Marín-Spiotta, Erika; Martínez-Ramos, Miguel; Massoca, Paulo; Meave, Jorge A; Mesquita, Rita; Mora, Francisco; Muñoz, Rodrigo; Muscarella, Robert; Nunes, Yule R F; Ochoa-Gaona, Susana; de Oliveira, Alexandre A; Orihuela-Belmonte, Edith; Peña-Claros, Marielos; Pérez-García, Eduardo A; Piotto, Daniel; Powers, Jennifer S; Rodríguez-Velázquez, Jorge; Romero-Pérez, I Eunice; Ruíz, Jorge; Saldarriaga, Juan G; Sanchez-Azofeifa, Arturo; Schwartz, Naomi B; Steininger, Marc K; Swenson, Nathan G; Toledo, Marisol; Uriarte, Maria; van Breugel, Michiel; van der Wal, Hans; Veloso, Maria D M; Vester, Hans F M; Vicentini, Alberto; Vieira, Ima C G; Bentos, Tony Vizcarra; Williamson, G Bruce; Rozendaal, Danaë M A

    2016-02-11

    Land-use change occurs nowhere more rapidly than in the tropics, where the imbalance between deforestation and forest regrowth has large consequences for the global carbon cycle. However, considerable uncertainty remains about the rate of biomass recovery in secondary forests, and how these rates are influenced by climate, landscape, and prior land use. Here we analyse aboveground biomass recovery during secondary succession in 45 forest sites and about 1,500 forest plots covering the major environmental gradients in the Neotropics. The studied secondary forests are highly productive and resilient. Aboveground biomass recovery after 20 years was on average 122 megagrams per hectare (Mg ha(-1)), corresponding to a net carbon uptake of 3.05 Mg C ha(-1) yr(-1), 11 times the uptake rate of old-growth forests. Aboveground biomass stocks took a median time of 66 years to recover to 90% of old-growth values. Aboveground biomass recovery after 20 years varied 11.3-fold (from 20 to 225 Mg ha(-1)) across sites, and this recovery increased with water availability (higher local rainfall and lower climatic water deficit). We present a biomass recovery map of Latin America, which illustrates geographical and climatic variation in carbon sequestration potential during forest regrowth. The map will support policies to minimize forest loss in areas where biomass resilience is naturally low (such as seasonally dry forest regions) and promote forest regeneration and restoration in humid tropical lowland areas with high biomass resilience.

  5. Accuracy assessment of the National Forest Inventory map of Mexico: sampling designs and the fuzzy characterization of landscapes

    Directory of Open Access Journals (Sweden)

    Stéphane Couturier

    2009-10-01

    Full Text Available There is no record so far in the literature of a comprehensive method to assess the accuracy of regional scale Land Cover/ Land Use (LCLU maps in the sub-tropical belt. The elevated biodiversity and the presence of highly fragmented classes hamper the use of sampling designs commonly employed in previous assessments of mainly temperate zones. A sampling design for assessing the accuracy of the Mexican National Forest Inventory (NFI map at community level is presented. A pilot study was conducted on the Cuitzeo Lake watershed region covering 400 000 ha of the 2000 Landsat-derived map. Various sampling designs were tested in order to find a trade-off between operational costs, a good spatial distribution of the sample and the inclusion of all scarcely distributed classes (‘rare classes’. A two-stage sampling design where the selection of Primary Sampling Units (PSU was done under separate schemes for commonly and scarcely distributed classes, showed best characteristics. A total of 2 023 punctual secondary sampling units were verified against their NFI map label. Issues regarding the assessment strategy and trends of class confusions are devised.

  6. Real time forest fire warning and forest fire risk zoning: a Vietnamese case study

    Science.gov (United States)

    Chu, T.; Pham, D.; Phung, T.; Ha, A.; Paschke, M.

    2016-12-01

    Forest fire occurs seriously in Vietnam and has been considered as one of the major causes of forest lost and degradation. Several studies of forest fire risk warning were conducted using Modified Nesterov Index (MNI) but remaining shortcomings and inaccurate predictions that needs to be urgently improved. In our study, several important topographic and social factors such as aspect, slope, elevation, distance to residential areas and road system were considered as "permanent" factors while meteorological data were updated hourly using near-real-time (NRT) remotely sensed data (i.e. MODIS Terra/Aqua and TRMM) for the prediction and warning of fire. Due to the limited number of weather stations in Vietnam, data from all active stations (i.e. 178) were used with the satellite data to calibrate and upscale meteorological variables. These data with finer resolution were then used to generate MNI. The only significant "permanent" factors were selected as input variables based on the correlation coefficients that computed from multi-variable regression among true fire-burning (collected from 1/2007) and its spatial characteristics. These coefficients also used to suggest appropriate weight for computing forest fire risk (FR) model. Forest fire risk model was calculated from the MNI and the selected factors using fuzzy regression models (FRMs) and GIS based multi-criteria analysis. By this approach, the FR was slightly modified from MNI by the integrated use of various factors in our fire warning and prediction model. Multifactor-based maps of forest fire risk zone were generated from classifying FR into three potential danger levels. Fire risk maps were displayed using webgis technology that is easy for managing data and extracting reports. Reported fire-burnings thereafter have been used as true values for validating the forest fire risk. Fire probability has strong relationship with potential danger levels (varied from 5.3% to 53.8%) indicating that the higher

  7. ForWarn: A Cross-Cutting Forest Resource Management and Decision Support System Providing the Capacity to Identify and Track Forest Disturbances Nationally

    Science.gov (United States)

    Hargrove, W. W.; Spruce, J.; Norman, S.; Christie, W.; Hoffman, F. M.

    2012-12-01

    The Eastern Forest Environmental Threat Assessment Center and Western Wildland Environmental Assessment Center of the USDA Forest Service have collaborated with NASA Stennis Space Center to develop ForWarn, a forest monitoring tool that uses MODIS satellite imagery to produce weekly snapshots of vegetation conditions across the lower 48 United States. Forest and natural resource managers can use ForWarn to rapidly detect, identify, and respond to unexpected changes in the nation's forests caused by insects, diseases, wildfires, severe weather, or other natural or human-caused events. ForWarn detects most types of forest disturbances, including insects, disease, wildfires, frost and ice damage, tornadoes, hurricanes, blowdowns, harvest, urbanization, and landslides. It also detects drought, flood, and temperature effects, and shows early and delayed seasonal vegetation development. Operating continuously since January 2010, results show ForWarn to be a robust and highly capable tool for detecting changes in forest conditions. ForWarn is the first national-scale system of its kind based on remote sensing developed specifically for forest disturbances. It has operated as a prototype since January 2010 and has provided useful information about the location and extent of disturbances detected during the 2011 growing season, including tornadoes, wildfires, and extreme drought. The ForWarn system had an official unveiling and rollout in March 2012, initiated by a joint NASA and USDA press release. The ForWarn home page has had 2,632 unique visitors since rollout in March 2012, with 39% returning visits. ForWarn was used to map tornado scars from the historic April 27, 2011 tornado outbreak, and detected timber damage within more than a dozen tornado tracks across northern Mississippi, Alabama, and Georgia. ForWarn is the result of an ongoing, substantive cooperation among four different government agencies: USDA, NASA, USGS, and DOE. Disturbance maps are available on the

  8. National satellite-based humid tropical forest change assessment in Peru in support of REDD+ implementation

    Science.gov (United States)

    Potapov, P. V.; Dempewolf, J.; Talero, Y.; Hansen, M. C.; Stehman, S. V.; Vargas, C.; Rojas, E. J.; Castillo, D.; Mendoza, E.; Calderón, A.; Giudice, R.; Malaga, N.; Zutta, B. R.

    2014-12-01

    Transparent, consistent, and accurate national forest monitoring is required for successful implementation of reducing emissions from deforestation and forest degradation (REDD+) programs. Collecting baseline information on forest extent and rates of forest loss is a first step for national forest monitoring in support of REDD+. Peru, with the second largest extent of Amazon basin rainforest, has made significant progress in advancing its forest monitoring capabilities. We present a national-scale humid tropical forest cover loss map derived by the Ministry of Environment REDD+ team in Peru. The map quantifies forest loss from 2000 to 2011 within the Peruvian portion of the Amazon basin using a rapid, semi-automated approach. The available archive of Landsat imagery (11 654 scenes) was processed and employed for change detection to obtain annual gross forest cover loss maps. A stratified sampling design and a combination of Landsat (30 m) and RapidEye (5 m) imagery as reference data were used to estimate the primary forest cover area, total gross forest cover loss area, proportion of primary forest clearing, and to validate the Landsat-based map. Sample-based estimates showed that 92.63% (SE = 2.16%) of the humid tropical forest biome area within the country was covered by primary forest in the year 2000. Total gross forest cover loss from 2000 to 2011 equaled 2.44% (SE = 0.16%) of the humid tropical forest biome area. Forest loss comprised 1.32% (SE = 0.37%) of primary forest area and 9.08% (SE = 4.04%) of secondary forest area. Validation confirmed a high accuracy of the Landsat-based forest cover loss map, with a producer’s accuracy of 75.4% and user’s accuracy of 92.2%. The majority of forest loss was due to clearing (92%) with the rest attributed to natural processes (flooding, fires, and windstorms). The implemented Landsat data processing and classification system may be used for operational annual forest cover loss updates at the national level for REDD

  9. National satellite-based humid tropical forest change assessment in Peru in support of REDD+ implementation

    International Nuclear Information System (INIS)

    Potapov, P V; Dempewolf, J; Talero, Y; Hansen, M C; Stehman, S V; Vargas, C; Rojas, E J; Calderón, A; Giudice, R; Malaga, N; Zutta, B R; Castillo, D; Mendoza, E

    2014-01-01

    Transparent, consistent, and accurate national forest monitoring is required for successful implementation of reducing emissions from deforestation and forest degradation (REDD+) programs. Collecting baseline information on forest extent and rates of forest loss is a first step for national forest monitoring in support of REDD+. Peru, with the second largest extent of Amazon basin rainforest, has made significant progress in advancing its forest monitoring capabilities. We present a national-scale humid tropical forest cover loss map derived by the Ministry of Environment REDD+ team in Peru. The map quantifies forest loss from 2000 to 2011 within the Peruvian portion of the Amazon basin using a rapid, semi-automated approach. The available archive of Landsat imagery (11 654 scenes) was processed and employed for change detection to obtain annual gross forest cover loss maps. A stratified sampling design and a combination of Landsat (30 m) and RapidEye (5 m) imagery as reference data were used to estimate the primary forest cover area, total gross forest cover loss area, proportion of primary forest clearing, and to validate the Landsat-based map. Sample-based estimates showed that 92.63% (SE = 2.16%) of the humid tropical forest biome area within the country was covered by primary forest in the year 2000. Total gross forest cover loss from 2000 to 2011 equaled 2.44% (SE = 0.16%) of the humid tropical forest biome area. Forest loss comprised 1.32% (SE = 0.37%) of primary forest area and 9.08% (SE = 4.04%) of secondary forest area. Validation confirmed a high accuracy of the Landsat-based forest cover loss map, with a producer’s accuracy of 75.4% and user’s accuracy of 92.2%. The majority of forest loss was due to clearing (92%) with the rest attributed to natural processes (flooding, fires, and windstorms). The implemented Landsat data processing and classification system may be used for operational annual forest cover loss updates at the national level

  10. Annual Dynamics of Forest Areas in South America during 2007-2010 at 50-m Spatial Resolution

    Science.gov (United States)

    Qin, Y.; Xiao, X.; Dong, J.; Zhou, Y.; Wang, J.; Doughty, R.; Chen, Y.; Zou, Z.; Moore, B., III

    2017-12-01

    The user community has an urgent need for high accuracy tropical forest distribution and spatio-temporal changes since tropical forests are facing defragmentation and persistent clouds. In this study, we selected South America as a hotspot and presented a robust approach to map annual forests during 2007-2010 based on the coupled greenness-relevant MOD13Q1 NDVI and structure/biomass-relevant ALOS PALSAR time series data. We analyzed the consistency and uncertainty among eight major forest maps at continental, country, and pixel scales. The 50-m PALSAR/MODIS forest area in South America was about 8.63×106 km2 in 2010. Large differences in total forest area (8.2×106 km2-12.7×106 km2) existed among these forest products. Forest products generated under a similar forest definition had similar or even larger variation than those generated under differing forest definitions. One needs to consider leaf area index as an adjusting factor and use much higher threshold values in the VCF datasets to estimate forest cover. Analyses of PALSAR/MODIS forest maps showed a relatively small and equivalent rate of loss (3.2×104 km2 year-1) in net forest cover to that of FAO FRA (3.3×104 km2 year-1). PALSAR/MODIS forest maps showed that more and more deforestation occurred in the intact forest areas. The rate of forest loss (1.95×105 km2 year-1) was higher than that of Global Forest Watch (0.81×105 km2 year-1). Caution should be used when using the different forest maps to analyze forest loss and make policies regarding forest ecosystem services and biodiversity conservation.

  11. A global map of mangrove forest soil carbon at 30 m spatial resolution

    Science.gov (United States)

    Sanderman, Jonathan; Hengl, Tomislav; Fiske, Greg; Solvik, Kylen; Adame, Maria Fernanda; Benson, Lisa; Bukoski, Jacob J.; Carnell, Paul; Cifuentes-Jara, Miguel; Donato, Daniel; Duncan, Clare; Eid, Ebrahem M.; Ermgassen, Philine zu; Ewers Lewis, Carolyn J.; Macreadie, Peter I.; Glass, Leah; Gress, Selena; Jardine, Sunny L.; Jones, Trevor G.; Ndemem Nsombo, Eugéne; Mizanur Rahman, Md; Sanders, Christian J.; Spalding, Mark; Landis, Emily

    2018-05-01

    With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30 m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250 m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kg m‑3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha‑1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.

  12. Japanese national forest inventory and its spatial extension by remote sensing

    Science.gov (United States)

    Yasumasa Hirata; Mitsuo Matsumoto; Toshiro Iehara

    2009-01-01

    Japan has two independent forest inventory systems. One forest inventory is required by the forest planning system based on the Forest Law, in which forest registers and forest planning maps are prepared. The other system is a forest resource monitoring survey, in which systematic sampling is done at 4-km grid intervals. Here, we present these national forest inventory...

  13. The Greek National Observatory of Forest Fires (NOFFi)

    Science.gov (United States)

    Tompoulidou, Maria; Stefanidou, Alexandra; Grigoriadis, Dionysios; Dragozi, Eleni; Stavrakoudis, Dimitris; Gitas, Ioannis Z.

    2016-08-01

    Efficient forest fire management is a key element for alleviating the catastrophic impacts of wildfires. Overall, the effective response to fire events necessitates adequate planning and preparedness before the start of the fire season, as well as quantifying the environmental impacts in case of wildfires. Moreover, the estimation of fire danger provides crucial information required for the optimal allocation and distribution of the available resources. The Greek National Observatory of Forest Fires (NOFFi)—established by the Greek Forestry Service in collaboration with the Laboratory of Forest Management and Remote Sensing of the Aristotle University of Thessaloniki and the International Balkan Center—aims to develop a series of modern products and services for supporting the efficient forest fire prevention management in Greece and the Balkan region, as well as to stimulate the development of transnational fire prevention and impacts mitigation policies. More specifically, NOFFi provides three main fire-related products and services: a) a remote sensing-based fuel type mapping methodology, b) a semi-automatic burned area mapping service, and c) a dynamically updatable fire danger index providing mid- to long-term predictions. The fuel type mapping methodology was developed and applied across the country, following an object-oriented approach and using Landsat 8 OLI satellite imagery. The results showcase the effectiveness of the generated methodology in obtaining highly accurate fuel type maps on a national level. The burned area mapping methodology was developed as a semi-automatic object-based classification process, carefully crafted to minimize user interaction and, hence, be easily applicable on a near real-time operational level as well as for mapping historical events. NOFFi's products can be visualized through the interactive Fire Forest portal, which allows the involvement and awareness of the relevant stakeholders via the Public Participation GIS

  14. Spatial distribution of carbon sources and sinks in Canada's forests

    International Nuclear Information System (INIS)

    Chen, Jing M.; Weimin, Ju; Liu, Jane; Cihlar, Josef; Chen, Wenjun

    2003-01-01

    Annual spatial distributions of carbon sources and sinks in Canada's forests at 1 km resolution are computed for the period from 1901 to 1998 using ecosystem models that integrate remote sensing images, gridded climate, soils and forest inventory data. GIS-based fire scar maps for most regions of Canada are used to develop a remote sensing algorithm for mapping and dating forest burned areas in the 25 yr prior to 1998. These mapped and dated burned areas are used in combination with inventory data to produce a complete image of forest stand age in 1998. Empirical NPP age relationships were used to simulate the annual variations of forest growth and carbon balance in 1 km pixels, each treated as a homogeneous forest stand. Annual CO 2 flux data from four sites were used for model validation. Averaged over the period 1990-1998, the carbon source and sink map for Canada's forests show the following features: (i) large spatial variations corresponding to the patchiness of recent fire scars and productive forests and (ii) a general south-to-north gradient of decreasing carbon sink strength and increasing source strength. This gradient results mostly from differential effects of temperature increase on growing season length, nutrient mineralization and heterotrophic respiration at different latitudes as well as from uneven nitrogen deposition. The results from the present study are compared with those of two previous studies. The comparison suggests that the overall positive effects of non-disturbance factors (climate, CO 2 and nitrogen) outweighed the effects of increased disturbances in the last two decades, making Canada's forests a carbon sink in the 1980s and 1990s. Comparisons of the modeled results with tower-based eddy covariance measurements of net ecosystem exchange at four forest stands indicate that the sink values from the present study may be underestimated

  15. Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale

    Directory of Open Access Journals (Sweden)

    Anne Clasen

    2015-11-01

    Full Text Available Forest biochemical and biophysical variables and their spatial and temporal distribution are essential inputs to process-orientated ecosystem models. To provide this information, imaging spectroscopy appears to be a promising tool. In this context, the present study investigates the potential of spectral unmixing to derive sub-pixel crown component fractions in a temperate deciduous forest ecosystem. However, the high proportion of foliage in this complex vegetation structure leads to the problem of saturation effects, when applying broadband vegetation indices. This study illustrates that multiple endmember spectral mixture analysis (MESMA can contribute to overcoming this challenge. Reference fractional abundances, as well as spectral measurements of the canopy components, could be precisely determined from a crane measurement platform situated in a deciduous forest in North-East Germany. In contrast to most other studies, which only use leaf and soil endmembers, this experimental setup allowed for the inclusion of a bark endmember for the unmixing of components within the canopy. This study demonstrates that the inclusion of additional endmembers markedly improves the accuracy. A mean absolute error of 7.9% could be achieved for the fractional occurrence of the leaf endmember and 5.9% for the bark endmember. In order to evaluate the results of this field-based study for airborne and satellite-based remote sensing applications, a transfer to Airborne Imaging Spectrometer for Applications (AISA and simulated Environmental Mapping and Analysis Program (EnMAP and Sentinel-2 imagery was carried out. All sensors were capable of unmixing crown components with a mean absolute error ranging between 3% and 21%.

  16. Accuracy Assessment of Satellite Derived Forest Cover Products in South and Southeast Asia

    Science.gov (United States)

    Gilani, H.; Xu, X.; Jain, A. K.

    2017-12-01

    South and Southeast Asia (SSEA) region occupies 16 % of worlds land area. It is home to over 50% of the world's population. The SSEA's countries are experiencing significant land-use and land-cover changes (LULCCs), primarily in agriculture, forest, and urban land. For this study, we compiled four existing global forest cover maps for year 2010 by Gong et al.(2015), Hansen et al. (2013), Sexton et al.(2013) and Shimada et al. (2014), which were all medium resolution (≤30 m) products based on Landsat and/or PALSAR satellite images. To evaluate the accuracy of these forest products, we used three types of information: (1) ground measurements, (2) high resolution satellite images and (3) forest cover maps produced at the national scale. The stratified random sampling technique was used to select a set of validation data points from the ground and high-resolution satellite images. Then the confusion matrix method was used to assess and rank the accuracy of the forest cover products for the entire SSEA region. We analyzed the spatial consistency of different forest cover maps, and further evaluated the consistency with terrain characteristics. Our study suggests that global forest cover mapping algorithms are trained and tested using limited ground measurement data. We found significant uncertainties in mountainous areas due to the topographical shadow effect and the dense tree canopies effects. The findings of this study will facilitate to improve our understanding of the forest cover dynamics and their impacts on the quantities and pathways of terrestrial carbon and nitrogen fluxes. Gong, P., et al. (2012). "Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data." International Journal of Remote Sensing 34(7): 2607-2654. Hansen, M. C., et al. (2013). "High-Resolution Global Maps of 21st-Century Forest Cover Change." Science 342(6160): 850-853. Sexton, J. O., et al. (2013). "Global, 30-m resolution

  17. USGS Transportation Overlay Map Service from The National Map

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The USGS Transportation service from The National Map (TNM) is based on TIGER/Line data provided through U.S. Census Bureau and road data from U.S. Forest Service....

  18. Mapping forest transition trends in Okomu reserve using Landsat ...

    African Journals Online (AJOL)

    DR. ALEX O. ONOJEGHUO

    1 Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, United ... and improve upon the technical capacity of forest managers to improve forest management. Overall, the .... cloud cover or were totally free of such and acquired within the same season (as was the case in this ... Green (2), red (3) and.

  19. Analysis of tsunami disaster map by Geographic Information System (GIS): Aceh Singkil-Indonesia

    Science.gov (United States)

    Farhan, A.; Akhyar, H.

    2017-02-01

    Tsunami risk map is used by stakeholder as a base to decide evacuation plan and evaluates from disaster. Aceh Singkil district of Aceh- Indonesia’s disaster maps have been developed and analyzed by using GIS tool. Overlay methods through algorithms are used to produce hazard map, vulnerability, capacity and finally created disaster risk map. Spatial maps are used topographic maps, administrative map, SRTM. The parameters are social, economic, physical environmental vulnerability, a level of exposed people, parameters of houses, public building, critical facilities, productive land, population density, sex ratio, poor ratio, disability ratio, age group ratio, the protected forest, natural forest, and mangrove forest. The results show high-risk tsunami disaster at nine villages; moderate levels are seventeen villages, and other villages are shown in the low level of tsunami risk disaster.

  20. Predicting temperate forest stand types using only structural profiles from discrete return airborne lidar

    Science.gov (United States)

    Fedrigo, Melissa; Newnham, Glenn J.; Coops, Nicholas C.; Culvenor, Darius S.; Bolton, Douglas K.; Nitschke, Craig R.

    2018-02-01

    Light detection and ranging (lidar) data have been increasingly used for forest classification due to its ability to penetrate the forest canopy and provide detail about the structure of the lower strata. In this study we demonstrate forest classification approaches using airborne lidar data as inputs to random forest and linear unmixing classification algorithms. Our results demonstrated that both random forest and linear unmixing models identified a distribution of rainforest and eucalypt stands that was comparable to existing ecological vegetation class (EVC) maps based primarily on manual interpretation of high resolution aerial imagery. Rainforest stands were also identified in the region that have not previously been identified in the EVC maps. The transition between stand types was better characterised by the random forest modelling approach. In contrast, the linear unmixing model placed greater emphasis on field plots selected as endmembers which may not have captured the variability in stand structure within a single stand type. The random forest model had the highest overall accuracy (84%) and Cohen's kappa coefficient (0.62). However, the classification accuracy was only marginally better than linear unmixing. The random forest model was applied to a region in the Central Highlands of south-eastern Australia to produce maps of stand type probability, including areas of transition (the 'ecotone') between rainforest and eucalypt forest. The resulting map provided a detailed delineation of forest classes, which specifically recognised the coalescing of stand types at the landscape scale. This represents a key step towards mapping the structural and spatial complexity of these ecosystems, which is important for both their management and conservation.

  1. Changes of forest cover and disturbance regimes in the mountain forests of the Alps☆

    Science.gov (United States)

    Bebi, P.; Seidl, R.; Motta, R.; Fuhr, M.; Firm, D.; Krumm, F.; Conedera, M.; Ginzler, C.; Wohlgemuth, T.; Kulakowski, D.

    2017-01-01

    Natural disturbances, such as avalanches, snow breakage, insect outbreaks, windthrow or fires shape mountain forests globally. However, in many regions over the past centuries human activities have strongly influenced forest dynamics, especially following natural disturbances, thus limiting our understanding of natural ecological processes, particularly in densely-settled regions. In this contribution we briefly review the current understanding of changes in forest cover, forest structure, and disturbance regimes in the mountain forests across the European Alps over the past millennia. We also quantify changes in forest cover across the entire Alps based on inventory data over the past century. Finally, using the Swiss Alps as an example, we analyze in-depth changes in forest cover and forest structure and their effect on patterns of fire and wind disturbances, based on digital historic maps from 1880, modern forest cover maps, inventory data on current forest structure, topographical data, and spatially explicit data on disturbances. This multifaceted approach presents a long-term and detailed picture of the dynamics of mountain forest ecosystems in the Alps. During pre-industrial times, natural disturbances were reduced by fire suppression and land-use, which included extraction of large amounts of biomass that decreased total forest cover. More recently, forest cover has increased again across the entire Alps (on average +4% per decade over the past 25–115 years). Live tree volume (+10% per decade) and dead tree volume (mean +59% per decade) have increased over the last 15–40 years in all regions for which data were available. In the Swiss Alps secondary forests that established after 1880 constitute approximately 43% of the forest cover. Compared to forests established previously, post-1880 forests are situated primarily on steep slopes (>30°), have lower biomass, a more aggregated forest structure (primarily stem-exclusion stage), and have been more

  2. Representing human-mediated pathways in forest pest risk mapping

    Science.gov (United States)

    Frank H. Koch; William D. Smith

    2010-01-01

    Historically, U.S. forests have been invaded by a variety of nonindigenous insects and pathogens. Some of these pests have catastrophically impacted important species over a relatively short timeframe. To curtail future changes of this magnitude, agencies such as the U.S. Department of Agriculture Forest Service have devoted substantial resources to assessing the risks...

  3. Quantitative retrieving forest ecological parameters based on remote sensing in Liping County of China

    Science.gov (United States)

    Tian, Qingjiu; Chen, Jing M.; Zheng, Guang; Xia, Xueqi; Chen, Junying

    2006-09-01

    Forest ecosystem is an important component of terrestrial ecosystem and plays an important role in global changes. Aboveground biomass (AGB) of forest ecosystem is an important factor in global carbon cycle studies. The purpose of this study was to retrieve the yearly Net Primary Productivity (NPP) of forest from the 8-days-interval MODIS-LAI images of a year and produce a yearly NPP distribution map. The LAI, DBH (diameter at breast height), tree height, and tree age field were measured in different 80 plots for Chinese fir, Masson pine, bamboo, broadleaf, mix forest in Liping County. Based on the DEM image and Landsat TM images acquired on May 14th, 2000, the geometric correction and terrain correction were taken. In addition, the "6S"model was used to gain the surface reflectance image. Then the correlation between Leaf Area Index (LAI) and Reduced Simple Ratio (RSR) was built. Combined with the Landcover map, forest stand map, the LAI, aboveground biomass, tree age map were produced respectively. After that, the 8-days- interval LAI images of a year, meteorology data, soil data, forest stand image and Landcover image were inputted into the BEPS model to get the NPP spatial distribution. At last, the yearly NPP spatial distribution map with 30m spatial resolution was produced. The values in those forest ecological parameters distribution maps were quite consistent with those of field measurements. So it's possible, feasible and time-saving to estimate forest ecological parameters at a large scale by using remote sensing.

  4. Entering the lesbian world in Japan: debut stories.

    Science.gov (United States)

    Kamano, Saori

    2005-01-01

    Conceiving of a "lesbian community" as the process and/or the end product of a lesbian's going outside herself or her intimate relationship to connect with other lesbians, this paper explores the experiences of lesbians in entering the community in Tokyo, Japan, which lesbians refer to as "community debut." Based on the personal accounts gathered through interviewing 24 women in 2002 in the Tokyo area, this paper examines the personal contexts in which the women entered a lesbian community, which included searching for and defining themselves, accepting themselves, and acting out the new identity to make changes in their lives. Some of the women interviewed were prompted by a need to understand themselves as lesbians. Others with a lesbian identity searched for further affirmation through connecting with "the world of lesbians" beyond their immediate contexts. For some other women interviewed, entering the community was a way to help them start their lives anew by getting out of their previous (married) lives. The paper also specifically touches on the significance of the Internet as a source of information for individual women and as a way of creating a lesbian community, identifying both positive and negative aspects. Although the research reported in this paper leaves for further exploration how boundaries of the communities are negotiated and drawn, the norms of the communities, and conflicts and negotiations among individuals and groups, it has provided one piece of the mosaic of lesbian communities in Japan. The communities, while still largely invisible in the mainstream society, are nonetheless an important part of life, albeit in different ways, of many lesbians. The research process leads the author to anticipate greater visibility of lesbians and lesbian communities in Japan in the not too distant future.

  5. Tree species mapping in tropical forests using multi-temporal imaging spectroscopy: Wavelength adaptive spectral mixture analysis

    Science.gov (United States)

    Somers, B.; Asner, G. P.

    2014-09-01

    The use of imaging spectroscopy for florisic mapping of forests is complicated by the spectral similarity among co-existing species. Here we evaluated an alternative spectral unmixing strategy combining a time series of EO-1 Hyperion images and an automated feature selection in Multiple Endmember Spectral Mixture Analysis (MESMA). The temporal analysis provided a way to incorporate species phenology while feature selection indicated the best phenological time and best spectral feature set to optimize the separability between tree species. Instead of using the same set of spectral bands throughout the image which is the standard approach in MESMA, our modified Wavelength Adaptive Spectral Mixture Analysis (WASMA) approach allowed the spectral subsets to vary on a per pixel basis. As such we were able to optimize the spectral separability between the tree species present in each pixel. The potential of the new approach for floristic mapping of tree species in Hawaiian rainforests was quantitatively assessed using both simulated and actual hyperspectral image time-series. With a Cohen's Kappa coefficient of 0.65, WASMA provided a more accurate tree species map compared to conventional MESMA (Kappa = 0.54; p-value < 0.05. The flexible or adaptive use of band sets in WASMA provides an interesting avenue to address spectral similarities in complex vegetation canopies.

  6. High-resolution forest carbon stocks and emissions in the Amazon.

    Science.gov (United States)

    Asner, Gregory P; Powell, George V N; Mascaro, Joseph; Knapp, David E; Clark, John K; Jacobson, James; Kennedy-Bowdoin, Ty; Balaji, Aravindh; Paez-Acosta, Guayana; Victoria, Eloy; Secada, Laura; Valqui, Michael; Hughes, R Flint

    2010-09-21

    Efforts to mitigate climate change through the Reduced Emissions from Deforestation and Degradation (REDD) depend on mapping and monitoring of tropical forest carbon stocks and emissions over large geographic areas. With a new integrated use of satellite imaging, airborne light detection and ranging, and field plots, we mapped aboveground carbon stocks and emissions at 0.1-ha resolution over 4.3 million ha of the Peruvian Amazon, an area twice that of all forests in Costa Rica, to reveal the determinants of forest carbon density and to demonstrate the feasibility of mapping carbon emissions for REDD. We discovered previously unknown variation in carbon storage at multiple scales based on geologic substrate and forest type. From 1999 to 2009, emissions from land use totaled 1.1% of the standing carbon throughout the region. Forest degradation, such as from selective logging, increased regional carbon emissions by 47% over deforestation alone, and secondary regrowth provided an 18% offset against total gross emissions. Very high-resolution monitoring reduces uncertainty in carbon emissions for REDD programs while uncovering fundamental environmental controls on forest carbon storage and their interactions with land-use change.

  7. Assessing double counting of carbon emissions between forest land cover change and forest wildfires: a case study in the United States, 1992-2006

    Science.gov (United States)

    Daolan Zheng; Linda S. Heath; Mark J. Ducey; Brad. Quayle

    2013-01-01

    The relative contributions of double counting of carbon emissions between forest-to-nonforest cover change (FNCC) and forest wildfires are an unknown in estimating net forest carbon exchanges at large scales. This study employed land-cover change maps and forest fire data in the four representative states (Arkansas, California, Minnesota, and Washington) of the US for...

  8. Visual analysis of forest health using story maps: a tale of two forest insect pests

    Science.gov (United States)

    Susan J. Crocker; Brian F. Walters; Randall S. Morin

    2015-01-01

    Historically, results of surveys conducted by the Forest Inventory and Analysis (FIA) program of the USDA Forest Service were conveyed in printed reports, featuring text, tables and static figures. Since the advent of the Internet and with the ubiquity of mobile smart devices, technology has changed how people consume information, as well as how they experience and...

  9. The choice of forest site for recreation

    DEFF Research Database (Denmark)

    Agimass, Fitalew; Lundhede, Thomas; Panduro, Toke Emil

    2018-01-01

    logit as well as a random parameter logit model. The variables that are found to affect the choice of forest site to a visit for recreation include: forest area, tree species composition, forest density, availability of historical sites, terrain difference, state ownership, and distance. Regarding......In this paper, we investigate the factors that can influence the site choice of forest recreation. Relevant attributes are identified by using spatial data analysis from a questionnaire asking people to indicate their most recent forest visits by pinpointing on a map. The main objectives...

  10. Estimation of Forest Degradation with Remote Sensing and GIS Analysis

    DEFF Research Database (Denmark)

    Dons, Klaus

    +). An indirect remote sensing (RS) approach has been suggested to map the infrastructure used for degradation rather than the actual change in forest canopy cover. This offers a way to delineate intact forest land and to model and estimate emissions from forest degradation in the non‐intact forest land – thereby...

  11. Sustainability assessment in forest management based on individual preferences.

    Science.gov (United States)

    Martín-Fernández, Susana; Martinez-Falero, Eugenio

    2018-01-15

    This paper presents a methodology to elicit the preferences of any individual in the assessment of sustainable forest management at the stand level. The elicitation procedure was based on the comparison of the sustainability of pairs of forest locations. A sustainability map of the whole territory was obtained according to the individual's preferences. Three forest sustainability indicators were pre-calculated for each point in a study area in a Scots pine forest in the National Park of Sierra de Guadarrama in the Madrid Region in Spain to obtain the best management plan with the sustainability map. We followed a participatory process involving fifty people to assess the sustainability of the forest management and the methodology. The results highlighted the demand for conservative forest management, the usefulness of the methodology for managers, and the importance and necessity of incorporating stakeholders into forestry decision-making processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Forest Imaging

    Science.gov (United States)

    1992-01-01

    NASA's Technology Applications Center, with other government and academic agencies, provided technology for improved resources management to the Cibola National Forest. Landsat satellite images enabled vegetation over a large area to be classified for purposes of timber analysis, wildlife habitat, range measurement and development of general vegetation maps.

  13. ALOS PALSAR Applications in the Tropics and Subtropics: Characterisation, Mapping and Detecting Change in Forests and Coastal Wetlands

    Science.gov (United States)

    Lucas, Richard; Carreiras, Joao; Proisy, Christophe; Buniting, Peter

    2008-11-01

    Research undertaken as part of the Japanese Space Exploration Agency (JAXA) Principal Investigator (PI) and Kyoto and Carbon (K&C) programs has focused on the regional characterization (growth stage as a function of biomass and structure) and mapping of forests across northern Australia and mangroves (including wetlands) in selected tropical regions (northern Australia, Belize, French Guiana and Brazil) using Advanced Land Observing Satellite (ALOS) Phased Array L-band SAR (PALSAR) data, either singularly or in conjunction with other remote sensing (e.g., optical) data. Comparison against existing baseline datasets has allowed these data to be used for detecting change in these tropical and subtropical regions. Regional products (e.g., forest growth stage, mangrove/wetland extent and change) generated from the K&C dual polarimetric strip data are anticipated to benefit conservation of these ecosystems and allow better assessments of carbon stocks and changes in these as a function of natural and anthropogenic drivers, thereby supporting key international conventions.

  14. Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling

    Science.gov (United States)

    Bricher, Phillippa K.; Lucieer, Arko; Shaw, Justine; Terauds, Aleks; Bergstrom, Dana M.

    2013-01-01

    Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6–96.3%, κ = 0.849–0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments. PMID:23940805

  15. Vegetation Indices for Mapping Canopy Foliar Nitrogen in a Mixed Temperate Forest

    Directory of Open Access Journals (Sweden)

    Zhihui Wang

    2016-06-01

    Full Text Available Hyperspectral remote sensing serves as an effective tool for estimating foliar nitrogen using a variety of techniques. Vegetation indices (VIs are a simple means of retrieving foliar nitrogen. Despite their popularity, few studies have been conducted to examine the utility of VIs for mapping canopy foliar nitrogen in a mixed forest context. In this study, we assessed the performance of 32 vegetation indices derived from HySpex airborne hyperspectral images for estimating canopy mass-based foliar nitrogen concentration (%N in the Bavarian Forest National Park. The partial least squares regression (PLSR was performed for comparison. These vegetation indices were classified into three categories that are mostly correlated to nitrogen, chlorophyll, and structural properties such as leaf area index (LAI. %N was destructively measured in 26 broadleaf, needle leaf, and mixed stand plots to represent the different species and canopy structure. The canopy foliar %N is defined as the plot-level mean foliar %N of all species weighted by species canopy foliar mass fraction. Our results showed that the variance of canopy foliar %N is mainly explained by functional type and species composition. The normalized difference nitrogen index (NDNI produced the most accurate estimation of %N (R2CV = 0.79, RMSECV = 0.26. A comparable estimation of %N was obtained by the chlorophyll index Boochs2 (R2CV = 0.76, RMSECV = 0.27. In addition, the mean NIR reflectance (800–850 nm, representing canopy structural properties, also achieved a good accuracy in %N estimation (R2CV = 0.73, RMSECV = 0.30. The PLSR model provided a less accurate estimation of %N (R2CV = 0.69, RMSECV = 0.32. We argue that the good performance of all three categories of vegetation indices in %N estimation can be attributed to the synergy among plant traits (i.e., canopy structure, leaf chemical and optical properties while these traits may converge across plant species for evolutionary reasons. Our

  16. Using Multi Criteria Evaluation in Forest resource conservation in ...

    African Journals Online (AJOL)

    The research attempts to propose technology in managing scarce forest resources through the use of GIS techniques. It contributes to the discourse on forest management, ecological mapping and inventory of forest resources in Ghana. It provides an information base to tackle the threat of deforestation on a location by ...

  17. A New Synthetic Global Biomass Carbon Map for the year 2010

    Science.gov (United States)

    Spawn, S.; Lark, T.; Gibbs, H.

    2017-12-01

    Satellite technologies have facilitated a recent boom in high resolution, large-scale biomass estimation and mapping. These data are the input into a wide range of global models and are becoming the gold standard for required national carbon (C) emissions reporting. Yet their geographical and/or thematic scope may exclude some or all parts of a given country or region. Most datasets tend to focus exclusively on forest biomass. Grasslands and shrublands generally store less C than forests but cover nearly twice as much global land area and may represent a significant portion of a given country's biomass C stock. To address these shortcomings, we set out to create synthetic, global above- and below-ground biomass maps that combine recently-released satellite based data of standing forest biomass with novel estimates for non-forest biomass stocks that are typically neglected. For forests we integrated existing publicly available regional, global and biome-specific biomass maps and modeled below ground biomass using empirical relationships described in the literature. For grasslands, we developed models for both above- and below-ground biomass based on NPP, mean annual temperature and precipitation to extrapolate field measurements across the globe. Shrubland biomass was extrapolated from existing regional biomass maps using environmental factors to generate the first global estimate of shrub biomass. Our new synthetic map of global biomass carbon circa 2010 represents an update to the IPCC Tier-1 Global Biomass Carbon Map for the Year 2000 (Ruesch and Gibbs, 2008) using the best data currently available. In the absence of a single seamless remotely sensed map of global biomass, our synthetic map provides the only globally-consistent source of comprehensive biomass C data and is valuable for land change analyses, carbon accounting, and emissions modeling.

  18. Space-born spectrodirectional estimation of forest properties

    NARCIS (Netherlands)

    Verrelst, J.

    2010-01-01

    With the upcoming global warming forests are under threat. To forecast climate change impacts and adaptations, there is need for developing improved forest monitoring services, which are able to record, quantify and map bio-indicators of the forests’ health status across the globe. In this context,

  19. Determining subcanopy Psidium cattleianum invasion in Hawaiian forests using imaging spectroscopy

    Science.gov (United States)

    Jomar Barbosa; Gregory Asner; Roberta Martin; Claire Baldeck; Flint Hughes; Tracy Johnson

    2016-01-01

    High-resolution airborne imaging spectroscopy represents a promising avenue for mapping the spread of invasive tree species through native forests, but for this technology to be useful to forest managers there are two main technical challenges that must be addressed: (1) mapping a single focal species amongst a diverse array of other tree species; and (2) detecting...

  20. Mapping of past stand-level forest disturbances and estimation of time since disturbance using simulated spaceborne LiDAR data

    Science.gov (United States)

    Sanchez Lopez, N.; Hudak, A. T.; Boschetti, L.

    2017-12-01

    , and Elk Creek watersheds ( 54,000 ha) within the Nez Perce-Clearwater National Forest in Idaho, where airborne LiDAR and reference maps on TSD were available. Simulated GEDI footprints and waveforms were obtained from airborne LiDAR point clouds and the results were compared to similar analysis performed with airborne LiDAR.

  1. Development of a spatial forest data base for the eastern boreal forest region of Ontario. Forest fragmentation and biodiversity project technical report No. 14

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-12-31

    In 1991, a spatial forest database over large regions of Ontario was initiated as the basis for research into forest fragmentation and biodiversity using data generated from the digital analysis of LANDSAT thematic mapper satellite data integrated into a geographic information system (GIS). The project was later extended into the eastern segment of the Boreal forest system. This report describes preparation of the spatial forest data base over the eastern Boreal Forest Region that extends from the northern boundary of the Great Lakes-St. Lawrence Forest Region and the southern margin of the James Bay Lowland, between the Ontario-Quebec border and a point west of Michipicoten on Lake Superior. The report describes the methodology used to produce the data base and results, including mapping of water, dense and sparse conifer forest, mixed forest, dense and sparse deciduous forest, poorly vegetated areas, recent cutovers of less than 10 years, old cutovers and burns, recent burns of less than 10 years, wetlands, bedrock outcrops, agriculture, built-up areas, and mine tailings.

  2. Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Jiamin; Hoffman, Joanne; Zhao, Jocelyn; Yao, Jianhua; Lu, Le; Kim, Lauren; Turkbey, Evrim B.; Summers, Ronald M., E-mail: rms@nih.gov [Imaging Biomarkers and Computer-aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center Building, 10 Room 1C224 MSC 1182, Bethesda, Maryland 20892-1182 (United States)

    2016-07-15

    Purpose: To develop an automated system for mediastinal lymph node detection and station mapping for chest CT. Methods: The contextual organs, trachea, lungs, and spine are first automatically identified to locate the region of interest (ROI) (mediastinum). The authors employ shape features derived from Hessian analysis, local object scale, and circular transformation that are computed per voxel in the ROI. Eight more anatomical structures are simultaneously segmented by multiatlas label fusion. Spatial priors are defined as the relative multidimensional distance vectors corresponding to each structure. Intensity, shape, and spatial prior features are integrated and parsed by a random forest classifier for lymph node detection. The detected candidates are then segmented by the following curve evolution process. Texture features are computed on the segmented lymph nodes and a support vector machine committee is used for final classification. For lymph node station labeling, based on the segmentation results of the above anatomical structures, the textual definitions of mediastinal lymph node map according to the International Association for the Study of Lung Cancer are converted into patient-specific color-coded CT image, where the lymph node station can be automatically assigned for each detected node. Results: The chest CT volumes from 70 patients with 316 enlarged mediastinal lymph nodes are used for validation. For lymph node detection, their system achieves 88% sensitivity at eight false positives per patient. For lymph node station labeling, 84.5% of lymph nodes are correctly assigned to their stations. Conclusions: Multiple-channel shape, intensity, and spatial prior features aggregated by a random forest classifier improve mediastinal lymph node detection on chest CT. Using the location information of segmented anatomic structures from the multiatlas formulation enables accurate identification of lymph node stations.

  3. Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest

    International Nuclear Information System (INIS)

    Liu, Jiamin; Hoffman, Joanne; Zhao, Jocelyn; Yao, Jianhua; Lu, Le; Kim, Lauren; Turkbey, Evrim B.; Summers, Ronald M.

    2016-01-01

    Purpose: To develop an automated system for mediastinal lymph node detection and station mapping for chest CT. Methods: The contextual organs, trachea, lungs, and spine are first automatically identified to locate the region of interest (ROI) (mediastinum). The authors employ shape features derived from Hessian analysis, local object scale, and circular transformation that are computed per voxel in the ROI. Eight more anatomical structures are simultaneously segmented by multiatlas label fusion. Spatial priors are defined as the relative multidimensional distance vectors corresponding to each structure. Intensity, shape, and spatial prior features are integrated and parsed by a random forest classifier for lymph node detection. The detected candidates are then segmented by the following curve evolution process. Texture features are computed on the segmented lymph nodes and a support vector machine committee is used for final classification. For lymph node station labeling, based on the segmentation results of the above anatomical structures, the textual definitions of mediastinal lymph node map according to the International Association for the Study of Lung Cancer are converted into patient-specific color-coded CT image, where the lymph node station can be automatically assigned for each detected node. Results: The chest CT volumes from 70 patients with 316 enlarged mediastinal lymph nodes are used for validation. For lymph node detection, their system achieves 88% sensitivity at eight false positives per patient. For lymph node station labeling, 84.5% of lymph nodes are correctly assigned to their stations. Conclusions: Multiple-channel shape, intensity, and spatial prior features aggregated by a random forest classifier improve mediastinal lymph node detection on chest CT. Using the location information of segmented anatomic structures from the multiatlas formulation enables accurate identification of lymph node stations.

  4. The new Brazilian national forest inventory

    Science.gov (United States)

    Joberto V. de Freitas; Yeda M. M. de Oliveira; Doadi A. Brena; Guilherme L.A. Gomide; Jose Arimatea Silva; < i> et al< /i>

    2009-01-01

    The new Brazilian national forest inventory (NFI) is being planned to be carried out through five components: (1) general coordination, led by the Brazilian Forest Service; (2) vegetation mapping, which will serve as the basis for sample plot location; (3) field data collection; (4) landscape data collection of 10 x 10-km sample plots, based on high-resolution...

  5. Mapping migratory bird prevalence using remote sensing data fusion.

    Science.gov (United States)

    Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G; Sun, Mindy; Simard, Marc; Holmes, Richard

    2012-01-01

    Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.

  6. Mapping and monitoring forest remnants : a multiscale analysis of spatio-temporal data

    NARCIS (Netherlands)

    Carvalho, de L.M.T.

    2001-01-01

    KEYWORDS : Landsat, time series, machine learning, semideciduous Atlantic forest, Brazil, wavelet transforms, classification, change detection

    Forests play a major role in important global matters such as carbon cycle, climate change, and biodiversity. Besides, forests also

  7. Forest decline through radioactivity

    International Nuclear Information System (INIS)

    Reichelt, G.; Kollert, R.

    1985-01-01

    Is more serious damage of forest observed in the vicinity of nuclear reactors. How are those decline patterns to be explained. Does the combined effect of radioactivity and different air pollutants (such as nitrogen oxides, sulfur dioxide, oxidants etc.) have an influence in the decline of the forest. In what way do synergisms, i.e. mutually enhanced effects, participate. How does natural and artificial radioactivity affect the chemistry of air in the polluted atmosphere. What does this mean for the extension of nuclear energy, especially for the reprocessing plant planned. Damage in the forests near nuclear and industrial plants was mapped and the resulting hypotheses on possible emittors were statistically verified. Quantitative calculations as to the connection between nuclear energy and forest decline were carried through: they demand action. (orig./HP) [de

  8. Mapping Tropical Forest Mosaics with C- and L-band SAR: First Results from Osa Peninsula, Costa Rica

    Science.gov (United States)

    Pinto, N.; Hensley, S.; Aguilar-Amuchastegui, N.; Broadbent, E. N.; Ahmed, R.

    2016-12-01

    In tropical countries, economic incentives and improved infrastructure are creating forest mosaics where small-scale farming and industrial plantations are embedded within and potentially replacing native ecosystems. Practices such as agroforestry, slash-and-burn cultivation, and oil palm monocultures bring widely different impacts on carbon stocks. Characterizing these production systems is not only critical to ascribe deforestation to particular drivers, but also essential to understand the impact of macroeconomic scenarios, national policies, and land tenure schemes on carbon fluxes. The last decade has experienced a dramatic improvement in the extent and consistency of tree cover and gross deforestation products from optical imagery. At the same time, recent work shows that Synthetic Aperture Radar (SAR) can complement optical data and reveal structural types that cannot be easily resolved with reflectance measurements alone. While these results demonstrate the validity of sensor fusion methodologies, they typically rely on local classifications or even manual delineation and as such they cannot support large-scale investigations. Furthermore, there have been few attempts to exploit PolInSAR or multiple wavelengths that can provide critical information to resolve natural and anthropogenic land cover types. We report results from our research at Costa Rica's Osa Peninsula. This site is ideal for algorithm development as it includes a highly diverse tropical forest within Corcovado National Park, as well as agroforestry zones, mangroves, and palm plantations. We first integrate SAR backscatter and coherence data from NASA's L-band UAVSAR, JAXA's ALOS/PALSAR, and ESA's Sentinel to produce a map of structural types. Second, we assess whether coherence measurements and PolInSAR retrievals can be used to resolve forest stand differences at 30m resolution and disitinguish between primary and secondary forest sites.

  9. Fragmentation of Continental United States Forests

    Science.gov (United States)

    Kurt H. Riitters; James D. Wickham; Robert V. O' Neill; K. Bruce Jones; Elizabeth R. Smith; John W. Coulston; Timothy G. Wade; Jonathan H. Smith

    2002-01-01

    We report a multiple-scale analysis of forest fragmentation based on 30-m (0.09 ha pixel-1) land- cover maps for the conterminous United States. Each 0.09-ha unit of forest was classified according to fragmentation indexes measured within the surrounding landscape, for five landscape sizes including 2.25, 7.29, 65.61, 590.49, and 5314.41 ha....

  10. Derivation of a northern-hemispheric biomass map for use in global carbon cycle models

    Science.gov (United States)

    Thurner, Martin; Beer, Christian; Santoro, Maurizio; Carvalhais, Nuno; Wutzler, Thomas; Schepaschenko, Dmitry; Shvidenko, Anatoly; Kompter, Elisabeth; Levick, Shaun; Schmullius, Christiane

    2013-04-01

    Quantifying the state and the change of the World's forests is crucial because of their ecological, social and economic value. Concerning their ecological importance, forests provide important feedbacks on the global carbon, energy and water cycles. In addition to their influence on albedo and evapotranspiration, they have the potential to sequester atmospheric carbon dioxide and thus to mitigate global warming. The current state and inter-annual variability of forest carbon stocks remain relatively unexplored, but remote sensing can serve to overcome this shortcoming. While for the tropics wall-to-wall estimates of above-ground biomass have been recently published, up to now there was a lack of similar products covering boreal and temperate forests. Recently, estimates of forest growing stock volume (GSV) were derived from ENVISAT ASAR C-band data for latitudes above 30° N. Utilizing a wood density and a biomass compartment database, a forest carbon density map covering North-America, Europe and Asia with 0.01° resolution could be derived out of this dataset. Allometric functions between stem, branches, root and foliage biomass were fitted and applied for different leaf types (broadleaf, needleleaf deciduous, needleleaf evergreen forest). Additionally, this method enabled uncertainty estimation of the resulting carbon density map. Intercomparisons with inventory-based biomass products in Russia, Europe and the USA proved the high accuracy of this approach at a regional scale (r2 = 0.70 - 0.90). Based on the final biomass map, the forest carbon stocks and densities (excluding understorey vegetation) for three biomes were estimated across three continents. While 40.7 ± 15.7 Gt of carbon were found to be stored in boreal forests, temperate broadleaf/mixed forests and temperate conifer forests contain 24.5 ± 9.4 Gt(C) and 14.5 ± 4.8 Gt(C), respectively. In terms of carbon density, most of the carbon per area is stored in temperate conifer (62.1 ± 20.7 Mg(C)/ha(Forest

  11. Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast-growing Eucalyptus forest plantation using airborne LiDAR data.

    Science.gov (United States)

    Silva, Carlos Alberto; Hudak, Andrew Thomas; Klauberg, Carine; Vierling, Lee Alexandre; Gonzalez-Benecke, Carlos; de Padua Chaves Carvalho, Samuel; Rodriguez, Luiz Carlos Estraviz; Cardil, Adrián

    2017-12-01

    LiDAR remote sensing is a rapidly evolving technology for quantifying a variety of forest attributes, including aboveground carbon (AGC). Pulse density influences the acquisition cost of LiDAR, and grid cell size influences AGC prediction using plot-based methods; however, little work has evaluated the effects of LiDAR pulse density and cell size for predicting and mapping AGC in fast-growing Eucalyptus forest plantations. The aim of this study was to evaluate the effect of LiDAR pulse density and grid cell size on AGC prediction accuracy at plot and stand-levels using airborne LiDAR and field data. We used the Random Forest (RF) machine learning algorithm to model AGC using LiDAR-derived metrics from LiDAR collections of 5 and 10 pulses m -2 (RF5 and RF10) and grid cell sizes of 5, 10, 15 and 20 m. The results show that LiDAR pulse density of 5 pulses m -2 provides metrics with similar prediction accuracy for AGC as when using a dataset with 10 pulses m -2 in these fast-growing plantations. Relative root mean square errors (RMSEs) for the RF5 and RF10 were 6.14 and 6.01%, respectively. Equivalence tests showed that the predicted AGC from the training and validation models were equivalent to the observed AGC measurements. The grid cell sizes for mapping ranging from 5 to 20 also did not significantly affect the prediction accuracy of AGC at stand level in this system. LiDAR measurements can be used to predict and map AGC across variable-age Eucalyptus plantations with adequate levels of precision and accuracy using 5 pulses m -2 and a grid cell size of 5 m. The promising results for AGC modeling in this study will allow for greater confidence in comparing AGC estimates with varying LiDAR sampling densities for Eucalyptus plantations and assist in decision making towards more cost effective and efficient forest inventory.

  12. A framework for identifying carbon hotspots and forest management drivers

    Science.gov (United States)

    Nilesh Timilsina; Francisco J. Escobedo; Wendell P. Cropper; Amr Abd-Elrahman; Thomas Brandeis; Sonia Delphin; Samuel Lambert

    2013-01-01

    Spatial analyses of ecosystem system services that are directly relevant to both forest management decision making and conservation in the subtropics are rare. Also, frameworks that identify and map carbon stocks and corresponding forest management drivers using available regional, national, and international-level forest inventory datasets could provide insights into...

  13. Developing a Carbon Monitoring System For Pinyon-juniper Forests and Woodlands

    Science.gov (United States)

    Falkowski, M. J.; Hudak, A. T.; Fekety, P.; Filippelli, S.

    2017-12-01

    Pinyon-juniper (PJ) forests and woodlands are the third largest vegetation type in the United States. They cover over 40 million hectares across the western US, representing 40% of the total forest and woodland area in the Intermountain West. Although the density of carbon stored in these ecosystems is relatively low compared to other forest types, the vast area of short stature forests and woodlands (both nationally and globally) make them critical components of regional, national, and global carbon budgets. The overarching goal of this research is to prototype a carbon monitoring, reporting, and verification (MRV) system for characterizing total aboveground biomass stocks and flux across the PJ vegetation gradient in the western United States. We achieve this by combining in situ forest measurements and novel allometric equations with tree measurements derived from high resolution airborne imagery to map aboveground biomass across 500,000 km2 in the Western US. These high-resolution maps of aboveground biomass are then leveraged as training data to predict biomass flux through time from Landsat time-series data. The results from this research highlight the potential in mapping biomass stocks and flux in open forests and woodlands, and could be easily adopted into an MRV framework.

  14. California's forest resources. Preliminary assessment

    Energy Technology Data Exchange (ETDEWEB)

    1979-01-01

    This Preliminary Assessment was prepared in response to the California Forest Resources Assessment and Policy Act of 1977 (FRAPA). This Act was passed to improve the information base upon which State resource administrators formulate forest policy. The Act provides for this report and a full assessment by 1987 and at five year intervals thereafter. Information is presented under the following chapter titles: introduction to the forest resources assessment program; the forest area: a general description; classifications of the forest lands; the watersheds; forest lands and the air resource; fish and wildlife resources; the forested rangelands; the wilderness; forest lands as a recreation resource; the timber resource; wood energy; forest lands and the mineral, fossil fuels, and geothermal energy resources; mathematically modeling California's forest lands; vegetation mapping using remote sensing technology; important forest resources legislation; and, State and cooperative State/Federal forestry programs. Twelve indexes, a bibliography, and glossary are included. (JGB)

  15. EnviroAtlas - Memphis, TN - 51m Riparian Buffer Forest Cover

    Science.gov (United States)

    This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is forested. Forest is defined as Trees & Forest and Woody Wetlands. There is a potential for decreased water quality in areas where the riparian buffer is less forested. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  16. EnviroAtlas - Cleveland, OH - 51m Riparian Buffer Forest Cover

    Science.gov (United States)

    This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is forested. In this community, forest is defined as Trees & Forest and Woody Wetlands. There is a potential for decreased water quality in areas where the riparian buffer is less forested. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas ) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets)

  17. EnviroAtlas - Austin, TX - 51m Riparian Buffer Forest Cover

    Science.gov (United States)

    This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is forested. Forest is defined as Trees & Forest. There is a potential for decreased water quality in areas where the riparian buffer is less forested. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  18. Mapping Forest Canopy Height Across Large Areas by Upscaling ALS Estimates with Freely Available Satellite Data

    Directory of Open Access Journals (Sweden)

    Phil Wilkes

    2015-09-01

    Full Text Available Operational assessment of forest structure is an on-going challenge for land managers, particularly over large, remote or inaccessible areas. Here, we present an easily adopted method for generating a continuous map of canopy height at a 30 m resolution, demonstrated over 2.9 million hectares of highly heterogeneous forest (canopy height 0–70 m in Victoria, Australia. A two-stage approach was utilized where Airborne Laser Scanning (ALS derived canopy height, captured over ~18% of the study area, was used to train a regression tree ensemble method; random forest. Predictor variables, which have a global coverage and are freely available, included Landsat Thematic Mapper (Tasselled Cap transformed, Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index time series, Shuttle Radar Topography Mission elevation data and other ancillary datasets. Reflectance variables were further processed to extract additional spatial and temporal contextual and textural variables. Modeled canopy height was validated following two approaches; (i random sample cross validation; and (ii with 108 inventory plots from outside the ALS capture extent. Both the cross validation and comparison with inventory data indicate canopy height can be estimated with a Root Mean Square Error (RMSE of ≤ 31% (~5.6 m at the 95th percentile confidence interval. Subtraction of the systematic component of model error, estimated from training data error residuals, rescaled canopy height values to more accurately represent the response variable distribution tails e.g., tall and short forest. Two further experiments were carried out to test the applicability and scalability of the presented method. Results suggest that (a no improvement in canopy height estimation is achieved when models were constructed and validated for smaller geographic areas, suggesting there is no upper limit to model scalability; and (b training data can be captured over a small

  19. Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

    Science.gov (United States)

    Hoffer, R. M.; Dean, M. E.; Knowlton, D. J.; Latty, R. S.

    1982-01-01

    Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented.

  20. Mapping Deciduous Rubber Plantation Areas and Stand Ages with PALSAR and Landsat Images

    Directory of Open Access Journals (Sweden)

    Weili Kou

    2015-01-01

    Full Text Available Accurate and updated finer resolution maps of rubber plantations and stand ages are needed to understand and assess the impacts of rubber plantations on regional ecosystem processes. This study presented a simple method for mapping rubber plantation areas and their stand ages by integration of PALSAR 50-m mosaic images and multi-temporal Landsat TM/ETM+ images. The L-band PALSAR 50-m mosaic images were used to map forests (including both natural forests and rubber trees and non-forests. For those PALSAR-based forest pixels, we analyzed the multi-temporal Landsat TM/ETM+ images from 2000 to 2009. We first studied phenological signatures of deciduous rubber plantations (defoliation and foliation and natural forests through analysis of surface reflectance, Normal Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, and Land Surface Water Index (LSWI and generated a map of rubber plantations in 2009. We then analyzed phenological signatures of rubber plantations with different stand ages and generated a map, in 2009, of rubber plantation stand ages (≤5, 6–10, >10 years-old based on multi-temporal Landsat images. The resultant maps clearly illustrated how rubber plantations have expanded into the mountains in the study area over the years. The results in this study demonstrate the potential of integrating microwave (e.g., PALSAR and optical remote sensing in the characterization of rubber plantations and their expansion over time.

  1. New Geospatial Approaches for Efficiently Mapping Forest Biomass Logistics at High Resolution over Large Areas

    Directory of Open Access Journals (Sweden)

    John Hogland

    2018-04-01

    Full Text Available Adequate biomass feedstock supply is an important factor in evaluating the financial feasibility of alternative site locations for bioenergy facilities and for maintaining profitability once a facility is built. We used newly developed spatial analysis and logistics software to model the variables influencing feedstock supply and to estimate and map two components of the supply chain for a bioenergy facility: (1 the total biomass stocks available within an economically efficient transportation distance; (2 the cost of logistics to move the required stocks from the forest to the facility. Both biomass stocks and flows have important spatiotemporal dynamics that affect procurement costs and project viability. Though seemingly straightforward, these two components can be difficult to quantify and map accurately in a useful and spatially explicit manner. For an 8 million hectare study area, we used raster-based methods and tools to quantify and visualize these supply metrics at 10 m2 spatial resolution. The methodology and software leverage a novel raster-based least-cost path modeling algorithm that quantifies off-road and on-road transportation and other logistics costs. The results of the case study highlight the efficiency, flexibility, fine resolution, and spatial complexity of model outputs developed for facility siting and procurement planning.

  2. Detecting of forest afforestation and deforestation in Hainan Jianfengling Forest Park (China) using yearly Landsat time-series images

    Science.gov (United States)

    Jiao, Quanjun; Zhang, Xiao; Sun, Qi

    2018-03-01

    The availability of dense time series of Landsat images pro-vides a great chance to reconstruct forest disturbance and change history with high temporal resolution, medium spatial resolution and long period. This proposal aims to apply forest change detection method in Hainan Jianfengling Forest Park using yearly Landsat time-series images. A simple detection method from the dense time series Landsat NDVI images will be used to reconstruct forest change history (afforestation and deforestation). The mapping result showed a large decrease occurred in the extent of closed forest from 1980s to 1990s. From the beginning of the 21st century, we found an increase in forest areas with the implementation of forestry measures such as the prohibition of cutting and sealing in our study area. Our findings provide an effective approach for quickly detecting forest changes in tropical original forest, especially for afforestation and deforestation, and a comprehensive analysis tool for forest resource protection.

  3. EUFODOS: European Forest Downstream Services - Improved Information on Forest Structure and Damage

    Science.gov (United States)

    Hirschmugl, M.; Gallaun, H.; Wack, R.; Granica, K.; Schardt, M.

    2013-05-01

    Forests play a key role in the European economy and environment. This role incorporates ecological functions which can be affected by the occurrence of insect infestations, forest fire, heavy snowfall or windfall events. Local or Regional Authorities (LRAs) thus require detailed information on the degradation status of their forests to be able to take appropriate measures for their forest management plans. In the EUFODOS project, state-of-the-art satellite and laser scanning technologies are used to provide forest authorities with cost-effective and comprehensive information on forest structure and damage. One of the six test sites is located in the Austrian province of Styria where regional forest authorities have expressed a strong need for detailed forest parameters in protective forest. As airborne laser-scanning data is available, it will be utilized to derive detailed forest parameters such as the upper forest border line, tree height, growth classes, forest density, vertical structure or volume. At the current project status, the results of (i) the forest border line, (ii) the segmentation of forest stands and (iii) the tree top detection are available and presented including accuracy assessment and interim results are shown for timber volume estimations. The final results show that the forest border can be mapped operationally with an overall accuracy of almost 99% from LiDAR data. For the segmentation of forest stands, a comparison of the automatically derived result with visual-manual delineation showed in general a more detailed segmentation result, but for all visual-manual segments a congruence of 87% within a 4 m buffer. Tree top detections were compared to stem numbers estimated based on angle-count samplings in a field campaign, which led to a correlation coefficient (R) of 0.79.

  4. Biomass accumulation rates of Amazonian secondary forest and biomass of old-growth forests from Landsat time series and the Geoscience Laser Altimeter System

    Science.gov (United States)

    E. H. Helmer; M. A. Lefsky; D. A. Roberts

    2009-01-01

    We estimate the age of humid lowland tropical forests in Rondônia, Brazil, from a somewhat densely spaced time series of Landsat images (1975–2003) with an automated procedure, the Threshold Age Mapping Algorithm (TAMA), first described here. We then estimate a landscape-level rate of aboveground woody biomass accumulation of secondary forest by combining forest age...

  5. The Finnish multisource national forest inventory: small-area estimation and map production

    Science.gov (United States)

    Erkki Tomppo

    2009-01-01

    A driving force motivating development of the multisource national forest inventory (MS-NFI) in connection with the Finnish national forest inventory (NFI) was the desire to obtain forest resource information for smaller areas than is possible using field data only without significantly increasing the cost of the inventory. A basic requirement for the method was that...

  6. Multidimensional remote sensing based mapping of tropical forests and their dynamics

    NARCIS (Netherlands)

    Dutrieux, L.P.

    2016-01-01

    Tropical forests concentrate a large part of the terrestrial biodiversity, provide important resources, and deliver many ecosystem services such as climate regulation, carbon sequestration, and hence climate change mitigation. While in the current context of anthropogenic pressure these forests

  7. Forest soil survey and mapping of the nutrient status of the vegetation on Olkiluoto island. Results from the first inventory on the FEH plots

    International Nuclear Information System (INIS)

    Tamminen, P.; Aro, A.; Salemaa, M.

    2007-09-01

    The aim of the inventory was to determine the status of the forest soils and to map the current nutrient status of forest vegetation on Olkiluoto Island in order to create a basis for monitoring future changes in the forests and to provide data for a biospheric description of the island. The study was carried out on 94 FEH plots, which were selected from the forest extensive monitoring network (FET plots) on the basis of the forest site type distribution and tree stand characteristics measured on the island during 2002 - 2004. Forest soils on Olkiluoto are very young and typical of soils along the Finnish coast, i.e. stony or shallow soils overlying bedrock, but with more nutrients than the forest soils inland. In addition to nutrients, the heavy metal concentrations are clearly higher on Olkiluoto than the average values for Finnish forest soils. The soil in the alder stands growing along the seashore is different from the other soils on Olkiluoto and the control soils inland. These soils are less acidic and have large reserves of sodium, magnesium and nitrogen. Macronutrient concentrations in vascular plant species were relatively similar to those reported for Southern Finland. However, it is obvious that the accumulation of particulate material on the vegetation, especially on forest floor bryophytes, has increased due to emissions derived from the construction of roads, drilling and rock crushing, as well as the other industrial activities on Olkiluoto Island. Leaf and needle analysis indicated that the tree stands had, in the main, a good nutrient status on Olkiluoto Island. The surveying methods used on Olkiluoto are better suited to detect systematic changes over a larger area or within a group of sample plots than the changes on individual plots. (orig.)

  8. Evaluating the condition of a mangrove forest of the Mexican Pacific based on an estimated leaf area index mapping approach.

    Science.gov (United States)

    Kovacs, J M; King, J M L; Flores de Santiago, F; Flores-Verdugo, F

    2009-10-01

    Given the alarming global rates of mangrove forest loss it is important that resource managers have access to updated information regarding both the extent and condition of their mangrove forests. Mexican mangroves in particular have been identified as experiencing an exceptional high annual rate of loss. However, conflicting studies, using remote sensing techniques, of the current state of many of these forests may be hindering all efforts to conserve and manage what remains. Focusing on one such system, the Teacapán-Agua Brava-Las Haciendas estuarine-mangrove complex of the Mexican Pacific, an attempt was made to develop a rapid method of mapping the current condition of the mangroves based on estimated LAI. Specifically, using an AccuPAR LP-80 Ceptometer, 300 indirect in situ LAI measurements were taken at various sites within the black mangrove (Avicennia germinans) dominated forests of the northern section of this system. From this sample, 225 measurements were then used to develop linear regression models based on their relationship with corresponding values derived from QuickBird very high resolution optical satellite data. Specifically, regression analyses of the in situ LAI with both the normalized difference vegetation index (NDVI) and the simple ration (SR) vegetation index revealed significant positive relationships [LAI versus NDVI (R (2) = 0.63); LAI versus SR (R (2) = 0.68)]. Moreover, using the remaining sample, further examination of standard errors and of an F test of the residual variances indicated little difference between the two models. Based on the NDVI model, a map of estimated mangrove LAI was then created. Excluding the dead mangrove areas (i.e. LAI = 0), which represented 40% of the total 30.4 km(2) of mangrove area identified in the scene, a mean estimated LAI value of 2.71 was recorded. By grouping the healthy fringe mangrove with the healthy riverine mangrove and by grouping the dwarf mangrove together with the poor condition

  9. Forest biomass carbon stocks and variation in Tibet's carbon-dense forests from 2001 to 2050.

    Science.gov (United States)

    Sun, Xiangyang; Wang, Genxu; Huang, Mei; Chang, Ruiying; Ran, Fei

    2016-10-05

    Tibet's forests, in contrast to China's other forests, are characterized by primary forests, high carbon (C) density and less anthropogenic disturbance, and they function as an important carbon pool in China. Using the biomass C density data from 413 forest inventory sites and a spatial forest age map, we developed an allometric equation for the forest biomass C density and forest age to assess the spatial biomass C stocks and variation in Tibet's forests from 2001 to 2050. The results indicated that the forest biomass C stock would increase from 831.1 Tg C in 2001 to 969.4 Tg C in 2050, with a net C gain of 3.6 Tg C yr -1 between 2001 and 2010 and a decrease of 1.9 Tg C yr -1 between 2040 and 2050. Carbon tends to allocate more in the roots of fir forests and less in the roots of spruce and pine forests with increasing stand age. The increase of the biomass carbon pool does not promote significant augmentation of the soil carbon pool. Our findings suggest that Tibet's mature forests will remain a persistent C sink until 2050. However, afforestation or reforestation, especially with the larger carbon sink potential forest types, such as fir and spruce, should be carried out to maintain the high C sink capacity.

  10. Object-based random forest classification of Landsat ETM+ and WorldView-2 satellite imagery for mapping lowland native grassland communities in Tasmania, Australia

    Science.gov (United States)

    Melville, Bethany; Lucieer, Arko; Aryal, Jagannath

    2018-04-01

    This paper presents a random forest classification approach for identifying and mapping three types of lowland native grassland communities found in the Tasmanian Midlands region. Due to the high conservation priority assigned to these communities, there has been an increasing need to identify appropriate datasets that can be used to derive accurate and frequently updateable maps of community extent. Therefore, this paper proposes a method employing repeat classification and statistical significance testing as a means of identifying the most appropriate dataset for mapping these communities. Two datasets were acquired and analysed; a Landsat ETM+ scene, and a WorldView-2 scene, both from 2010. Training and validation data were randomly subset using a k-fold (k = 50) approach from a pre-existing field dataset. Poa labillardierei, Themeda triandra and lowland native grassland complex communities were identified in addition to dry woodland and agriculture. For each subset of randomly allocated points, a random forest model was trained based on each dataset, and then used to classify the corresponding imagery. Validation was performed using the reciprocal points from the independent subset that had not been used to train the model. Final training and classification accuracies were reported as per class means for each satellite dataset. Analysis of Variance (ANOVA) was undertaken to determine whether classification accuracy differed between the two datasets, as well as between classifications. Results showed mean class accuracies between 54% and 87%. Class accuracy only differed significantly between datasets for the dry woodland and Themeda grassland classes, with the WorldView-2 dataset showing higher mean classification accuracies. The results of this study indicate that remote sensing is a viable method for the identification of lowland native grassland communities in the Tasmanian Midlands, and that repeat classification and statistical significant testing can be

  11. Roles of Fog and Topography in Redwood Forest Hydrology

    Science.gov (United States)

    Francis, E. J.; Asner, G. P.

    2017-12-01

    Spatial variability of water in forests is a function of both climatic gradients that control water inputs and topo-edaphic variation that determines the flows of water belowground, as well as interactions of climate with topography. Coastal redwood forests are hydrologically unique because they are influenced by coastal low clouds, or fog, that is advected onto land by a strong coastal-to-inland temperature difference. Where fog intersects the land surface, annual water inputs from summer fog drip can be greater than that of winter rainfall. In this study, we take advantage of mapped spatial gradients in forest canopy water storage, topography, and fog cover in California to better understand the roles and interactions of fog and topography in the hydrology of redwood forests. We test a conceptual model of redwood forest hydrology with measurements of canopy water content derived from high-resolution airborne imaging spectroscopy, topographic variables derived from high-resolution LiDAR data, and fog cover maps derived from NASA MODIS data. Landscape-level results provide insight into hydrological processes within redwood forests, and cross-site analyses shed light on their generality.

  12. Aboveground Biomass Variability Across Intact and Degraded Forests in the Brazilian Amazon

    Science.gov (United States)

    Longo, Marcos; Keller, Michael; Dos-Santos, Maiza N.; Leitold, Veronika; Pinage, Ekena R.; Baccini, Alessandro; Saatchi, Sassan; Nogueira, Euler M.; Batistella, Mateus; Morton, Douglas C.

    2016-01-01

    Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, re, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n 359) and airborne lidar data (18,000 ha) assembled to date for the Brazilian Amazon. We developed statistical models relating inventory ACD estimates to lidar metrics that explained70 of the variance across forest types. Airborne lidar-ACD estimates for intact forests ranged between 5.0 +/- 2.5 and 31.9 +/- 10.8 kg C m(exp -2). Degradation carbon losses were large and persistent. Sites that burned multiple times within a decade lost up to 15.0 +/- 0.7 kg C m(-2)(94%) of ACD. Forests that burned nearly15 years ago had between 4.1 +/- 0.5 and 6.8 +/- 0.3 kg C m(exp -2) (22-40%) less ACD than intact forests. Even for low-impact logging disturbances, ACD was between 0.7 +/- 0.3 and 4.4 +/- 0.4 kg C m(exp -2)(4-21%) lower than unlogged forests. Comparing biomass estimates from airborne lidar to existing biomass maps, we found that regional and pan-tropical products consistently overestimated ACD in degraded forests, under-estimated ACD in intact forests, and showed little sensitivity to res and logging. Fine-scale heterogeneity in ACD across intact and degraded forests highlights the benefits of airborne lidar for carbon mapping. Differences between airborne lidar and regional biomass maps underscore the need to improve and update biomass estimates for dynamic land use frontiers, to better characterize deforestation and degradation carbon emissions for regional carbon budgets and Reduce Emissions from Deforestation and forest Degradation(REDD+).

  13. Age structure and disturbance legacy of North American forests

    Directory of Open Access Journals (Sweden)

    Y. Pan

    2011-03-01

    Full Text Available Most forests of the world are recovering from a past disturbance. It is well known that forest disturbances profoundly affect carbon stocks and fluxes in forest ecosystems, yet it has been a great challenge to assess disturbance impacts in estimates of forest carbon budgets. Net sequestration or loss of CO2 by forests after disturbance follows a predictable pattern with forest recovery. Forest age, which is related to time since disturbance, is a useful surrogate variable for analyses of the impact of disturbance on forest carbon. In this study, we compiled the first continental forest age map of North America by combining forest inventory data, historical fire data, optical satellite data and the dataset from NASA's Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS project. A companion map of the standard deviations for age estimates was developed for quantifying uncertainty. We discuss the significance of the disturbance legacy from the past, as represented by current forest age structure in different regions of the US and Canada, by analyzing the causes of disturbances from land management and nature over centuries and at various scales. We also show how such information can be used with inventory data for analyzing carbon management opportunities. By combining geographic information about forest age with estimated C dynamics by forest type, it is possible to conduct a simple but powerful analysis of the net CO2 uptake by forests, and the potential for increasing (or decreasing this rate as a result of direct human intervention in the disturbance/age status. Finally, we describe how the forest age data can be used in large-scale carbon modeling, both for land-based biogeochemistry models and atmosphere-based inversion models, in order to improve the spatial accuracy of carbon cycle simulations.

  14. Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

    Directory of Open Access Journals (Sweden)

    Wilson Barry Tyler

    2013-01-01

    Full Text Available Abstract The U.S. has been providing national-scale estimates of forest carbon (C stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these estimates to finer scales to enable strategic forest management and monitoring activities focused on various ecosystem services such as C storage enhancement. Through application of a nearest-neighbor imputation approach, spatially extant estimates of forest C density were developed for the conterminous U.S. using the U.S.’s annual forest inventory. Results suggest that an existing forest inventory plot imputation approach can be readily modified to provide raster maps of C density across a range of pools (e.g., live tree to soil organic carbon and spatial scales (e.g., sub-county to biome. Comparisons among imputed maps indicate strong regional differences across C pools. The C density of pools closely related to detrital input (e.g., dead wood is often highest in forests suffering from recent mortality events such as those in the northern Rocky Mountains (e.g., beetle infestations. In contrast, live tree carbon density is often highest on the highest quality forest sites such as those found in the Pacific Northwest. Validation results suggest strong agreement between the estimates produced from the forest inventory plots and those from the imputed maps, particularly when the C pool is closely associated with the imputation model (e.g., aboveground live biomass and live tree basal area, with weaker agreement for detrital pools (e.g., standing dead trees. Forest inventory imputed plot maps provide an efficient and flexible approach to monitoring diverse C pools at national (e.g., UNFCCC and regional scales (e.g., Reducing Emissions from Deforestation and Forest

  15. Taboos and forest governance: informal protection of hot spot dry forest in southern Madagascar.

    Science.gov (United States)

    Tengö, Maria; Johansson, Kristin; Rakotondrasoa, Fanambinantsoa; Lundberg, Jakob; Andriamaherilala, Jean-Aimé; Rakotoarisoa, Jean-Aimé; Elmqvist, Thomas

    2007-12-01

    In the dry forest of southern Madagascar, a region of global conservation priority, formally protected areas are nearly totally absent. We illustrate how the continued existence of unique forest habitats in the Androy region is directly dependent on informal institutions, taboos, regulating human behavior. Qualitative interviews to map and analyze the social mechanisms underlying forest protection have been combined with vegetation analyses of species diversity and composition. Of 188 forest patches, 93% were classified as protected, and in Southern Androy all remaining forest patches larger than 5 ha were protected. Eight different types of forests, with a gradient of social fencing from open access to almost complete entry prohibitions, were identified. Transgressions were well enforced with strong sanctions of significant economic as well as religious importance. Analyses of species diversity between protected and unprotected forests were complicated because of size differences and access restrictions. However, since, for example, in southern Androy >90% of the total remaining forest cover is protected through taboos, these informal institutions represent an important, and presently the only, mechanism for conservation of the highly endemic forest species. We conclude that social aspects, such as local beliefs and legitimate sanctioning systems, need to be analyzed and incorporated along with biodiversity studies for successful conservation.

  16. Identification of a system of ecologically homogeneous areas and of priority intervention levels for forest plantation planning in Sicily

    Directory of Open Access Journals (Sweden)

    Pizzurro GM

    2008-10-01

    Full Text Available Afforestation and reforestation activities in Sicily have been widespreaded in the last century. The results of forestation activities indicate the need to adopt a operational tools to promote the extension of forest surface at regional and sub-regional levels. In this view, with the aim to produce useful tools for forest plantation planning, the entire regional area was analysed and ecologically homogeneous areas have been identified to join and target arboriculture and/or forestation plantation activities, to choose tree and shrub species for different environments and to identify priority areas of intervention. The map of Rivas-Martinez bioclimate and the map of litological types were used as basic information layers to map pedo-climatic homogeneous areas. In order to mitigate disruptive hydrogeological effects and to reduce desertification risk and forest fragmentation, the Corine Land Cover map (CLC2000, the hydrogeological bond map and the desertification risk map were used to identify areas characterized by urgent need of forest activities at high priority level. A total of 23 ecologically homogeneous areas have been identified in Sicily, while more than a quarter of the regional surface has been characterized as highest priority intervention level. At sub-regional level, the target of the analysis was carried out at administrative province and at hydrographic basin level.

  17. Forest management and water in the United States [Chapter 13

    Science.gov (United States)

    Daniel G. Neary

    2017-01-01

    This chapter outlines a brief history of the United States native forests and forest plantations. It describes the past and current natural and plantation forest distribution (map, area, main species), as well as main products produced (timber, pulp, furniture, etc.). Integrated into this discussion is a characterization of the water resources of the United States and...

  18. Managing Forest Resources in Sub-Saharan Africa : Issues and Challenges

    OpenAIRE

    Narenda P. Sharma; Simon Reitbergen; Claude R. Heimo; Joti Patel

    1994-01-01

    The note summarizes the findings of the Africa Forest Strategy Paper, which responded to the problems confronting forest resources in the Sub-Saharan Africa (SSA), providing a comprehensive overview, and analysis of the forest sector, and mapping a set of actions for consideration by African countries. The diagnosis highlights the nexus between rapid population growth, environmental degrad...

  19. Forest Stand Segmentation Using Airborne LIDAR Data and Very High Resolution Multispectral Imagery

    Science.gov (United States)

    Dechesne, Clément; Mallet, Clément; Le Bris, Arnaud; Gouet, Valérie; Hervieu, Alexandre

    2016-06-01

    Forest stands are the basic units for forest inventory and mapping. Stands are large forested areas (e.g., ≥ 2 ha) of homogeneous tree species composition. The accurate delineation of forest stands is usually performed by visual analysis of human operators on very high resolution (VHR) optical images. This work is highly time consuming and should be automated for scalability purposes. In this paper, a method based on the fusion of airborne laser scanning data (or lidar) and very high resolution multispectral imagery for automatic forest stand delineation and forest land-cover database update is proposed. The multispectral images give access to the tree species whereas 3D lidar point clouds provide geometric information on the trees. Therefore, multi-modal features are computed, both at pixel and object levels. The objects are individual trees extracted from lidar data. A supervised classification is performed at the object level on the computed features in order to coarsely discriminate the existing tree species in the area of interest. The analysis at tree level is particularly relevant since it significantly improves the tree species classification. A probability map is generated through the tree species classification and inserted with the pixel-based features map in an energetical framework. The proposed energy is then minimized using a standard graph-cut method (namely QPBO with α-expansion) in order to produce a segmentation map with a controlled level of details. Comparison with an existing forest land cover database shows that our method provides satisfactory results both in terms of stand labelling and delineation (matching ranges between 94% and 99%).

  20. Spatio-temporal change in forest cover and carbon storage considering actual and potential forest cover in South Korea.

    Science.gov (United States)

    Nam, Kijun; Lee, Woo-Kyun; Kim, Moonil; Kwak, Doo-Ahn; Byun, Woo-Hyuk; Yu, Hangnan; Kwak, Hanbin; Kwon, Taesung; Sung, Joohan; Chung, Dong-Jun; Lee, Seung-Ho

    2015-07-01

    This study analyzes change in carbon storage by applying forest growth models and final cutting age to actual and potential forest cover for six major tree species in South Korea. Using National Forest Inventory data, the growth models were developed to estimate mean diameter at breast height, tree height, and number of trees for Pinus densiflora, Pinus koraiensis, Pinus rigida, Larix kaempferi, Castanea crenata and Quercus spp. stands. We assumed that actual forest cover in a forest type map will change into potential forest covers according to the Hydrological and Thermal Analogy Groups model. When actual forest cover reaches the final cutting age, forest volume and carbon storage are estimated by changed forest cover and its growth model. Forest volume between 2010 and 2110 would increase from 126.73 to 157.33 m(3) hm(-2). Our results also show that forest cover, volume, and carbon storage could abruptly change by 2060. This is attributed to the fact that most forests are presumed to reach final cutting age. To avoid such dramatic change, a regeneration and yield control scheme should be prepared and implemented in a way that ensures balance in forest practice and yield.

  1. Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier—A Case of Yuyao, China

    Directory of Open Access Journals (Sweden)

    Quanlong Feng

    2015-03-01

    Full Text Available Flooding is a severe natural hazard, which poses a great threat to human life and property, especially in densely-populated urban areas. As one of the fastest developing fields in remote sensing applications, an unmanned aerial vehicle (UAV can provide high-resolution data with a great potential for fast and accurate detection of inundated areas under complex urban landscapes. In this research, optical imagery was acquired by a mini-UAV to monitor the serious urban waterlogging in Yuyao, China. Texture features derived from gray-level co-occurrence matrix were included to increase the separability of different ground objects. A Random Forest classifier, consisting of 200 decision trees, was used to extract flooded areas in the spectral-textural feature space. Confusion matrix was used to assess the accuracy of the proposed method. Results indicated the following: (1 Random Forest showed good performance in urban flood mapping with an overall accuracy of 87.3% and a Kappa coefficient of 0.746; (2 the inclusion of texture features improved classification accuracy significantly; (3 Random Forest outperformed maximum likelihood and artificial neural network, and showed a similar performance to support vector machine. The results demonstrate that UAV can provide an ideal platform for urban flood monitoring and the proposed method shows great capability for the accurate extraction of inundated areas.

  2. Visualizing the Forest in a Boreal Forest Landscape—The Perspective of Swedish Municipal Comprehensive Planning

    Directory of Open Access Journals (Sweden)

    Camilla Thellbro

    2017-05-01

    Full Text Available At the international policy level, there is a clear link between access to information about forests and the work towards sustainable land use. However, involving forests in planning for sustainable development (SuD at the Swedish local level, by means of municipal comprehensive planning (MCP, is complicated by sector structure and legislation. Currently, there is a gap or hole in the MCP process when it comes to use and access to knowledge about forest conditions and forest land use. This hole limits the possibilities to formulate well-informed municipal visions and goals for sustainable forest land use as well as for overall SuD. Here we introduce an approach for compilation and presentation of geographic information to increase the preconditions for integrating forest information into Swedish MCP. We produce information about forest ownership patterns and forest conditions in terms of age and significant ecological and social values in forests for a case study municipality. We conclude that it is possible to effectively compile geographic and forest-related information to fill the hole in the municipal land use map. Through our approach, MCP could be strengthened as a tool for overall land use planning and hence as a base in SuD planning.

  3. EnviroAtlas - Des Moines, IA - 51m Riparian Buffer Forest Cover

    Science.gov (United States)

    This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is forested. Forest is defined as Trees & Forest. There is a potential for decreased water quality in areas where the riparian buffer is less forested. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://enviroatlas.epa.gov/EnviroAtlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets)

  4. EnviroAtlas - New York, NY - 51m Riparian Buffer Forest Cover

    Science.gov (United States)

    This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is forested. In this community, forest is defined as Trees & Forest. There is a potential for decreased water quality in areas where the riparian buffer is less forested. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets)

  5. Preliminary work of mangrove ecosystem carbon stock mapping in small island using remote sensing: above and below ground carbon stock mapping on medium resolution satellite image

    Science.gov (United States)

    Wicaksono, Pramaditya; Danoedoro, Projo; Hartono, Hartono; Nehren, Udo; Ribbe, Lars

    2011-11-01

    Mangrove forest is an important ecosystem located in coastal area that provides various important ecological and economical services. One of the services provided by mangrove forest is the ability to act as carbon sink by sequestering CO2 from atmosphere through photosynthesis and carbon burial on the sediment. The carbon buried on mangrove sediment may persist for millennia before return to the atmosphere, and thus act as an effective long-term carbon sink. Therefore, it is important to understand the distribution of carbon stored within mangrove forest in a spatial and temporal context. In this paper, an effort to map carbon stocks in mangrove forest is presented using remote sensing technology to overcome the handicap encountered by field survey. In mangrove carbon stock mapping, the use of medium spatial resolution Landsat 7 ETM+ is emphasized. Landsat 7 ETM+ images are relatively cheap, widely available and have large area coverage, and thus provide a cost and time effective way of mapping mangrove carbon stocks. Using field data, two image processing techniques namely Vegetation Index and Linear Spectral Unmixing (LSU) were evaluated to find the best method to explain the variation in mangrove carbon stocks using remote sensing data. In addition, we also tried to estimate mangrove carbon sequestration rate via multitemporal analysis. Finally, the technique which produces significantly better result was used to produce a map of mangrove forest carbon stocks, which is spatially extensive and temporally repetitive.

  6. Examining fire-induced forest changes using novel remote sensing technique: a case study in a mixed pine-oak forest

    Science.gov (United States)

    Meng, R.; Wu, J.; Zhao, F. R.; Cook, B.; Hanavan, R. P.; Serbin, S.

    2017-12-01

    Fire-induced forest changes has long been a central focus for forest ecology and global carbon cycling studies, and is becoming a pressing issue for global change biologists particularly with the projected increases in the frequency and intensity of fire with a warmer and drier climate. Compared with time-consuming and labor intensive field-based approaches, remote sensing offers a promising way to efficiently assess fire effects and monitor post-fire forest responses across a range of spatial and temporal scales. However, traditional remote sensing studies relying on simple optical spectral indices or coarse resolution imagery still face a number of technical challenges, including confusion or contamination of the signal by understory dynamics and mixed pixels with moderate to coarse resolution data (>= 30 m). As such, traditional remote sensing may not meet the increasing demand for more ecologically-meaningful monitoring and quantitation of fire-induced forest changes. Here we examined the use of novel remote sensing technique (i.e. airborne imaging spectroscopy and LiDAR measurement, very high spatial resolution (VHR) space-borne multi-spectral measurement, and high temporal-spatial resolution UAS-based (Unmanned Aerial System) imagery), in combination with field and phenocam measurements to map forest burn severity across spatial scales, quantify crown-scale post-fire forest recovery rate, and track fire-induced phenology changes in the burned areas. We focused on a mixed pine-oak forest undergoing multiple fire disturbances for the past several years in Long Island, NY as a case study. We demonstrate that (1) forest burn severity mapping from VHR remote sensing measurement can capture crown-scale heterogeneous fire patterns over large-scale; (2) the combination of VHR optical and structural measurements provides an efficient means to remotely sense species-level post-fire forest responses; (3) the UAS-based remote sensing enables monitoring of fire

  7. Digital surveying and mapping of forest road network for development of a GIS tool for the effective protection and management of natural ecosystems

    Science.gov (United States)

    Drosos, Vasileios C.; Liampas, Sarantis-Aggelos G.; Doukas, Aristotelis-Kosmas G.

    2014-08-01

    In our time, the Geographic Information Systems (GIS) have become important tools, not only in the geosciences and environmental sciences, as well as virtually for all researches that require monitoring, planning or land management. The purpose of this paper was to develop a planning tool and decision making tool using AutoCAD Map software, ArcGIS and Google Earth with emphasis on the investigation of the suitability of forest roads' mapping and the range of its implementation in Greece in prefecture level. Integrating spatial information into a database makes data available throughout the organization; improving quality, productivity, and data management. Also working in such an environment, you can: Access and edit information, integrate and analyze data and communicate effectively. To select desirable information such as forest road network in a very early stage in the planning of silviculture operations, for example before the planning of the harvest is carried out. The software programs that were used were AutoCAD Map for the export in shape files for the GPS data, and ArcGIS in shape files (ArcGlobe), while Google Earth with KML files (Keyhole Markup Language) in order to better visualize and evaluate existing conditions, design in a real-world context and exchange information with government agencies, utilities, and contractors in both CAD and GIS data formats. The automation of the updating procedure and transfer of any files between agencies-departments is one of the main tasks of the integrated GIS-tool among the others should be addressed.

  8. EUFODOS: European Forest Downstream Services – Improved Information on Forest Structure and Damage

    Directory of Open Access Journals (Sweden)

    M. Hirschmugl

    2013-05-01

    Full Text Available Forests play a key role in the European economy and environment. This role incorporates ecological functions which can be affected by the occurrence of insect infestations, forest fire, heavy snowfall or windfall events. Local or Regional Authorities (LRAs thus require detailed information on the degradation status of their forests to be able to take appropriate measures for their forest management plans. In the EUFODOS project, state-of-the-art satellite and laser scanning technologies are used to provide forest authorities with cost-effective and comprehensive information on forest structure and damage. One of the six test sites is located in the Austrian province of Styria where regional forest authorities have expressed a strong need for detailed forest parameters in protective forest. As airborne laser-scanning data is available, it will be utilized to derive detailed forest parameters such as the upper forest border line, tree height, growth classes, forest density, vertical structure or volume. At the current project status, the results of (i the forest border line, (ii the segmentation of forest stands and (iii the tree top detection are available and presented including accuracy assessment and interim results are shown for timber volume estimations. The final results show that the forest border can be mapped operationally with an overall accuracy of almost 99% from LiDAR data. For the segmentation of forest stands, a comparison of the automatically derived result with visual-manual delineation showed in general a more detailed segmentation result, but for all visual-manual segments a congruence of 87% within a 4 m buffer. Tree top detections were compared to stem numbers estimated based on angle-count samplings in a field campaign, which led to a correlation coefficient (R of 0.79.

  9. Forest biomass carbon stocks and variation in Tibet’s carbon-dense forests from 2001 to 2050

    Science.gov (United States)

    Sun, Xiangyang; Wang, Genxu; Huang, Mei; Chang, Ruiying; Ran, Fei

    2016-01-01

    Tibet’s forests, in contrast to China’s other forests, are characterized by primary forests, high carbon (C) density and less anthropogenic disturbance, and they function as an important carbon pool in China. Using the biomass C density data from 413 forest inventory sites and a spatial forest age map, we developed an allometric equation for the forest biomass C density and forest age to assess the spatial biomass C stocks and variation in Tibet’s forests from 2001 to 2050. The results indicated that the forest biomass C stock would increase from 831.1 Tg C in 2001 to 969.4 Tg C in 2050, with a net C gain of 3.6 Tg C yr−1 between 2001 and 2010 and a decrease of 1.9 Tg C yr−1 between 2040 and 2050. Carbon tends to allocate more in the roots of fir forests and less in the roots of spruce and pine forests with increasing stand age. The increase of the biomass carbon pool does not promote significant augmentation of the soil carbon pool. Our findings suggest that Tibet’s mature forests will remain a persistent C sink until 2050. However, afforestation or reforestation, especially with the larger carbon sink potential forest types, such as fir and spruce, should be carried out to maintain the high C sink capacity. PMID:27703215

  10. Mapping resource use over a Russian landscape: an integrated look at harvesting of a non-timber forest product in central Kamchatka

    International Nuclear Information System (INIS)

    Hitztaler, Stephanie K; Bergen, Kathleen M

    2013-01-01

    Small-scale resource use became an important adaptive mechanism in remote logging communities in Russia at the onset of the post-Soviet period in 1991. We focused on harvesting of a non-timber forest product, lingonberry (Vaccinium vitis-idaea), in the forests of the Kamchatka Peninsula (Russian Far East). We employed an integrated geographical approach to make quantifiable connections between harvesting and the landscape, and to interpret these relationships in their broader contexts. Landsat TM images were used for a new classification; the resulting land-cover map was the basis for linking non-spatial data on harvesters’ gathering behaviors to spatial data within delineated lingonberry gathering sites. Several significant relationships emerged: (1) mature forests negatively affected harvesters’ initial choice to gather in a site, while young forests had a positive effect; (2) land-cover type was critical in determining how and why gathering occurred: post-disturbance young and maturing forests were significantly associated with higher gathering intensity and with the choice to market harvests; and (3) distance from gathering sites to villages and main roads also mattered: longer distances were significantly correlated to more time spent gathering and to increased marketing of harvests. We further considered our findings in light of the larger ecological and social dynamics at play in central Kamchatka. This unique study is an important starting point for conservation- and sustainable development-based work, and for additional research into the drivers of human–landscape interactions in the Russian Far East. (letter)

  11. Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps.

    Science.gov (United States)

    Kimball, J. S.; Keyser, A. R.; Running, S. W.; Saatchi, S. S.

    2000-06-01

    An ecological process model (BIOME-BGC) was used to assess boreal forest regional net primary production (NPP) and response to short-term, year-to-year weather fluctuations based on spatially explicit, land cover and biomass maps derived by radar remote sensing, as well as soil, terrain and daily weather information. Simulations were conducted at a 30-m spatial resolution, over a 1205 km(2) portion of the BOREAS Southern Study Area of central Saskatchewan, Canada, over a 3-year period (1994-1996). Simulations of NPP for the study region were spatially and temporally complex, averaging 2.2 (+/- 0.6), 1.8 (+/- 0.5) and 1.7 (+/- 0.5) Mg C ha(-1) year(-1) for 1994, 1995 and 1996, respectively. Spatial variability of NPP was strongly controlled by the amount of aboveground biomass, particularly photosynthetic leaf area, whereas biophysical differences between broadleaf deciduous and evergreen coniferous vegetation were of secondary importance. Simulations of NPP were strongly sensitive to year-to-year variations in seasonal weather patterns, which influenced the timing of spring thaw and deciduous bud-burst. Reductions in annual NPP of approximately 17 and 22% for 1995 and 1996, respectively, were attributed to 3- and 5-week delays in spring thaw relative to 1994. Boreal forest stands with greater proportions of deciduous vegetation were more sensitive to the timing of spring thaw than evergreen coniferous stands. Similar relationships were found by comparing simulated snow depth records with 10-year records of aboveground NPP measurements obtained from biomass harvest plots within the BOREAS region. These results highlight the importance of sub-grid scale land cover complexity in controlling boreal forest regional productivity, the dynamic response of the biome to short-term interannual climate variations, and the potential implications of climate change and other large-scale disturbances.

  12. Overview of National Thematic Data Integration (An Experience on One Map Mangrove Sulawesi)

    Science.gov (United States)

    Rudiastuti, A. W.; Yuwono, D. M.; Niendyawati; Pramono, G. H.; Rahmanto, B. D.

    2016-11-01

    Playing role as coastal shield with enormous economic value and ecological functions, mangrove forest management is always challenging to be studied. As either the largest archipelagic countryor the largest mangrove forest habitat around the globe, Indonesia needs a national mangrove forest baseline data and its updating for coastal management. Many stakeholders and institutions, including Geospatial Information Agency (BIG), had conducted mangrove mapping and updating. However, in order to achieve one mangrove national data, coordination and synergy among stakeholders and institutions such as: the Ministry of Environment and Forestry as mangrove custodian, Indonesian National Institute of Aeronautics and Space, Ministry of Marine and Fisheries, and BIG aligned with the National Mangrove Working Group is needed. A fundamental step for national mangrove forest management is the establishment of National One Map Mangrove Program by means of coordination, synchronization, and integration of mangrove geospatial data from various stakeholders. This paper will discuss the technical process of data integration and field survey in order to produce One Map Mangrove Sulawesi with the same geo-reference, database, and also standard and specification. The result of One Map Mangrove Sulawesi Program comprises of information about mangrove current status, existing area, and its distribution in Sulawesi.Beside the geospatial data from Ministry of Environment and Forestry and other institutions, the primary data used to map mangrove forest in Sulawesi is SPOT 6 and SPOT 7(year 2014 - 2015) imageries yielded map scale of 1: 25,000. On screen digitation using NIR, Red and Green bands and Normalized Difference Vegetation Index (NDVI)image transformation are applied for the initial canopy density classification. Field survey was doneto obtain field data forvegetation analysis, image classification andre-interpretation. In 2015, the process of producing One Map Mangrove Sulawesi has

  13. An application of remote sensing data in mapping landscape-level forest biomass for monitoring the effectiveness of forest policies in northeastern China.

    Science.gov (United States)

    Wang, Xinchuang; Shao, Guofan; Chen, Hua; Lewis, Bernard J; Qi, Guang; Yu, Dapao; Zhou, Li; Dai, Limin

    2013-09-01

    Monitoring the dynamics of forest biomass at various spatial scales is important for better understanding the terrestrial carbon cycle as well as improving the effectiveness of forest policies and forest management activities. In this article, field data and Landsat image data acquired in 1999 and 2007 were utilized to quantify spatiotemporal changes of forest biomass for Dongsheng Forestry Farm in Changbai Mountain region of northeastern China. We found that Landsat TM band 4 and Difference Vegetation Index with a 3 × 3 window size were the best predictors associated with forest biomass estimations in the study area. The inverse regression model with Landsat TM band 4 predictor was found to be the best model. The total forest biomass in the study area decreased slightly from 2.77 × 10(6) Mg in 1999 to 2.73 × 10(6) Mg in 2007, which agreed closely with field-based model estimates. The area of forested land increased from 17.9 × 10(3) ha in 1999 to 18.1 × 10(3) ha in 2007. The stabilization of forest biomass and the slight increase of forested land occurred in the period following implementations of national forest policies in China in 1999. The pattern of changes in both forest biomass and biomass density was altered due to different management regimes adopted in light of those policies. This study reveals the usefulness of the remote sensing-based approach for detecting and monitoring quantitative changes in forest biomass at a landscape scale.

  14. Dynamic analysis and pattern visualization of forest fires.

    Science.gov (United States)

    Lopes, António M; Tenreiro Machado, J A

    2014-01-01

    This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

  15. The Impact of Charcoal Production on Forest Degradation: a Case Study in Tete, Mozambique

    Science.gov (United States)

    Sedano, F.; Silva. J. A.; Machoco, R.; Meque, C. H.; Sitoe, A.; Ribeiro, N.; Anderson, K.; Ombe, Z. A.; Baule, S. H.; Tucker, C. J.

    2016-01-01

    Charcoal production for urban energy consumption is a main driver of forest degradation in sub-Saharan Africa. Urban growth projections for the continent suggest that the relevance of this process will increase in the coming decades. Forest degradation associated to charcoal production is difficult to monitor and commonly overlooked and underrepresented in forest cover change and carbon emission estimates. We use a multi-temporal dataset of very high-resolution remote sensing images to map kiln locations in a representative study area of tropical woodlands in central Mozambique. The resulting maps provided a characterization of the spatial extent and temporal dynamics of charcoal production. Using an indirect approach we combine kiln maps and field information on charcoal making to describe the magnitude and intensity of forest degradation linked to charcoal production, including aboveground biomass and carbon emissions. Our findings reveal that forest degradation associated to charcoal production in the study area is largely independent from deforestation driven by agricultural expansion and that its impact on forest cover change is in the same order of magnitude as deforestation. Our work illustrates the feasibility of using estimates of urban charcoal consumption to establish a link between urban energy demands and forest degradation. This kind of approach has potential to reduce uncertainties in forest cover change and carbon emission assessments in sub-Saharan Africa.

  16. The Habitat Susceptibility of Bali Starling (Leucopsar rothschildi Stresemann> 1912) Based on Forest Fire Vulnerability Mappin in West Bali National Park

    Science.gov (United States)

    Pramatana, F.; Prasetyo, L. B.; Rushayati, S. B.

    2017-10-01

    Bali starling is an endemic and endangered species which tend to decrease of its population in the wild. West Bali National Park (WBNP) is the only habitat of bali starling, however it is threatened nowadays by forest fire. Understanding the sensitivity of habitat to forest & land fire is urgently needed. Geographic Information System (GIS) can be used for mapping the vulnerability of forest fire. This study aims to analyze the contributed factor of forest fire, to develop vulnerability level map of forest fire in WBNP, to estimate habitat vulnerability of bali starling. The variable for mapping forest fire in WBNP were road distance, village distance, land cover, NDVI, NDMI, surface temperature, and slope. Forest fire map in WBNP was created by scoring from each variable, and classified into four classes of forest fire vulnerability which are very low (9 821 ha), low (5 015.718 ha), middle (6 778.656 ha), and high (2 126.006 ha). Bali starling existence in the middle and high vulnerability forest fire class in WBNP, consequently the population and habitat of bali starling is a very vulnerable. Management of population and habitat of bali starling in WBNP must be implemented focus on forest fire impact.

  17. Forest types of the "Argentino River Valley" Natural Reserve

    Directory of Open Access Journals (Sweden)

    Bagnato S

    2008-09-01

    Full Text Available Forest classification is a fundamental target for understanding forest stand dynamics and for sustainable management strategy applications. In this paper the methodological approach of forest types, already used in other Italians region, was applied for the classification of the RNO "Argentino River Valley" (southern Apennine, Italy. This study has been organized in 4 steps: 1 bibliographic analysis and collection of the acquired knowledge; 2 preliminary verification of forest types in the field; 3 description of the different units; 4 final validation of typological units. Using this approach we have characterized 9 categories and 12 forest types units. The description of each units has been filed as cards, where information of different nature is summarized and related to the organization of the typological units, to its location, to the description of the qualitative indicators (disturbances, cohort, mortality, natural dynamic tendencies, SDT, CWD etc. and quantitative indicators (dbh, average height, current annual increment, etc., to the functioning and the current management. For a better understanding of types functioning, "sylvology models" based on the "Spatial Pattern of Relative Collective Interaction" (PSICR and on the principal characteristics influencing and characterizing forest stand dynamics (availability of resources, type and frequency of disturbances, stand development, etc. have been singled out and proposed. The "forest types map" and other maps useful for the management of forest resources have been obtained. Moreover, data collected did allow to formulate several hypotheses on sustainable management.

  18. Regional forest cover estimation via remote sensing: the calibration center concept

    Science.gov (United States)

    Louis R. Iverson; Elizabeth A. Cook; Robin L. Graham; Robin L. Graham

    1994-01-01

    A method for combining Landsat Thematic Mapper (TM), Advanced Very High Resolution Radiometer (AVHRR) imagery, and other biogeographic data to estimate forest cover over large regions is applied and evaluated at two locations. In this method, TM data are used to classify a small area (calibration center) into forest/nonforest; the resulting forest cover map is then...

  19. Assessing forest degradation in Guyana with GeoEye, Quickbird and Landsat

    Science.gov (United States)

    Bobby Braswell; Steve Hagen; William Salas; Michael Palace; Sandra Brown; Felipe Casarim; Nancy Harris

    2013-01-01

    Forest degradation is defined as a change in forest quality and condition (e.g. reduction in biomass), while deforestation is a change in forest area. This pilot study evaluated several image processing approaches to map degradation and estimate carbon removals from logging. From the Joint Concept Note on REDD+ cooperation between Guyana and Norway carbon loss as...

  20. Considerations in Forest Growth Estimation Between Two Measurements of Mapped Forest Inventory Plots

    Science.gov (United States)

    Michael T. Thompson

    2006-01-01

    Several aspects of the enhanced Forest Inventory and Analysis (FIA) program?s national plot design complicate change estimation. The design incorporates up to three separate plot sizes (microplot, subplot, and macroplot) to sample trees of different sizes. Because multiple plot sizes are involved, change estimators designed for polyareal plot sampling, such as those...

  1. Effects of satellite image spatial aggregation and resolution on estimates of forest land area

    Science.gov (United States)

    M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer

    2009-01-01

    Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...

  2. Economic vulnerability of timber resources to forest fires.

    Science.gov (United States)

    y Silva, Francisco Rodríguez; Molina, Juan Ramón; González-Cabán, Armando; Machuca, Miguel Ángel Herrera

    2012-06-15

    The temporal-spatial planning of activities for a territorial fire management program requires knowing the value of forest ecosystems. In this paper we extend to and apply the economic valuation principle to the concept of economic vulnerability and present a methodology for the economic valuation of the forest production ecosystems. The forest vulnerability is analyzed from criteria intrinsically associated to the forest characterization, and to the potential behavior of surface fires. Integrating a mapping process of fire potential and analytical valuation algorithms facilitates the implementation of fire prevention planning. The availability of cartography of economic vulnerability of the forest ecosystems is fundamental for budget optimization, and to help in the decision making process. Published by Elsevier Ltd.

  3. Land cover change map comparisons using open source web mapping technologies

    Science.gov (United States)

    Erik Lindblom; Ian Housman; Tony Guay; Mark Finco; Kevin. Megown

    2015-01-01

    The USDA Forest Service is evaluating the status of current landscape change maps and assessing gaps in their information content. These activities have been occurring under the auspices of the Landscape Change Monitoring System (LCMS) project, which is a joint effort between USFS Research, USFS Remote Sensing Applications Center (RSAC), USGS Earth Resources...

  4. NASA LCLUC Program: An Integrated Forest Monitoring System for Central Africa

    Science.gov (United States)

    Laporte, Nadine; LeMoigne, Jacqueline; Elkan, Paul; Desmet, Olivier; Paget, Dominique; Pumptre, Andrew; Gouala, Patrice; Honzack, Miro; Maisels, Fiona

    2004-01-01

    Central Africa has the second largest unfragmented block of tropical rain forest in the world; it is also one of the largest carbon and biodiversity reservoirs. With nearly one-third of the forest currently allocated for logging, the region is poised to undergo extensive land-use change. Through the mapping of the forests, our Integrated Forest Monitoring System for Central Africa (INFORMS) project aims to monitor habitat alteration, support biodiversity conservation, and promote better land-use planning and forest management. Designed as an interdisciplinary project, its goal is to integrate data acquired from satellites with field observations from forest inventories, wildlife surveys, and socio-economic studies to map and monitor forest resources. This project also emphasizes on collaboration and coordination with international, regional, national, and local partners-including non-profit, governmental, and commercial sectors. This project has been focused on developing remote sensing products for the needs of forest conservation and management, insuring that research findings are incorporated in forest management plans at the national level. The societal impact of INFORMS can be also appreciated through the development of a regional remote sensing network in central Africa. With a regional office in Kinshasa, (www.OSFAC.org), the contribution to the development of forest management plans for 1.5 million hectares of forests in northern Republic of Congo (www.tt-timber.com), and the monitoring of park encroachments in the Albertine region (Uganda and DRC) (www.albertinerift.org).

  5. Forest biomass observation: current state and prospective

    Directory of Open Access Journals (Sweden)

    D. G. Schepaschenko

    2017-08-01

    Full Text Available With this article, we provide an overview of the methods, instruments and initiatives for forest biomass observation at global scale. We focus on the freely available information, provided by both remote and in-situ observations. The advantages and limitation of various space borne methods, including optical, radar (C, L and P band and LiDAR, as well as respective instruments available on the orbit (MODIS, Proba-V, Landsat, Sentinel-1, Sentinel-2 , ALOS PALSAR, Envisat ASAR or expecting (BIOMASS, GEDI, NISAR, SAOCOM-CS are discussed. We emphasize the role of in-situ methods in the development of a biomass models, providing calibration and validation of remote sensing data. We focus on freely available forest biomass maps, databases and empirical models. We describe the functionality of Biomass.Geo-Wiki.org portal, which provides access to a collection of global and regional biomass maps in full resolution with unified legend and units overplayed with high-resolution imagery. The Forest-Observation-System.net is announced as an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. Prospects of unmanned aerial vehicles in the forest inventory are briefly discussed. The work was partly supported by ESA IFBN project (contract 4000114425/15/NL/FF/gp.

  6. 36 CFR 9.42 - Well records and reports, plots and maps, samples, tests and surveys.

    Science.gov (United States)

    2010-07-01

    ... Well records and reports, plots and maps, samples, tests and surveys. Any technical data gathered... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Well records and reports, plots and maps, samples, tests and surveys. 9.42 Section 9.42 Parks, Forests, and Public Property...

  7. To Tree, or not to Tree: Sediment Storage in Forested and Non-forested Mountainous Hillslopes of the Bitterroot Mountains, MT

    Science.gov (United States)

    Quinn, C.; Dixon, J. L.; Wilcox, A. C.

    2017-12-01

    In steep, mountainous landscapes, interactions between soil, rock, and biotic factors combine to form complex feedbacks. Here, we explore the dynamic interplay between soil and vegetation and its influence on hillslope sediment storage and movement in the Bitterroot Range of Montana's Rocky Mountains. We focus on a set of analogous forested and non-forested hillslopes along Lost Horse Creek, where avalanche paths determine vegetative density without significant impact on other topographic variables. LiDAR, high-resolution aerial photography, and field mapping are used to determine the local and landscape variables that influence soil cover and sediment storage. We find high-resolution surface roughness is a useful remote proxy to identify bedrock and boulder outcrops, particularly beneath canopy cover. Based on this analysis and field mapping, the spatial extent of soil cover does not vary significantly between forested and non-forested regions, though soils are generally thicker under forest cover. We additionally measure fallout radiogenic nuclides (FRNs; Cs-137 and Pb-210) in soils across 40 sites to provide insight into short-term soil erosion and movement. Preliminary results show high spatial variability in FRN activities of mineral soils in both systems, which may reflect either spatially variable delivery or soil erosion. Additionally, FRN activity of surface litter and duff at the forest floor is three to four times higher than mineral soils in both the forested and non-forested sites, suggesting that FRNs may provide a novel tracer of carbon storage and export. Our results show that the coupled use of isotopic tracers and high resolution spatial data reveal quantitative insights into landscape scale hillslope soil dynamics.

  8. Mapping boreal forest biomass from a SRTM and TanDEM-X based on canopy height model and Landsat spectral indices

    Science.gov (United States)

    Sadeghi, Yaser; St-Onge, Benoît; Leblon, Brigitte; Prieur, Jean-François; Simard, Marc

    2018-06-01

    We propose a method for mapping above-ground biomass (AGB) (Mg ha-1) in boreal forests based predominantly on Landsat 8 images and on canopy height models (CHM) generated using interferometric synthetic aperture radar (InSAR) from the Shuttle Radar Topographic Mission (SRTM) and the TanDEM-X mission. The original SRTM digital elevation model (DEM) was corrected by modelling the respective effects of landform and land cover on its errors and then subtracted from a TanDEM-X DSM to produce a SAR CHM. Among all the landform factors, the terrain curvature had the largest effect on SRTM elevation errors, with a r2 of 0.29. The NDSI was the best predictor of the residual SRTM land cover error, with a r2 of 0.30. The final SAR CHM had a RMSE of 2.45 m, with a bias of 0.07 m, compared to a lidar-based CHM. An AGB prediction model was developed based on a combination of the SAR CHM, TanDEM-X coherence, Landsat 8 NDVI, and other vegetation indices of RVI, DVI, GRVI, EVI, LAI, GNDVI, SAVI, GVI, Brightness, Greenness, and Wetness. The best results were obtained using a Random forest regression algorithm, at the stand level, yielding a RMSE of 26 Mg ha-1 (34% of average biomass), with a r2 of 0.62. This method has the potential of creating spatially continuous biomass maps over entire biomes using only spaceborne sensors and requiring only low-intensity calibration.

  9. Using space-time features to improve detection of forest disturbances from Landsat time series

    NARCIS (Netherlands)

    Hamunyela, E.; Reiche, J.; Verbesselt, J.; Herold, M.

    2017-01-01

    Current research on forest change monitoring using medium spatial resolution Landsat satellite data aims for accurate and timely detection of forest disturbances. However, producing forest disturbance maps that have both high spatial and temporal accuracy is still challenging because of the

  10. Mapping snags and understory shrubs for LiDAR based assessment of wildlife habitat suitability

    Science.gov (United States)

    Sebastian Martinuzzi; Lee A. Vierling; William A. Gould; Michael J. Falkowski; Jeffrey S. Evans; Andrew T. Hudak; Kerri T. Vierling

    2009-01-01

    The lack of maps depicting forest three-dimensional structure, particularly as pertaining to snags and understory shrub species distribution, is a major limitation for managing wildlife habitat in forests. Developing new techniques to remotely map snags and understory shrubs is therefore an important need. To address this, we first evaluated the use of LiDAR data for...

  11. Global-Scale Patterns of Forest Fragmentation

    Directory of Open Access Journals (Sweden)

    Kurt Riitters

    2000-12-01

    Full Text Available We report an analysis of forest fragmentation based on 1-km resolution land-cover maps for the globe. Measurements in analysis windows from 81 km 2 (9 x 9 pixels, "small" scale to 59,049 km 2 (243 x 243 pixels, "large" scale were used to characterize the fragmentation around each forested pixel. We identified six categories of fragmentation (interior, perforated, edge, transitional, patch, and undetermined from the amount of forest and its occurrence as adjacent forest pixels. Interior forest exists only at relatively small scales; at larger scales, forests are dominated by edge and patch conditions. At the smallest scale, there were significant differences in fragmentation among continents; within continents, there were significant differences among individual forest types. Tropical rain forest fragmentation was most severe in North America and least severe in Europe-Asia. Forest types with a high percentage of perforated conditions were mainly in North America (five types and Europe-Asia (four types, in both temperate and subtropical regions. Transitional and patch conditions were most common in 11 forest types, of which only a few would be considered as "naturally patchy" (e.g., dry woodland. The five forest types with the highest percentage of interior conditions were in North America; in decreasing order, they were cool rain forest, coniferous, conifer boreal, cool mixed, and cool broadleaf.

  12. Global-scale patterns of forest fragmentation

    Science.gov (United States)

    Riitters, K.; Wickham, J.; O'Neill, R.; Jones, B.; Smith, E.

    2000-01-01

    We report an analysis of forest fragmentation based on 1-km resolution land-cover maps for the globe. Measurements in analysis windows from 81 km 2 (9 ?? 9 pixels, "small" scale) to 59,049 km 2 (243 ?? 243 pixels, "large" scale) were used to characterize the fragmentation around each forested pixel. We identified six categories of fragmentation (interior, perforated, edge, transitional, patch, and undetermined) from the amount of forest and its occurrence as adjacent forest pixels. Interior forest exists only at relatively small scales; at larger scales, forests are dominated by edge and patch conditions. At the smallest scale, there were significant differences in fragmentation among continents; within continents, there were significant differences among individual forest types. Tropical rain forest fragmentation was most severe in North America and least severe in Europe - Asia. Forest types with a high percentage of perforated conditions were mainly in North America (five types) and Europe - Asia (four types), in both temperate and subtropical regions. Transitional and patch conditions were most common in 11 forest types, of which only a few would be considered as "naturally patchy" (e.g., dry woodland). The five forest types with the highest percentage of interior conditions were in North America; in decreasing order, they were cool rain forest, coniferous, conifer boreal, cool mixed, and cool broadleaf. Copyright ?? 2000 by The Resilience Alliance.

  13. A synoptic climatology for forest fires in the NE US and future implications for GCM simulations

    Science.gov (United States)

    Yan Qing; Ronald Sabo; Yiqiang Wu; J.Y. Zhu

    1994-01-01

    We studied surface-pressure patterns corresponding to reduced precipitation, high evaporation potential, and enhanced forest-fire danger for West Virginia, which experienced extensive forest-fire damage in November 1987. From five years of daily weather maps we identified eight weather patterns that describe distinctive flow situations throughout the year. Map patterns...

  14. Application of Modis Data to Assess the Latest Forest Cover Changes of Sri Lanka

    Science.gov (United States)

    Perera, K.; Herath, S.; Apan, A.; Tateishi, R.

    2012-07-01

    Assessing forest cover of Sri Lanka is becoming important to lower the pressure on forest lands as well as man-elephant conflicts. Furthermore, the land access to north-east Sri Lanka after the end of 30 years long civil war has increased the need of regularly updated land cover information for proper planning. This study produced an assessment of the forest cover of Sri Lanka using two satellite data based maps within 23 years of time span. For the old forest cover map, the study used one of the first island-wide digital land cover classification produced by the main author in 1988. The old land cover classification was produced at 80 m spatial resolution, using Landsat MSS data. A previously published another study by the author has investigated the application feasibility of MODIS and Landsat MSS imagery for a selected sub-section of Sri Lanka to identify the forest cover changes. Through the light of these two studies, the assessment was conducted to investigate the application possibility of MODIS 250 m over a small island like Sri Lanka. The relation between the definition of forest in the study and spatial resolution of the used satellite data sets were considered since the 2012 map was based on MODIS data. The forest cover map of 1988 was interpolated into 250 m spatial resolution to integrate with the GIS data base. The results demonstrated the advantages as well as disadvantages of MODIS data in a study at this scale. The successful monitoring of forest is largely depending on the possibility to update the field conditions at regular basis. Freely available MODIS data provides a very valuable set of information of relatively large green patches on the ground at relatively real-time basis. Based on the changes of forest cover from 1988 to 2012, the study recommends the use of MODIS data as a resalable method to forest assessment and to identify hotspots to be re-investigated. It's noteworthy to mention the possibility of uncounted small isolated pockets of

  15. Remote sensing for conservation of tropical moist forests: A study in Indonesia

    Science.gov (United States)

    Warwick-Smith, Robert Myles

    The Indonesian archipelago extends in a great 6000km arc from the northern tip of Sumatra to the eastern border of Irian Jaya. It includes a wide diversity of ecosystems ranging from the floristically rich and economically important lowland tropical rain forests to the 'moss' and sub-alpine meadows of the higher mountains and from fresh-water swamp forest to the dry monsoon forest and savanna woodlands of the lesser Sunda islands. These forests are of importance for the protection of watersheds and catchment areas, for the maintenance of water supplies, and for their general and local influence upon climate. They are the habitat of a large number of rare, endangered and endemic plant and animal species; also many other birds, mammals, reptiles and insects which form a colourful, scientifically valuable and irreplaceable part of the national heritage and world genetic resources. This study examines an area of great ecological importance in Sulawesi, and an attempt is made to map a number of ecosystems in the area. Landsat multispectral imagery (1972) was the basis of the mapping and field work was completed in 1980. The satellite imagery proved to be a satisfactory mapping tool in these tropical moist forest conditions.

  16. Computer-aided classification of forest cover types from small scale aerial photography

    Science.gov (United States)

    Bliss, John C.; Bonnicksen, Thomas M.; Mace, Thomas H.

    1980-11-01

    The US National Park Service must map forest cover types over extensive areas in order to fulfill its goal of maintaining or reconstructing presettlement vegetation within national parks and monuments. Furthermore, such cover type maps must be updated on a regular basis to document vegetation changes. Computer-aided classification of small scale aerial photography is a promising technique for generating forest cover type maps efficiently and inexpensively. In this study, seven cover types were classified with an overall accuracy of 62 percent from a reproduction of a 1∶120,000 color infrared transparency of a conifer-hardwood forest. The results were encouraging, given the degraded quality of the photograph and the fact that features were not centered, as well as the lack of information on lens vignetting characteristics to make corrections. Suggestions are made for resolving these problems in future research and applications. In addition, it is hypothesized that the overall accuracy is artificially low because the computer-aided classification more accurately portrayed the intermixing of cover types than the hand-drawn maps to which it was compared.

  17. Use of a forest sapwood area index to explain long-term variability in mean annual evapotranspiration and streamflow in moist eucalypt forests

    Science.gov (United States)

    Benyon, Richard G.; Lane, Patrick N. J.; Jaskierniak, Dominik; Kuczera, George; Haydon, Shane R.

    2015-07-01

    Mean sapwood thickness, measured in fifteen 73 year old Eucalyptus regnans and E. delegatensis stands, correlated strongly with forest overstorey stocking density (R2 0.72). This curvilinear relationship was used with routine forest stocking density and basal area measurements to estimate sapwood area of the forest overstorey at various times in 15 research catchments in undisturbed and disturbed forests located in the Great Dividing Range, Victoria, Australia. Up to 45 years of annual precipitation and streamflow data available from the 15 catchments were used to examine relationships between mean annual loss (evapotranspiration estimated as mean annual precipitation minus mean annual streamflow), and sapwood area. Catchment mean sapwood area correlated strongly (R2 0.88) with catchment mean annual loss. Variation in sapwood area accounted for 68% more variation in mean annual streamflow than precipitation alone (R2 0.90 compared with R2 0.22). Changes in sapwood area accounted for 96% of the changes in mean annual loss observed after forest thinning or clear-cutting and regeneration. We conclude that forest inventory data can be used reliably to predict spatial and temporal variation in catchment annual losses and streamflow in response to natural and imposed disturbances in even-aged forests. Consequently, recent advances in mapping of sapwood area using airborne light detection and ranging will enable high resolution spatial and temporal mapping of mean annual loss and mean annual streamflow over large areas of forested catchment. This will be particularly beneficial in management of water resources from forested catchments subject to disturbance but lacking reliable long-term (years to decades) streamflow records.

  18. Application of geoinformatics for landscape assessment and conserving forest biodiversity in northeast India

    Science.gov (United States)

    Ashish Kumar; Bruce G. Marcot; Gautam Talukdar; P.S. Roy

    2012-01-01

    Herein, we summarize our work, within forest ecosystems of Garo Hills in northeast India, on mapping vegetation and land cover conditions, delineating wildlife habitat corridors among protected areas, evaluating forest conservation values of influence zones bordering protected areas, analyzing dispersion patterns of native forests, and determining potential effects of...

  19. FOREST DISTRIBUTION ON THE CENTRAL RUSSIAN UPLAND: HISTORICAL PERSPECTIVE

    Directory of Open Access Journals (Sweden)

    Maria V. Arkhipova

    2014-01-01

    Full Text Available We studied the change of forestland in the Central Russian Upland within the deciduous forest, forest-steppe, and steppe zones using old maps (XVIII-XX cc. and current satellite images. The forest distribution within the Central Russian Upland has been relatively stable during the last 220 years. On average, the decrease in the forested area was small. However, we identified significant changes in certain regions. In the southern part of CRU, the significant increase of the forested land is caused by the forest protection of abatis woodland and afforestation. During the last 100 years, reforestation took place mainly in the Oka basin due to both afforestation and natural reforestation. New forests appeared generally in ravines within all zones. The analysis of the abatis forests changes from the XVIII to XX cc. allowed us to identify forested area within the Central Russian Upland prior to active development.

  20. Changes in forest cover in the Foresta della Lama (Casentino Forests National Park from Karl Siemon’s and Anton Seeland’s 1837 forest management plan

    Directory of Open Access Journals (Sweden)

    Vazzano E

    2011-05-01

    Full Text Available Forest estates with a long history of forest management plans are quite rare in Italy. In such cases, the analysis of historical documents combined with the use of GIS technology, can provide useful information on the evolution of forest cover and silvicultural and management techniques. Based on two unpublished documents by Karl Siemon and Anton Seeland dating back to 1837 and 1850, an archive of historical maps for the Lama Forest (Foreste Casentinesi, Monte Falterona and Campigna National Park was created using GIS techniques. This archive outlines the evolution of the Lama Forest over the last 170 years. Particular attention was given to silver fir plantations, which have strongly characterized silviculture and local economics in the Foreste Casentinesi area. The results of our analysis show that changes in different historical periods have been caused both by silvicultural interventions prescribed by the management plans and by external causes such as changes in forest property or war periods, which have markedly influenced forest area and stand characteristics. Furthermore, our analysis confirms that the work of Karl Siemon and Anton Seeland, carried out between 1835 and 1837, is the oldest forest management plan for an Italian forest. It is interesting to note that the aim of the plan, i.e., a regulated (or “normal” even-aged forest, and the way the plan was laid out, typical of classic forest management originated in Germany at the end of the XVIIIth century, served as model for the forest management plans drawn out by the Florence Forestry School almost until the end of the XXth century.

  1. EnviroAtlas - Paterson, NJ - 51m Riparian Buffer Forest Cover

    Science.gov (United States)

    This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is forested. There is a potential for decreased water quality in areas where the riparian buffer is less forested. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. EnviroAtlas defines tree buffer for this community as only trees and forest. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  2. EVALUATING THE POTENTIAL OF SATELLITE HYPERSPECTRAL RESURS-P DATA FOR FOREST SPECIES CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    O. Brovkina

    2016-06-01

    Full Text Available Satellite-based hyperspectral sensors provide spectroscopic information in relatively narrow contiguous spectral bands over a large area which can be useful in forestry applications. This study evaluates the potential of satellite hyperspectral Resurs-P data for forest species mapping. Firstly, a comparative study between top of canopy reflectance obtained from the Resurs-P, from the airborne hyperspectral scanner CASI and from field measurement (FieldSpec ASD 4 on selected vegetation cover types is conducted. Secondly, Resurs-P data is tested in classification and verification of different forest species compartments. The results demonstrate that satellite hyperspectral Resurs-P sensor can produce useful informational and show good performance for forest species classification comparable both with forestry map and classification from airborne CASI data, but also indicate that developments in pre-processing steps are still required to improve the mapping level.

  3. Diversity of MAPs in some plant communities of Stara Planina

    Directory of Open Access Journals (Sweden)

    Obratov-Petković Dragica

    2006-01-01

    Full Text Available The high floristic diversity of Stara Planina was the starting base for the research of medicinal and aromatic plants (MAPs in individual forest and meadow communities. The sites Javor and Prelesje, forest community Fagetum moesiacae montanum B. Jov. 1953, pioneer community of birch Betuletum verrucosae s.l. and meadow community Agrostietum vulgaris (capillaris Pavlović, Z. 1955, were researched as follows: soil types, floristic composition and structure of the community, percentage of MAPs, as well as the selection of species which, according to the predetermined criteria can be recommended for further exploitation. The study shows that the soil of the forest communities is eutric brown, and meadow soils are dystric and eutric humus-siliceous. The percentage of MAPs in the floristic structure of the study sites in forest and meadow communities is 32.35%. The following species can be recommended for the collection and utilisation: Hypericum perforatum L., Asperula odorata L., Dryopteris filix-mas (L Schott. Urtica dioica L., Euphorbia amygdaloides L., Prunella grandiflora L. Tanacetum vulgare L., Achillea millefolium L., Rumex acetosa L., Campanula glomerata L., Stachys officinalis (L Trevis., Plantago lanceolata W. et K., Potentilla erecta (L Rauchel, Chamaespartium sagittale (L P. Gibbs. Cynanchum vincetoxicum (L Pers., Euphrasia stricta Host., Fagus moesiaca (Matt Liebl. and Fragaria vesca L.

  4. Mapping of land cover in Northern California with simulated HyspIRI images

    Science.gov (United States)

    Clark, M. L.; Kilham, N. E.

    2014-12-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (i.e., full range) of the spectrum have shown improved capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a full-range hyperspectral and thermal satellite being considered for development by NASA (hyspiri.jpl.nasa.gov). A hyperspectral satellite, such as HyspIRI, will provide detailed spectral and temporal information at global scales that could greatly improve our ability to map land cover with greater class detail and spatial and temporal accuracy than possible with conventional multispectral satellites. The broad goal of our research is to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping across a range of environmental and anthropogenic gradients in California. In this study, we mapped FAO Land Cover Classification System (LCCS) classes over 30,000 km2 in Northern California using multi-temporal HyspIRI imagery simulated from the AVIRIS airborne sensor. The Random Forests classification was applied to predictor variables derived from the multi-temporal hyperspectral data and accuracies were compared to that from Landsat 8 OLI. Results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different forest life-form types, such as mixed conifer and broadleaf forests and open- and closed-canopy forests.

  5. EnviroAtlas - Minneapolis/St. Paul, MN - 51m Riparian Buffer Forest Cover

    Science.gov (United States)

    This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is forested. In this community, forest is defined as Trees and Forest and Woody Wetlands. There is a potential for decreased water quality in areas where the riparian buffer is less forested. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  6. Mapping urban forest structure and function using hyperspectral imagery and lidar data

    Science.gov (United States)

    Michael Alonzo; Joseph P. McFadden; David J. Nowak; Dar A. Roberts

    2016-01-01

    Cities measure the structure and function of their urban forest resource to optimize forest managementand the provision of ecosystem services. Measurements made using plot sampling methods yield useful results including citywide or land-use level estimates of species counts, leaf area, biomass, and air pollution reduction. However, these quantities are statistical...

  7. Evaluation of alternative approaches for landscape-scale biomass estimation in a mixed-species northern forest

    Science.gov (United States)

    Coeli M. Hoover; Mark J. Ducey; R. Andy Colter; Mariko Yamasaki

    2018-01-01

    There is growing interest in estimating and mapping biomass and carbon content of forests across large landscapes. LiDAR-based inventory methods are increasingly common and have been successfully implemented in multiple forest types. Asner et al. (2011) developed a simple universal forest carbon estimation method for tropical forests that reduces the amount of required...

  8. Importance of bistatic SAR features from TanDEM-X for forest mapping and monitoring

    NARCIS (Netherlands)

    Schlund, M.; Poncet, von F.; Hoekman, D.H.; Kuntz, S.; Schmullius, C.

    2014-01-01

    Deforestation and forest degradation are one of the important sources for human induced carbon dioxide emissions and their rates are highest in tropical forests. For man-kind, it is of great importance to track land-use conversions like deforestation, e.g. for sustainable forest management and land

  9. AUTOMATED MAPPING OF PERMANENT PRESERVATION AREAS ON HILLTOPS

    Directory of Open Access Journals (Sweden)

    Guilherme de Castro Oliveira

    2016-03-01

    Full Text Available Permanent Preservation Areas (PPAs on hilltops are among the many areas protected by the New Forest Code in Brazil. Mapping of these involves difficult interpretation and application of the Law, as well a complex task of translating it in map algebra. This paper aims to present, in detail, a methodological model for delimitation of PPAs on hilltops, according to the Brazilian new Forest Code (NFC, Law 12,651/2012. The model was developed in Model Builder for ArcGIS 10.2, and is able to map the PPAs in any digital terrain model. However, field validations are required to verify its efficiency. There is need for legal standardization of criteria that may cause subjectivity in delimitation. The organization of these data on a large scale is very important, as example, to the Rural Environmental Registry, which provides georeferencing of all rural properties and its protected areas in Brazil.

  10. Forecasting forest development through modeling based on the legacy of forest structure over the past 43 years

    Energy Technology Data Exchange (ETDEWEB)

    Baskent, E. Z.; Celik, D. A.

    2013-09-01

    Aim of study: Sustainable management of forest ecosystems requires comprehensive coverage of data to reflect both the historical legacy and the future development of forests. This study focuses on analyzing the spatio-temporal dynamics of forests over the past 43 years to help better forecast the future development of forest under various management strategies. Area of study: The area is situated in Karaisalt district of Adana city in the southeastern corner of Turkey. Material and methods: The historical pattern from 1969 to 2012 was assessed with digital forest cover type maps, produced with high resolution aerial photo interpretation using Geographic Information Systems (GIS). The forest development over the next 120 years was forecasted using ecosystem-based multiple use forest management model (ETCAP) to understand the cause-effect relationships under various management strategies. Main results: The result showed that over the past 43 years while total forest areas decreased about 1,194 ha (4%), the productive forest areas increased about 5,397 ha (18%) with a decrease of degraded forest (5,824 ha, 20%) and increase of maquis areas (2,212 ha, 7%).The forecast of forest development under traditional management strategy resulted in an unsustainable forest due to broken initial age class structure, yet generated more total harvest (11%) due to 88% relaxing of even timber flow constraint. While more volume could be harvested under traditional management conditions, the sustainability of future forest is significantly jeopardized. Research highlights: This result trongly implies that it is essential adopting modeling techniques to understand forest dynamics and forecast the future development comprehensively. (Author)

  11. Mapping Brazilian Cropland Expansion, 2000-2013

    Science.gov (United States)

    Zalles, V.; Hansen, M.; Potapov, P.

    2016-12-01

    Brazil is one of the world's leading producers and exporters of agricultural goods. Despite undergoing significant increases in its cropland area in the last decades, it remains one of the countries with the most potential for further agricultural expansion. Most notably, the expansion in production areas of commodity crops such as soybean, corn, and sugarcane has become the leading cause of land cover conversion in Brazil. Natural land covers, such as the Amazon and Cerrado forests, have been negatively affected by this agricultural expansion, causing carbon emissions, biodiversity loss, altered water cycles, and many other disturbances to ecosystem services. Monitoring of change in cropland area extent can provide relevant information to decision makers seeking to understand and manage land cover change drivers and their impacts. In this study, the freely-available Landsat archive was leveraged to produce a large-scale, methodologically consistent map of cropland cover at 30 m. resolution for the entire Brazilian territory in the year 2000. Additionally, we mapped cropland expansion from 2000 to 2013, and used statistical sampling techniques to accurately estimate cropland area per Brazilian state. Using the Global Forest Change product produced by Hansen et al. (2013), we can disaggregate forest cover loss due to cropland expansion by year, revealing spatiotemporal trends that could advance our understanding of the drivers of forest loss.

  12. A Comparison of Novel Optical Remote Sensing-Based Technologies for Forest-Cover/Change Monitoring

    Directory of Open Access Journals (Sweden)

    Gillian V. Lui

    2015-03-01

    Full Text Available Remote sensing is gaining considerable traction in forest monitoring efforts, with the Carnegie Landsat Analysis System lite (CLASlite software package and the Global Forest Change dataset (GFCD being two of the most recently developed optical remote sensing-based tools for analysing forest cover and change. Due to the relatively nascent state of these technologies, their abilities to classify land cover and monitor forest dynamics have yet to be evaluated against more established approaches. Here, we compared maps of forest cover and change produced by the more traditional supervised classification approach with those produced by CLASlite and the GFCD, working with imagery collected over Sierra Leone, West Africa. CLASlite maps of forest change from 2001–2007 and 2007–2014 exhibited the highest overall accuracies (79.1% and 89.6%, respectively and, importantly, the greatest capacity to discriminate natural from planted mature forest growth. CLASlite’s comparative advantage likely derived from its more robust sub-pixel classification logic and numerous user-defined parameters, which resulted in classified products with greater site relevance than those of the two other classification approaches. In light of today’s continuously growing body of analytical toolsets for remotely sensed data, our study importantly elucidates the ways in which methodological processes and limitations inherent in certain classification tools can impact the maps they are capable of producing, and demonstrates the need to understand and weigh such factors before any one tool is selected for a given application.

  13. An Approach for Foliar Trait Retrieval from Airborne Imaging Spectroscopy of Tropical Forests

    Directory of Open Access Journals (Sweden)

    Roberta E. Martin

    2018-01-01

    Full Text Available Spatial information on forest functional composition is needed to inform management and conservation efforts, yet this information is lacking, particularly in tropical regions. Canopy foliar traits underpin the functional biodiversity of forests, and have been shown to be remotely measurable using airborne 350–2510 nm imaging spectrometers. We used newly acquired imaging spectroscopy data constrained with concurrent light detection and ranging (LiDAR measurements from the Carnegie Airborne Observatory (CAO, and field measurements, to test the performance of the Spectranomics approach for foliar trait retrieval. The method was previously developed in Neotropical forests, and was tested here in the humid tropical forests of Malaysian Borneo. Multiple foliar chemical traits, as well as leaf mass per area (LMA, were estimated with demonstrable precision and accuracy. The results were similar to those observed for Neotropical forests, suggesting a more general use of the Spectranomics approach for mapping canopy traits in tropical forests. Future mapping studies using this approach can advance scientific investigations and applications based on imaging spectroscopy.

  14. The Potential of EnMAP and Sentinel-2 Data for Detecting Drought Stress Phenomena in Deciduous Forest Communities

    Directory of Open Access Journals (Sweden)

    Sandra Dotzler

    2015-10-01

    Full Text Available Given the importance of forest ecosystems, the availability of reliable, spatially explicit information about the site-specific climate sensitivity of tree species is essential for implementing suitable adaptation strategies. In this study, airborne hyperspectral data were used to assess the response of deciduous species (dominated by European beech and Sessile and Pedunculate oak to water stress during a summery dry spell. After masking canopy gaps, shaded crown areas and non-deciduous species, potentially indicative spectral indices, the Photochemical Reflectance Index (PRI, Moisture Stress Index (MSI, Normalized Difference Water Index (NDWI, and Chlorophyll Index (CI, were analyzed with respect to available maps of site-specific soil moisture regimes. PRI provided an important indication of site-specific photosynthetic stress on leaf level in relation to limitations in soil water availability. The CI, MSI and NDWI revealed statistically significant differences in total chlorophyll and water concentration at the canopy level. However, after reducing the canopy effects by normalizing these indices with respect to the structure-sensitive simple ratio (SR vegetation index, it was not yet possible to identify site-specific concentration differences in leaf level at this early stage of the drought. The selected indicators were also tested with simulated EnMAP and Sentinel-2 data (derived from the original airborne data set. While PRI proved to be useful also in the spatial resolution of EnMAP (GSD = 30 m, this was not the case with Sentinel-2, owing to the lack of adequate spectral bands; the remaining indicators (MSI, CI, SR were also successfully produced with Sentinel-2 data at superior spatial resolution (GSD = 10 m. The study confirms the importance of using earth observation systems for supplementing traditional ecological site classification maps, particularly during dry spells and heat waves when ecological gradients are increasingly

  15. Forecasting forest development through modeling based on the legacy of forest structure over the past 43 years

    Directory of Open Access Journals (Sweden)

    E.Z. Baskent

    2013-07-01

    Full Text Available Aim of study: Sustainable management of forest ecosystems requires comprehensive coverage of data to reflect both the historical legacy and the future development of forests.  This study focuses on analyzing the spatio-temporal dynamics of forests over the past 43 years to help better forecast the future development of forest under various management strategies.Area of study: The area is situated in Karaisalı district of Adana city in the southeastern corner of Turkey.Material and methods: The historical pattern from 1969 to 2012 was assessed with digital forest cover type maps, produced with high resolution aerial photo interpretation using Geographic Information Systems (GIS. The forest development over the next 120 years was forecasted using ecosystem-based multiple use forest management model (ETÇAP to understand the cause-effect relationships under various management strategies.Main results: The result showed that over the past 43 years while total forest areas decreased about 1194 ha (4%, the productive forest areas increased about 5397 ha (18% with a decrease of degraded forest (5824 ha, 20% and increase of maquis areas (2212 ha, 7%.The forecast of forest development under traditional management strategy resulted in an unsustainable forest due to broken initial age class structure, yet generated more total harvest (11% due to 88% relaxing of even timber flow constraint. While more volume could be harvested under traditional management conditions, the sustainability of future forest is significantly jeopardized.Research highlights: This result trongly implies that it is essential adopting modeling techniques to understand forest dynamics and forecast the future development comprehensively.Keywords: Forest management; simulation; optimization; forest dynamics; land use change.

  16. Forest operations planning by using RTK-GPS based digital elevation model

    Directory of Open Access Journals (Sweden)

    Neşe Gülci

    2015-07-01

    Full Text Available Having large proportion of forests in mountainous terrain in Turkey, the logging methods that not only minimize operational costs but also minimize environmental damages should be determined in forest operations planning. In a case where necessary logging equipment and machines are available, ground slope is the most important factor in determining the logging method. For this reason, accurate, up to date, and precise ground slope data is very crucial in the success of forest operations planning. In recent years, high-resolution Digital Elevation Models (DEM can be generated for forested areas by using Real Time Kinematic (RTK GPS method and these DEMs can be used to develop precise slope maps. In this study, high-resolution DEM was developed by RTK-GPS method to generate precise slope map in a sample area. Then, the slope map was classified into slope classes specified by IUFRO in order to assist forest operations planning. According to the results, logging methods that are suitable for very steep and steep terrain conditions (i.e. skyline logging, cable pulling, and chute systems should be preferred in 48.1% of the study area. It was also found that logging methods that are suitable for terrain with medium slope (i.e. skidding and cable pulling and gentle slope (i.e. skidding and mobile winch should be preferred in 34.1% and 17.8% of the study area, respectively.

  17. Remotely sensed forest cover loss shows high spatial and temporal variation across Sumatera and Kalimantan, Indonesia 2000-2008

    International Nuclear Information System (INIS)

    Broich, Mark; Hansen, Matthew; Potapov, Peter; Margono, Belinda Arunarwati; Adusei, Bernard; Stolle, Fred

    2011-01-01

    The Indonesian islands of Sumatera and Kalimantan (the Indonesian part of the island of Borneo) are a center of significant and rapid forest cover loss in the humid tropics with implications for carbon dynamics, biodiversity conservation, and local livelihoods. The aim of our research was to analyze and interpret annual trends of forest cover loss for different sub-regions of the study area. We mapped forest cover loss for 2000-2008 using multi-resolution remote sensing data from the Landsat enhanced thematic mapper plus (ETM +) and moderate resolution imaging spectroradiometer (MODIS) sensors and analyzed annual trends per island, province, and official land allocation zone. The total forest cover loss for Sumatera and Kalimantan 2000-2008 was 5.39 Mha, which represents 5.3% of the land area and 9.2% of the year 2000 forest cover of these two islands. At least 6.5% of all mapped forest cover loss occurred in land allocation zones prohibiting clearing. An additional 13.6% of forest cover loss occurred where clearing is legally restricted. The overall trend of forest cover loss increased until 2006 and decreased thereafter. The trends for Sumatera and Kalimantan were distinctly different, driven primarily by the trends of Riau and Central Kalimantan provinces, respectively. This analysis shows that annual mapping of forest cover change yields a clearer picture than a one-time overall national estimate. Monitoring forest dynamics is important for national policy makers, especially given the commitment of Indonesia to reducing greenhouse gas emissions as part of the reducing emissions from deforestation and forest degradation in developing countries initiative (REDD +). The improved spatio-temporal detail of forest change monitoring products will make it possible to target policies and projects in meeting this commitment. Accurate, annual forest cover loss maps will be integral to many REDD + objectives, including policy formulation, definition of baselines, detection

  18. Mapping the spatial pattern of temperate forest above ground biomass by integrating airborne lidar with Radarsat-2 imagery via geostatistical models

    Science.gov (United States)

    Li, Wang; Niu, Zheng; Gao, Shuai; Wang, Cheng

    2014-11-01

    Light Detection and Ranging (LiDAR) and Synthetic Aperture Radar (SAR) are two competitive active remote sensing techniques in forest above ground biomass estimation, which is important for forest management and global climate change study. This study aims to further explore their capabilities in temperate forest above ground biomass (AGB) estimation by emphasizing the spatial auto-correlation of variables obtained from these two remote sensing tools, which is a usually overlooked aspect in remote sensing applications to vegetation studies. Remote sensing variables including airborne LiDAR metrics, backscattering coefficient for different SAR polarizations and their ratio variables for Radarsat-2 imagery were calculated. First, simple linear regression models (SLR) was established between the field-estimated above ground biomass and the remote sensing variables. Pearson's correlation coefficient (R2) was used to find which LiDAR metric showed the most significant correlation with the regression residuals and could be selected as co-variable in regression co-kriging (RCoKrig). Second, regression co-kriging was conducted by choosing the regression residuals as dependent variable and the LiDAR metric (Hmean) with highest R2 as co-variable. Third, above ground biomass over the study area was estimated using SLR model and RCoKrig model, respectively. The results for these two models were validated using the same ground points. Results showed that both of these two methods achieved satisfactory prediction accuracy, while regression co-kriging showed the lower estimation error. It is proved that regression co-kriging model is feasible and effective in mapping the spatial pattern of AGB in the temperate forest using Radarsat-2 data calibrated by airborne LiDAR metrics.

  19. Mapping deforestation and forest degradation using Landsat time series: a case of Sumatra—Indonesia

    Science.gov (United States)

    Belinda Arunarwati Margono

    2013-01-01

    Indonesia experiences the second highest rate of deforestation among tropical countries (FAO 2005, 2010). Consequently, timely and accurate forest data are required to combat deforestation and forest degradation in support of climate change mitigation and biodiversity conservation policy initiatives. Remote sensing is considered as a significant data source for forest...

  20. The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area

    Science.gov (United States)

    Ronald E. McRoberts

    2010-01-01

    Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing...

  1. Monetary Valuation of Natural Forest Habitats in Protected Areas

    Czech Academy of Sciences Publication Activity Database

    Pechanec, V.; Machar, I.; Štěrbová, Lenka; Prokopová, Marcela; Kilianová, H.; Chobot, K.; Cudlín, Pavel

    2017-01-01

    Roč. 8, č. 11 (2017), č. článku 427. ISSN 1999-4907 Institutional support: RVO:86652079 Keywords : mapping ecosystem services * environmental services * biodiversity conservation * ecological resilience * valuing biodiversity * floodplain forests * economic valuation * cost-effectiveness * management * payments * monetary value of forest biodiversity * Natura 2000 * special area of conservation Subject RIV: GK - Forestry OBOR OECD: Forestry Impact factor: 1.951, year: 2016

  2. Forest cover of Champaign County, Illinois in 1993

    Science.gov (United States)

    Jesus Danilo Chinea; Louis R. Iverson

    1997-01-01

    The forest cover of Champaign County, in east-central Illinois, was mapped from 1993 aerial photography and entered in a geographical information system database. One hundred and six forest patches cover 3,380 ha. These patches have a mean area of 32 ha, a mean perimeter of 4,851 m, a mean perimeter to area ratio of 237, a fractal dimension of 1.59, and a mean nearest...

  3. ROE Carbon Storage - Forest Biomass

    Science.gov (United States)

    This polygon dataset depicts the density of forest biomass in counties across the United States, in terms of metric tons of carbon per square mile of land area. These data were provided in spreadsheet form by the U.S. Department of Agriculture (USDA) Forest Service. To produce the Web mapping application, EPA joined the spreadsheet with a shapefile of U.S. county (and county equivalent) boundaries downloaded from the U.S. Census Bureau. EPA calculated biomass density based on the area of each county polygon. These data sets were converted into a single polygon feature class inside a file geodatabase.

  4. Using Landsat time series for characterizing forest disturbance dynamics in the coupled human and natural systems of Central Europe.

    Science.gov (United States)

    Senf, Cornelius; Pflugmacher, Dirk; Hostert, Patrick; Seidl, Rupert

    2017-08-01

    Remote sensing is a key information source for improving the spatiotemporal understanding of forest ecosystem dynamics. Yet, the mapping and attribution of forest change remains challenging, particularly in areas where a number of interacting disturbance agents simultaneously affect forest development. The forest ecosystems of Central Europe are coupled human and natural systems, with natural and human disturbances affecting forests both individually and in combination. To better understand the complex forest disturbance dynamics in such systems, we utilize 32-year Landsat time series to map forest disturbances in five sites across Austria, the Czech Republic, Germany, Poland, and Slovakia. All sites consisted of a National Park and the surrounding forests, reflecting three management zones of different levels of human influence (managed, protected, strictly protected). This allowed for a comparison of spectral, temporal, and spatial disturbance patterns across a gradient from natural to coupled human and natural disturbances. Disturbance maps achieved overall accuracies ranging from 81% to 93%. Disturbance patches were generally small, with 95% of the disturbances being smaller than 10 ha. Disturbance rates ranged from 0.29% yr -1 to 0.95% yr -1 , and differed substantially among management zones and study sites. Natural disturbances in strictly protected areas were longer in duration (median of 8 years) and slightly less variable in magnitude compared to human-dominated disturbances in managed forests (median duration of 1 year). However, temporal dynamics between natural and human-dominated disturbances showed strong synchrony, suggesting that disturbance peaks are driven by natural events affecting managed and unmanaged areas simultaneously. Our study demonstrates the potential of remote sensing for mapping forest disturbances in coupled human and natural systems, such as the forests of Central Europe. Yet, we also highlight the complexity of such systems in

  5. National-scale estimation of gross forest aboveground carbon loss: a case study of the Democratic Republic of the Congo

    International Nuclear Information System (INIS)

    Tyukavina, A; Potapov, P V; Turubanova, S A; Hansen, M C; Stehman, S V; Baccini, A; Goetz, S J; Laporte, N T; Houghton, R A

    2013-01-01

    Recent advances in remote sensing enable the mapping and monitoring of carbon stocks without relying on extensive in situ measurements. The Democratic Republic of the Congo (DRC) is among the countries where national forest inventories (NFI) are either non-existent or out of date. Here we demonstrate a method for estimating national-scale gross forest aboveground carbon (AGC) loss and associated uncertainties using remotely sensed-derived forest cover loss and biomass carbon density data. Lidar data were used as a surrogate for NFI plot measurements to estimate carbon stocks and AGC loss based on forest type and activity data derived using time-series multispectral imagery. Specifically, DRC forest type and loss from the FACET (Forêts d’Afrique Centrale Evaluées par Télédétection) product, created using Landsat data, were related to carbon data derived from the Geoscience Laser Altimeter System (GLAS). Validation data for FACET forest area loss were created at a 30-m spatial resolution and compared to the 60-m spatial resolution FACET map. We produced two gross AGC loss estimates for the DRC for the last decade (2000–2010): a map-scale estimate (53.3 ± 9.8 Tg C yr −1 ) accounting for whole-pixel classification errors in the 60-m resolution FACET forest cover change product, and a sub-grid estimate (72.1 ± 12.7 Tg C yr −1 ) that took into account 60-m cells that experienced partial forest loss. Our sub-grid forest cover and AGC loss estimates, which included smaller-scale forest disturbances, exceed published assessments. Results raise the issue of scale in forest cover change mapping and validation, and subsequent impacts on remotely sensed carbon stock change estimation, particularly for smallholder dominated systems such as the DRC. (letter)

  6. Estimating Aboveground Forest Carbon Stock of Major Tropical Forest Land Uses Using Airborne Lidar and Field Measurement Data in Central Sumatra

    Science.gov (United States)

    Thapa, R. B.; Watanabe, M.; Motohka, T.; Shiraishi, T.; shimada, M.

    2013-12-01

    including rubber, acacia, oil palm, and coconut. To cover these variations of forest type, eight LiDAR transacts crossing 60 (1-ha size) field plots were acquired for calibrating the models. The field plots consisted of AFCS ranging from 4 - 161 Mg /ha. The calibrated LiDAR to AFCS general model enabled to predict the AFCS with R2 = 0.87 and root mean square errors (RMSE) = 17.4 Mg /ha. The specific AFCS models provided carbon estimates, varied by forest types, with R2 ranging from 0.72 - 0.97 and uncertainty (RMSE) ranging from 1.4 - 10.7 Mg /ha. Using these models, AFCS maps were prepared for the LiDAR coverage that provided AFCS estimates for 8,000 ha offering larger ground sampling measurements for calibration of SAR based carbon mapping model to wider region of Sumatra.

  7. The “Forest Fire Project”, National cartographic portal of the Italian Environmental Department: an example of management of cartographic data to support forest fires fighting plans in national parks

    Directory of Open Access Journals (Sweden)

    Petrucci B

    2010-02-01

    Full Text Available The “Forest Fire Project” on the National cartographic portal (http://www.pcn.minambiente.it has been created by the Italian Ministry of Environment Territory and Sea (METS. The project is intended to support forest fire fighting plans in national protected areas as provided for by article 8 of the law November 21th 2000, no. 353 “Framework law on forest fires”. The project brings out the results of previous projects carried out in collaboration with several research institutes. Cartographic information is made available as free and reliable knowledge base in order to facilitate the draw up and implementation of the “Forest Fire Plans”, including the actual activity of forest fire extinction. Map information can be further implemented by various subjects such as researchers, land planning programmers or managers. The National cartographic portal gives the opportunity of overlaying various cartographic information and base maps supporting the “Forest Fire Project”; moreover it is possible to add other layers from other sources, through URL. Adequate “personalised” overlaps - which can be saved on one’s own GIS - allow in depth analysis and deductions aimed at specific objectives of territorial planning and management and in particular of Forest Fire Fighting Plans.

  8. Comparison of pixel and object-based classification for burned area mapping using SPOT-6 images

    Directory of Open Access Journals (Sweden)

    Elif Sertel

    2016-07-01

    Full Text Available On 30 May 2013, a forest fire occurred in Izmir, Turkey causing damage to both forest and fruit trees within the region. In this research, pre- and post-fire SPOT-6 images obtained on 30 April 2013 and 31 May 2013 were used to identify the extent of forest fire within the region. SPOT-6 images of the study region were orthorectified and classified using pixel and object-based classification (OBC algorithms to accurately delineate the boundaries of burned areas. The present results show that for OBC using only normalized difference vegetation index (NDVI thresholds is not sufficient enough to map the burn scars; however, creating a new and simple rule set that included mean brightness values of near infrared and red channels in addition to mean NDVI values of segments considerably improved the accuracy of classification. According to the accuracy assessment results, the burned area was mapped with a 0.9322 kappa value in OBC, while a 0.7433 kappa value was observed in pixel-based classification. Lastly, classification results were integrated with the forest management map to determine the effected forest types after the fire to be used by the National Forest Directorate for their operational activities to effectively manage the fire, response and recovery processes.

  9. Effect of forest on sediment yield in North China

    Directory of Open Access Journals (Sweden)

    Yu Xinxiao Prof.

    2013-06-01

    Full Text Available Forest-sediment relationship is a hot and important issue in Ecohydrology studies. China has implemented many large-scale reforestation programmes in the last decades to address the growing soil erosion and desertification. In this study, we made statistical and graphic analyses on the long-term hydrological data of the 39 watersheds in the rocky mountain area of the North China, and then we were able to analyze the effect of forest on sediment yield. Our results show that the effect is weak in the lees-precipitation regions (when MAP 500 mm, the impact of forest on reducing sediment yield is different with the varied forest coverage (f, the relationship between the sediment yield and forest coverage show a quadratic polynomial.

  10. Research on Topographic Map Updating

    Directory of Open Access Journals (Sweden)

    Ivana Javorović

    2013-04-01

    Full Text Available The investigation of interpretability of panchromatic satellite image IRS-1C integrated with multispectral Landsat TM image with the purpose of updating the topographic map sheet at the scale of 1:25 000 has been described. The geocoding of source map was based on trigonometric points of the map sheet. Satellite images were geocoded using control points selected from the map. The contents of map have been vectorized and topographic database designed. The digital image processing improved the interpretability of images. Then, the vectorization of new contents was made. The change detection of the forest and water area was defined by using unsupervised classification of spatial and spectral merged images. Verification of the results was made using corresponding aerial photographs. Although this methodology could not insure the complete updating of topographic map at the scale of 1:25 000, the database has been updated with huge amount of data. Erdas Imagine 8.3. software was used. 

  11. Global demand for gold is another threat for tropical forests

    International Nuclear Information System (INIS)

    Alvarez-Berríos, Nora L; Mitchell Aide, T

    2015-01-01

    The current global gold rush, driven by increasing consumption in developing countries and uncertainty in financial markets, is an increasing threat for tropical ecosystems. Gold mining causes significant alteration to the environment, yet mining is often overlooked in deforestation analyses because it occupies relatively small areas. As a result, we lack a comprehensive assessment of the spatial extent of gold mining impacts on tropical forests. In this study, we provide a regional assessment of gold mining deforestation in the tropical moist forest biome of South America. Specifically, we analyzed the patterns of forest change in gold mining sites between 2001 and 2013, and evaluated the proximity of gold mining deforestation to protected areas (PAs). The forest cover maps were produced using the Land Mapper web application and images from the MODIS satellite MOD13Q1 vegetation indices 250 m product. Annual maps of forest cover were used to model the incremental change in forest in ∼1600 potential gold mining sites between 2001–2006 and 2007–2013. Approximately 1680 km 2 of tropical moist forest was lost in these mining sites between 2001 and 2013. Deforestation was significantly higher during the 2007–2013 period, and this was associated with the increase in global demand for gold after the international financial crisis. More than 90% of the deforestation occurred in four major hotspots: Guianan moist forest ecoregion (41%), Southwest Amazon moist forest ecoregion (28%), Tapajós–Xingú moist forest ecoregion (11%), and Magdalena Valley montane forest and Magdalena–Urabá moist forest ecoregions (9%). In addition, some of the more active zones of gold mining deforestation occurred inside or within 10 km of ∼32 PAs. There is an urgent need to understand the ecological and social impacts of gold mining because it is an important cause of deforestation in the most remote forests in South America, and the impacts, particularly in aquatic systems

  12. Where are the forests in the United States "not disturbed" over a quarter century?

    Science.gov (United States)

    Huang, C.; Zhao, F. A.; Goward, S. N.; Schleeweis, K.; Michaelis, A.; Masek, J. G.; Dungan, J. L.; Cohen, W. B.; Moisen, G.; Rishmawi, K.

    2015-12-01

    Forests provide many important ecosystem services. Logging, fire, and other disturbances can disrupt or even diminish the provision of these services. Although many map products and inventory data can be used to estimate the total forested area in the United States, it is not clear how much of the country's forest remained undisturbed in recent decades. Through the North American Forest Dynamics (NAFD) study, we have mapped both disturbed and undisturbed forests over the conterminous United States (CONUS) using sub-annual time series of Landsat observations. The results revealed that 33.6% of the land area of CONUS had forest cover during some or all of the years between 1986 and 2010. About two thirds of the nation's forests remained undisturbed during the 25-year period. Most of these undisturbed forests were distributed in western and northern parts of the eastern US. The percentage of undisturbed forest in the southeastern states were lower, about 50% or less. In these states, much of the undisturbed forest was distributed along riparian zones or in protected areas, including national parks and national forests. In the northeastern and western US, riparian zones did not have a significantly higher proportion of undisturbed forests than non-riparian areas. While most protected areas had a high percentage of undisturbed forests, some of them had lower percentages than the average values of their surrounding regions. Topography may also have played a role in keeping forests "undisturbed". Many ecoregions in the western and northern US had a substantially higher percentage of undisturbed forests at high elevations than at low elevations.

  13. Interpreting forest biome productivity and cover utilizing nested scales of image resolution and biogeographical analysis

    Science.gov (United States)

    Iverson, Louis R.; Cook, Elizabeth A.; Graham, Robin L.; Olson, Jerry S.; Frank, Thomas D.; Ying, KE

    1988-01-01

    The objective was to relate spectral imagery of varying resolution with ground-based data on forest productivity and cover, and to create models to predict regional estimates of forest productivity and cover with a quantifiable degree of accuracy. A three stage approach was outlined. In the first stage, a model was developed relating forest cover or productivity to TM surface reflectance values (TM/FOREST models). The TM/FOREST models were more accurate when biogeographic information regarding the landscape was either used to stratigy the landscape into more homogeneous units or incorporated directly into the TM/FOREST model. In the second stage, AVHRR/FOREST models that predicted forest cover and productivity on the basis of AVHRR band values were developed. The AVHRR/FOREST models had statistical properties similar to or better than those of the TM/FOREST models. In the third stage, the regional predictions were compared with the independent U.S. Forest Service (USFS) data. To do this regional forest cover and forest productivity maps were created using AVHRR scenes and the AVHRR/FOREST models. From the maps the county values of forest productivity and cover were calculated. It is apparent that the landscape has a strong influence on the success of the approach. An approach of using nested scales of imagery in conjunction with ground-based data can be successful in generating regional estimates of variables that are functionally related to some variable a sensor can detect.

  14. Land use planning for forest catchment of Arasbaran

    International Nuclear Information System (INIS)

    Dehdar Dargahi, M.; Makhdoum, M.F.

    2001-01-01

    In this study, land use planning for six hydrological units (296690 ha) of Arasbaran forest catchment (N W of Iran in Azerbaijan) has been conducted. The main objectives of the plan were to promote sustainable use, to increase living conditions, and enhance environmental conservation in the region. First, ecological and socio-economic resources were surveyed and mapped (scale 1:50000). Then data analysis and integration with system analysis approach were performed. As a result, 3556 micro-ecosystems were mapped. Ecological capability of mapping unit (MU) was evaluated for: agriculture, range management, forestry, eco tourism and conservation with the aid of specified ecological models. Finally with coordination of socioeconomic data and ecological capability of MU, priority of land uses with qualitative-analogous method was established. At the end, map of land use planning for six hydrological units was depicted for management purposes. The results show that %5.38 of allocated land use is suitable for irrigation farming, %1.32 for dry farming, %17.43 for range management, %15.17 for protected forestry, %2.13 for forest plantation, %28.47 for extensive eco tourism, %0.01 for intensive eco tourism and finally %30.09 for conservation

  15. Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion

    Science.gov (United States)

    Yu, Yifan; Saatchi, Sassan; Heath, Linda S.; LaPoint, Elizabeth; Myneni, Ranga; Knyazikhin, Yuri

    2010-01-01

    Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P forests (R2 = 0.93, P forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.

  16. Integrated use of SRS Data &GIS Technique for Monitoring Changes in Riverine Forest of Sindh, Pakistan

    Science.gov (United States)

    Siddiqui, M.; Ali, Z.

    Deforestation / depletion in forest area threaten the sustainability of agricultural production systems and en-danger the economy of the country. Every year extensive areas of arable agricultural and forestlands are degraded and turned into wastelands, due to natural causes or human interventions. There are several causes of deforestation, such as expansion in agricultural area, urban development, forest fires, commercial logging, illicit cutting, grazing, constructions of dams / reservoirs and barrages, com munication links, etc. Depletion in forest cover, therefore, has an important impact on socio - economic development and ecological balance. High population growth rate in Pakistan is one of the main causes for the rapid deterioration of physical environment and natural resource base. In view of this, it is felt necessary to carryout land -u s e studies focusing on strategies for mapping the past and present conditions and extent of forests and rangelands using Satellite Remote Sensing (SRS) data and GIS t echnology. The SRS and GIS technology provides a possible means of monitoring and mapping changes occurring in natural resources and the environment on a continuing basis. The riverine forests of Sindh mostly grow along the River Indus in the flood plains, spread over an area of 241,000 ha are disappearing very rapidly. Construction of dams / barrages on the upper reaches of the River Indus for hydroelectric power and irrigation works have significantly reduced the discharge of fresh water into the lower Indus basin and as a result, 100,000 acres of forests have disappeared. Furthermore, the heavy floods that occurred in 1978, 1988, 1992 and 1997, altered the course of the River Indus in many places, especially in the lower reaches, this has also damaged the riverine forests of Sindh. An integrated approach involving analysis of SRS data from 1977 to 1998 and GIS technique have been used to evaluate the geographic ex-tent and distribution of the riverine

  17. Alaska High School Students Integrate Forest Ecology, Glacial Landscape Dynamics, and Human Maritime History in a Field Mapping Course at Cape Decision Lighthouse, Kuiu Island, Southeast Alaska

    Science.gov (United States)

    Connor, C. L.; Carstensen, R.; Domke, L.; Donohoe, S.; Clark, A.; Cordero, D.; Otsea, C.; Hakala, M.; Parks, R.; Lanwermeyer, S.; Discover Design Research (Ddr)

    2010-12-01

    Alaskan 10th and 11th graders earned college credit at Cape Decision Lighthouse as part of a 12-day, summer field research experience. Students and faculty flew to the southern tip of Kuiu Island located 388 km south of Juneau. Kuiu is the largest uninhabited island in southeastern Alaska. This field-based, introduction-to-research course was designed to engage students in the sciences and give them skills in technology, engineering, and mathematics. Two faculty, a forest naturalist and a geologist, introduced the students to the use of hand held GPS receivers, GIS map making, field note-taking and documentary photography, increment borer use, and soil studies techniques. Daily surveys across the region, provided onsite opportunities for the faculty to introduce the high schoolers to the many dimensions of forest ecology and plant succession. Students collected tree cores using increment borers to determine “release dates” providing clues to past wind disturbance. They discovered the influence of landscape change on the forest by digging soil pits and through guided interpretation of bedrock outcrops. The students learned about glacially influenced hydrology in forested wetlands during peat bog hikes. They developed an eye for geomorphic features along coastal traverses, which helped them to understand the influences of uplift through faulting and isostatic rebound in this tectonically active and once glaciated area. They surveyed forest patches to distinguish between regions of declining yellow-cedar from wind-disturbed spruce forests. The students encountered large volumes of primarily plastic marine debris, now stratified by density and wave energy, throughout the southern Kuiu intertidal zone. They traced pre-European Alaska Native subsistence use of the area, 19th and 20th century Alaska Territorial Maritime history, and learned about the 21st century radio tracking of over 10,000 commercial vessels by the Marine Exchange of Alaska from its many stations

  18. Assessing Habitat Quality of Forest-Corridors through NDVI Analysis in Dry Tropical Forests of South India: Implications for Conservation

    Directory of Open Access Journals (Sweden)

    Paramesha Mallegowda

    2015-02-01

    Full Text Available Most wildlife habitats and migratory routes are extremely threatened due to increasing demands on forestland and forest resources by burgeoning human population. Corridor landscape in Biligiri Rangaswamy Temple Tiger Reserve (BRT is one among them, subjected to various anthropogenic pressures. Human habitation, intensive farming, coffee plantations, ill-planned infrastructure developments and rapid spreading of invasive plant species Lantana camara, pose a serious threat to wildlife habitat and their migration. Aim of this work is to create detailed NDVI based land change maps and to use them to identify time-series trends in greening and browning in forest corridors in the study area and to identify the drivers that are influencing the observed changes. Over the four decades in BRT, NDVI increased in the core area of the forest and reduced in the fringe areas. The change analysis between 1973 and 2014 shows significant changes; browning due to anthropogenic activities as well as natural processes and greening due to Lantana spread. This indicates that the change processes are complex, involving multiple driving factors, such as socio-economic changes, high population growth, historical forest management practices and policies. Our study suggests that the use of updated and accurate change detection maps will be useful in taking appropriate site specific action-oriented conservation decisions to restore and manage the degraded critical wildlife corridors in human-dominated landscape.

  19. Quantifying scaling effects on satellite-derived forest area estimates for the conterminous USA

    Science.gov (United States)

    Daolan Zheng; L.S. Heath; M.J. Ducey; J.E. Smith

    2009-01-01

    We quantified the scaling effects on forest area estimates for the conterminous USA using regression analysis and the National Land Cover Dataset 30m satellite-derived maps in 2001 and 1992. The original data were aggregated to: (1) broad cover types (forest vs. non-forest); and (2) coarser resolutions (1km and 10 km). Standard errors of the model estimates were 2.3%...

  20. Composition and Structure of Forest Fire Refugia: What Are the Ecosystem Legacies across Burned Landscapes?

    Directory of Open Access Journals (Sweden)

    Garrett W. Meigs

    2018-05-01

    Full Text Available Locations within forest fires that remain unburned or burn at low severity—known as fire refugia—are important components of contemporary burn mosaics, but their composition and structure at regional scales are poorly understood. Focusing on recent, large wildfires across the US Pacific Northwest (Oregon and Washington, our research objectives are to (1 classify fire refugia and burn severity based on relativized spectral change in Landsat time series; (2 quantify the pre-fire composition and structure of mapped fire refugia; (3 in forested areas, assess the relative abundance of fire refugia and other burn severity classes across forest composition and structure types. We analyzed a random sample of 99 recent fires in forest-dominated landscapes from 2004 to 2015 that collectively encompassed 612,629 ha. Across the region, fire refugia extent was substantial but variable from year to year, with an annual mean of 38% of fire extent and range of 15–60%. Overall, 85% of total fire extent was forested, with the other 15% being non-forest. In comparison, 31% of fire refugia extent was non-forest prior to the most recent fire, highlighting that mapped refugia do not necessarily contain tree-based ecosystem legacies. The most prevalent non-forest cover types in refugia were vegetated: shrub (40%, herbaceous (33%, and crops (18%. In forested areas, the relative abundance of fire refugia varied widely among pre-fire forest types (20–70% and structural conditions (23–55%. Consistent with fire regime theory, fire refugia and high burn severity areas were inversely proportional. Our findings underscore that researchers, managers, and other stakeholders should interpret burn severity maps through the lens of pre-fire land cover, especially given the increasing importance of fire and fire refugia under global change.

  1. Dynamics of Industrial Forests in Southeast United States Assessed using Satellite and Field Inventory Data

    Science.gov (United States)

    Huang, C.; Tao, X.; Zhao, F. A.; Schleeweis, K.; Ling, P. Y.; Goward, S. N.; Masek, J. G.; Michaelis, A.

    2015-12-01

    The southeast United States (SE-US) is dominated by tree plantations and other forms of industrial forests that provide vital socio-ecological services to the human society. Most of these forests are managed to maximize economic outcome, and hence are often subject to intensive management practices and have different harvest-regrowth cycles as compared with natural forest ecosystems. Through the North American Forest Dynamics (NAFD) study, we have mapped forest disturbances for the conterminous United States using dense time series Landsat observations. The derived map products revealed that more than 50% of the forests in SE-US were harvested or disturbed by other forms of human or natural disturbance events at least once between 1986 and 2010. These products are being analyzed together with ancillary GIS data sets and field inventory data to identify industrial forests and to quantify their logging intensity, timber output, recovery rate, and the harvest-regrowth cycle. The derived results will be summarized in this presentation, along with discussions of the underlying environmental and management factors that may drive the spatio-temporal dynamics of the industrial forests in SE-US.

  2. Evaluation and prediction of shrub cover in coastal Oregon forests (USA)

    Science.gov (United States)

    Becky K. Kerns; Janet L. Ohmann

    2004-01-01

    We used data from regional forest inventories and research programs, coupled with mapped climatic and topographic information, to explore relationships and develop multiple linear regression (MLR) and regression tree models for total and deciduous shrub cover in the Oregon coastal province. Results from both types of models indicate that forest structure variables were...

  3. Myanmar Ecological Forecasting: Utilizing NASA Earth Observations to Monitor, Map, and Analyze Mangrove Forests in Myanmar for Enhanced Conservation

    Science.gov (United States)

    Weber, Samuel J.; Keddell, Louis; Kemal, Mohammed

    2014-01-01

    Mangroves supply many essential environmental amenities, such as preventing soil erosion, filtering water pollution, and protecting shorelines from harmful waves, floods, storms and winds. The Mangroves in Myanmar not only provide citizens with a food source, but they also offer firewood, charcoal, and construction materials. The depletion of mangroves is threatening more than the biodiversity however; Myanmar's fiscal livelihood is also in harm's way. Mangroves are valued at $100,000 to $277,000 per square kilometer and if managed in a sustainable fashion, can infuse constant income to the emerging Myanmarese economy. This study analyzed three coastline regions, the Ayeyarwady Delta, Rakhine and Tanintharyi, and mapped the spatial extent of mangrove forest during the dry season in 2000 and 2013. The classifications were derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operation Land Imager (OLI) imagery, as well as the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model information. This data was atmospherically corrected, mosaicked, masked and classified in ENVI, followed by ArcGIS to perform raster calculations and create final products. Forest degradation collected from 2000 to 2013 was later used to forecast the density and health of Mangroves in the year 2030. These results were subsequently presented to project partners Dr. Peter Leimgruber and Ellen Aiken at the Smithsonian Conservation Biology Institute in Front Royal, VA. After the presentation of the project to the partners, these organizations formally passed on to the Myanmar Ministry of Environment, Conservation and Forestry for policy makers and forest managers to utilize in order to protect the Myanmar mangrove ecosystem while sustaining a healthy economy.

  4. The variation of apparent crown size and canopy heterogeneity across lowland Amazonian forests

    OpenAIRE

    Barbier, N.; Couteron, Pierre; Proisy, Christophe; Malhi, Y.; Gastellu-Etchegorry, J. P.

    2010-01-01

    Aim The size structure of a forest canopy is an important descriptor of the forest environment that may yield information on forest biomass and ecology. However, its variability at regional scales is poorly described or understood because of the still prohibitive cost of very high-resolution imagery as well as the lack of an appropriate methodology. We here employ a novel approach to describe and map the canopy structure of tropical forests. Location Amazonia. Methods We apply Fourier transfo...

  5. Cross-border forest disturbance and the role of natural rubber in mainland Southeast Asia using annual Landsat time series

    DEFF Research Database (Denmark)

    Grogan, Kenneth; Pflugmacher, Dirk; Hostert, Patrick

    2015-01-01

    ) are there cross border differences in frontier and non-frontier forest disturbance rates between Cambodia and Vietnam, 3) what proportion of disturbances in frontier and non-frontier forests can be accounted for by the impact of rubber plantations, and 4) is there a relationship between global market prices...... rates related to rubber plantation expansion and price fluctuations of natural rubber. This suggests links between localized land cover/use change and international market forces, irrespective of differing political and socioeconomic backgrounds. Our study underlines the value of using dense Landsat...... that this approach can provide accurate forest disturbance maps but that accuracy is affected by forest type. Highest accuracies were found in evergreen forest (90%), with lower accuracies in mixed (80%) and dry-deciduous forest types (83%). Our final map considering all forest types yielded an overall accuracy...

  6. Understanding old-growth red and white pine dominated forests in Ontario. Forest fragmentation and biodiversity project technical report No. 2

    Energy Technology Data Exchange (ETDEWEB)

    Carleton, T.J.; Gordon, A.M.

    1992-01-01

    In summer 1991, a variety of forest stands dominated by old specimens of white pine and red pine were sampled across a representative portion of the species' range in northcentral Ontario. Plots were established in 40 stands of those surveyed to identify the salient structural components of old-growth, to survey the floristic composition (vascular plants and autotrophic non- vascular plants), to survey site characteristics, and to estimate the links in understorey alpha diversity with site conditions and stand structure. Long-term objectives include a definition of old- growth pine forest, recognition criteria, and prospective management options. Forest stand structure was enumerated through mapping, mensurational, and age estimation techniques. Forest vegetation, including over and understorey species, was non- destructively sampled and a range of data on stand and soil-site variables was also collected in conjunction with information on stand variables peculiar to old growth forests.

  7. Bioclimatic Extremes Drive Forest Mortality in Southwest, Western Australia

    Directory of Open Access Journals (Sweden)

    Bradley John Evans

    2013-07-01

    Full Text Available Extreme and persistent reductions in annual precipitation and an increase in the mean diurnal temperature range have resulted in patch scale forest mortality following the summer of 2010–2011 within the Forest study area near Perth, Western Australia. The impacts of 20 bioclimatic indicators derived from temperature, precipitation and of actual and potential evapotranspiration are quantified. We found that spatially aggregated seasonal climatologies across the study area show 2011 with an annual mean of 17.7 °C (± 5.3 °C was 1.1 °C warmer than the mean over recent decades (1981–2011,- 16.6 °C ± 4.6 °C and the mean has been increasing over the last decade. Compared to the same period, 2010–2011 summer maximum temperatures were 1.4 °C (31.6 °C ± 2.0 °C higher and the annual mean diurnal temperature range (Tmax−Tmin was 1.6 °C higher (14.7 °C ± 0.5 °C. In 2009, the year before the forest mortality began, annual precipitation across the study area was 69% less (301 mm ± 38 mm than the mean of 1981–2010 (907 mm ± 69 mm. Using Système Pour l'Observation de la Terre mission 5 (SPOT-5 satellite imagery captured after the summer of 2010–2011 we map a broad scale forest mortality event across the Forested study area. This satellite-climatology based methodology provides a means of monitoring and mapping similar forest mortality events- a critical contribution to our understanding the dynamical bioclimatic drivers of forest mortality events.

  8. Treefall Gap Mapping Using Sentinel-2 Images

    Directory of Open Access Journals (Sweden)

    Iván Barton

    2017-11-01

    Full Text Available Proper knowledge about resources in forest management is fundamental. One of the most important parameters of forests is their size or spatial extension. By determining the area of treefall gaps inside the compartments, a more accurate yield can be calculated and the scheduling of forestry operations could be planned better. Several field- and remote sensing-based approaches are in use for mapping but they provide only static measurements at high cost. The Earth Observation satellite mission Sentinel-2 was put in orbit as part of the Copernicus programme. With the 10-m resolution bands, it is possible to observe small-scale forestry operations like treefall gaps. The spatial extension of these gaps is often less than 200 m2, thus their detection can only be done on sub-pixel level. Due to the higher temporal resolution of Sentinel-2, multiple observations are available in a year; therefore, a time series evaluation is possible. The modelling of illumination can increase the accuracy of classification in mountainous areas. The method was tested on three deciduous forest sites in the Börzsöny Mountains in Hungary. The area evaluation produced less than 10% overestimation with the best possible solutions on the sites. The presented work shows a low-cost method for mapping treefall gaps which delivers annual information about the gap area in a deciduous forest.

  9. RGB-NDVI colour composites for visualizing forest change dynamics

    Science.gov (United States)

    Sader, S. A.; Winne, J. C.

    1992-01-01

    The study presents a simple and logical technique to display and quantify forest change using three dates of satellite imagery. The normalized difference vegetation index (NDVI) was computed for each date of imagery to define high and low vegetation biomass. Color composites were generated by combining each date of NDVI with either the red, green, or blue (RGB) image planes in an image display monitor. Harvest and regeneration areas were quantified by applying a modified parallelepiped classification creating an RGB-NDVI image with 27 classes that were grouped into nine major forest change categories. Aerial photographs and stand history maps are compared with the forest changes indicated by the RGB-NDVI image. The utility of the RGB-NDVI technique for supporting forest inventories and updating forest resource information systems are presented and discussed.

  10. Distribution and dynamics of mangrove forests of South Asia

    Science.gov (United States)

    Giri, Chandra; Long, Jordan; Abbas, Sawaid; Murali, R. Mani; Qamer, Faisal M.; Pengra, Bruce; Thau, David

    2014-01-01

    Mangrove forests in South Asia occur along the tidal sea edge of Bangladesh, India, Pakistan, and Sri Lanka. These forests provide important ecosystem goods and services to the region's dense coastal populations and support important functions of the biosphere. Mangroves are under threat from both natural and anthropogenic stressors; however the current status and dynamics of the region's mangroves are poorly understood. We mapped the current extent of mangrove forests in South Asia and identified mangrove forest cover change (gain and loss) from 2000 to 2012 using Landsat satellite data. We also conducted three case studies in Indus Delta (Pakistan), Goa (India), and Sundarbans (Bangladesh and India) to identify rates, patterns, and causes of change in greater spatial and thematic details compared to regional assessment of mangrove forests.

  11. Geologic Maps as the Foundation of Mineral-Hazards Maps in California

    Science.gov (United States)

    Higgins, C. T.; Churchill, R. K.; Downey, C. I.; Clinkenbeard, J. P.; Fonseca, M. C.

    2010-12-01

    The basic geologic map is essential to the development of products that help planners, engineers, government officials, and the general public make decisions concerning natural hazards. Such maps are the primary foundation that the California Geological Survey (CGS) uses to prepare maps that show potential for mineral-hazards. Examples of clients that request these maps are the California Department of Transportation (Caltrans) and California Department of Public Health (CDPH). Largely because of their non-catastrophic nature, mineral hazards have received much less public attention compared to earthquakes, landslides, volcanic eruptions, and floods. Nonetheless, mineral hazards can be a major concern locally when considering human health and safety and potential contamination of the environment by human activities such as disposal of earth materials. To address some of these concerns, the CGS has focused its mineral-hazards maps on naturally occurring asbestos (NOA), radon, and various potentially toxic metals as well as certain artificial features such as mines and oil and gas wells. The maps range in scope from statewide to counties and Caltrans districts to segments of selected highways. To develop the hazard maps, the CGS begins with traditional paper and digital versions of basic geologic maps, which are obtained from many sources such as its own files, the USGS, USDA Forest Service, California Department of Water Resources, and counties. For each study area, these maps present many challenges of compilation related to vintage, scale, definition of units, and edge-matching across map boundaries. The result of each CGS compilation is a digital geologic layer that is subsequently reinterpreted and transformed into new digital layers (e.g., lithologic) that focus on the geochemical and mineralogical properties of the area’s earth materials and structures. These intermediate layers are then integrated with other technical data to derive final digital layers

  12. Regional-Scale Drivers of Forest Structure and Function in Northwestern Amazonia

    Science.gov (United States)

    Higgins, Mark A.; Asner, Gregory P.; Anderson, Christopher B.; Martin, Roberta E.; Knapp, David E.; Tupayachi, Raul; Perez, Eneas; Elespuru, Nydia; Alonso, Alfonso

    2015-01-01

    Field studies in Amazonia have found a relationship at continental scales between soil fertility and broad trends in forest structure and function. Little is known at regional scales, however, about how discrete patterns in forest structure or functional attributes map onto underlying edaphic or geological patterns. We collected airborne LiDAR (Light Detection and Ranging) data and VSWIR (Visible to Shortwave Infrared) imaging spectroscopy measurements over 600 km2 of northwestern Amazonian lowland forests. We also established 83 inventories of plant species composition and soil properties, distributed between two widespread geological formations. Using these data, we mapped forest structure and canopy reflectance, and compared them to patterns in plant species composition, soils, and underlying geology. We found that variations in soils and species composition explained up to 70% of variation in canopy height, and corresponded to profound changes in forest vertical profiles. We further found that soils and plant species composition explained more than 90% of the variation in canopy reflectance as measured by imaging spectroscopy, indicating edaphic and compositional control of canopy chemical properties. We last found that soils explained between 30% and 70% of the variation in gap frequency in these forests, depending on the height threshold used to define gaps. Our findings indicate that a relatively small number of edaphic and compositional variables, corresponding to underlying geology, may be responsible for variations in canopy structure and chemistry over large expanses of Amazonian forest. PMID:25793602

  13. Regional-scale drivers of forest structure and function in northwestern Amazonia.

    Directory of Open Access Journals (Sweden)

    Mark A Higgins

    Full Text Available Field studies in Amazonia have found a relationship at continental scales between soil fertility and broad trends in forest structure and function. Little is known at regional scales, however, about how discrete patterns in forest structure or functional attributes map onto underlying edaphic or geological patterns. We collected airborne LiDAR (Light Detection and Ranging data and VSWIR (Visible to Shortwave Infrared imaging spectroscopy measurements over 600 km2 of northwestern Amazonian lowland forests. We also established 83 inventories of plant species composition and soil properties, distributed between two widespread geological formations. Using these data, we mapped forest structure and canopy reflectance, and compared them to patterns in plant species composition, soils, and underlying geology. We found that variations in soils and species composition explained up to 70% of variation in canopy height, and corresponded to profound changes in forest vertical profiles. We further found that soils and plant species composition explained more than 90% of the variation in canopy reflectance as measured by imaging spectroscopy, indicating edaphic and compositional control of canopy chemical properties. We last found that soils explained between 30% and 70% of the variation in gap frequency in these forests, depending on the height threshold used to define gaps. Our findings indicate that a relatively small number of edaphic and compositional variables, corresponding to underlying geology, may be responsible for variations in canopy structure and chemistry over large expanses of Amazonian forest.

  14. High-resolution forest carbon stocks and emissions in the Amazon

    Science.gov (United States)

    G. P. Asner; George V. N. Powell; Joseph Mascaro; David E. Knapp; John K. Clark; James Jacobson; Ty Kennedy-Bowdoin; Aravindh Balaji; Guayana Paez-Acosta; Eloy Victoria; Laura Secada; Michael Valqui; R. Flint. Hughes

    2010-01-01

    Efforts to mitigate climate change through the Reduced Emissions from Deforestation and Degradation (REDD) depend on mapping and monitoring of tropical forest carbon stocks and emissions over large geographic areas. With a new integrated use of satellite imaging, airborne light detection and ranging, and field plots, we mapped aboveground carbon stocks and emissions at...

  15. Fuzzy difference and data primitives: a transparent approach for supporting different definitions of forest in the context of REDD+

    Directory of Open Access Journals (Sweden)

    A. Comber

    2018-04-01

    Full Text Available This paper explores the use of fuzzy difference methods in order to understand the differences between forest classes. The context for this work is provided by REDD+, which seeks to reduce the net emissions of greenhouse gases by rewarding the conservation of forests in developing countries. REDD+ requires that local inventories of forest are undertaken and payments are made on the basis of the amount of forest (and associated carbon storage. At the most basic level this involves classifying land into forest and non-forest. However, the critical issues affecting the uptake, buy-in and ultimately the success of REDD+ are the lack of universally agreed definition of forest to support REDD+ mapping activities, and where such a definition is imposed, the marginalization of local community voices and local landscape conceptualizations. This tension is at the heart of REDD+. This paper addresses these issues by linking methods to quantify changes in fuzzy land cover to the concept of data primitives, which have been previously proposed as a suitable approach to move between land cover classes with different semantics. These are applied to case study that quantifies the difference in areas for two definitions of forest derived from the GLC and FAO definitions of forest. The results show how data primitives allow divergent concepts of forest to be represented and mapped from the same data and how the fuzzy sets approach can be used to quantify the differences and non-intersections of different concepts of forest. Together these methods provide for transparent translations between alternative conceptualizations of forest, allowing for plural notions of forest to be mapped and quantified. In particular, they allow for moving from an object-based notion of forest (and land cover in general to a field-based one, entirely avoiding the need for forest boundaries.

  16. High-severity fire: evaluating its key drivers and mapping its probability across western US forests

    Science.gov (United States)

    Parks, Sean A.; Holsinger, Lisa M.; Panunto, Matthew H.; Jolly, W. Matt; Dobrowski, Solomon Z.; Dillon, Gregory K.

    2018-04-01

    Wildland fire is a critical process in forests of the western United States (US). Variation in fire behavior, which is heavily influenced by fuel loading, terrain, weather, and vegetation type, leads to heterogeneity in fire severity across landscapes. The relative influence of these factors in driving fire severity, however, is poorly understood. Here, we explore the drivers of high-severity fire for forested ecoregions in the western US over the period 2002–2015. Fire severity was quantified using a satellite-inferred index of severity, the relativized burn ratio. For each ecoregion, we used boosted regression trees to model high-severity fire as a function of live fuel, topography, climate, and fire weather. We found that live fuel, on average, was the most important factor driving high-severity fire among ecoregions (average relative influence = 53.1%) and was the most important factor in 14 of 19 ecoregions. Fire weather was the second most important factor among ecoregions (average relative influence = 22.9%) and was the most important factor in five ecoregions. Climate (13.7%) and topography (10.3%) were less influential. We also predicted the probability of high-severity fire, were a fire to occur, using recent (2016) satellite imagery to characterize live fuel for a subset of ecoregions in which the model skill was deemed acceptable (n = 13). These ‘wall-to-wall’ gridded ecoregional maps provide relevant and up-to-date information for scientists and managers who are tasked with managing fuel and wildland fire. Lastly, we provide an example of the predicted likelihood of high-severity fire under moderate and extreme fire weather before and after fuel reduction treatments, thereby demonstrating how our framework and model predictions can potentially serve as a performance metric for land management agencies tasked with reducing hazardous fuel across large landscapes.

  17. ESTIMATION OF CARBON SEQUESTRATION BY RUSSIAN FORESTS: GEOSPATIAL ISSUE

    Directory of Open Access Journals (Sweden)

    N. V. Malysheva

    2017-01-01

    Full Text Available Сategories of carbon sequestration assessment for Russian forests are identified by GIS toolkit. Those are uniform by bioclimatic and site-specific conditions strata corresponding to modern version of bioclimatic forest district division. Stratification of forests at early stage substantially reduces the ambiguity of the evaluation because phytomass conversion sequestration capacity and expansion factor dependent on site-specific condition for calculating of forest carbon sink are absolutely necessary. Forest management units were linked to strata. Biomass conversion and expansion factor for forest carbon sink assessment linked to the strata were recalculated for forest management units. All operations were carried out with GIS analytical toolkit due to accessible functionalities. Units for forest carbon storage inventory and forest carbon balance calculation were localized. Production capacity parameters and forest carbon sequestration capacity have been visualized on maps complied by ArcGIS. Based on spatially-explicit information, we have found out that the greatest annual rates of forest’s carbon accumulation in Russian forests fall into mixed coniferous-deciduous forests of European-Ural part of Russia to Kaliningrad, Smolensk and Briansk Regions, coniferous-deciduous forests close to the boundary of Khabarovsk Region and Primorskij Kray in the Far East, as well as separate forest management units of Kabardino-Balkariya NorthCaucasian mountain area. The geospatial visualization of carbon sequestration by Russian forests and carbon balance assessment has been given.

  18. Forest fire risk assessment-an integrated approach based on multicriteria evaluation.

    Science.gov (United States)

    Goleiji, Elham; Hosseini, Seyed Mohsen; Khorasani, Nematollah; Monavari, Seyed Masoud

    2017-11-06

    The present study deals with application of the weighted linear combination method for zoning of forest fire risk in Dohezar and Sehezar region of Mazandaran province in northern Iran. In this study, the effective criteria for fires were identified by the Delphi method, and these included ecological and socioeconomic parameters. In this regard, the first step comprised of digital layers; the required data were provided from databases, related centers, and field data collected in the region. Then, the map of criteria was digitized in a geographic information system, and all criteria and indexes were normalized by fuzzy logic. After that, the geographic information system (GIS 10.3) was integrated with the Weighted Linear Combination and the Analytical Network Process, to produce zonation of the forest fire risk map in the Dohezar and Sehezar region. In order to analyze accuracy of the evaluation, the results obtained from the study were compared to records of former fire incidents in the region. This was done using the Kappa coefficient test and a receiver operating characteristic curve. The model showing estimations for forest fire risk explained that the prepared map had accuracy of 90% determined by the Kappa coefficient test and the value of 0.924 by receiver operating characteristic. These results showed that the prepared map had high accuracy and efficacy.

  19. Using AVIRIS data and multiple-masking techniques to map urban forest trees species

    Science.gov (United States)

    Q. Xiao; S.L. Ustin; E.G. McPherson

    2004-01-01

    Tree type and species information are critical parameters for urban forest management, benefit cost analysis and urban planning. However, traditionally, these parameters have been derived based on limited field samples in urban forest management practice. In this study we used high-resolution Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data and multiple-...

  20. Modeling of multi-strata forest fire severity using Landsat TM data

    Science.gov (United States)

    Q. Meng; R.K. Meentemeyer

    2011-01-01

    Most of fire severity studies use field measures of composite burn index (CBI) to represent forest fire severity and fit the relationships between CBI and Landsat imagery derived differenced normalized burn ratio (dNBR) to predict and map fire severity at unsampled locations. However, less attention has been paid on the multi-strata forest fire severity, which...

  1. Cluster-Based Adaptation Using Density Forest for HMM Phone Recognition

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Tan, Zheng-Hua; Christensen, Mads Græsbøll

    2014-01-01

    The dissimilarity between the training and test data in speech recognition systems is known to have a considerable effect on the recognition accuracy. To solve this problem, we use density forest to cluster the data and use maximum a posteriori (MAP) method to build a cluster-based adapted Gaussian...... mixture models (GMMs) in HMM speech recognition. Specifically, a set of bagged versions of the training data for each state in the HMM is generated, and each of these versions is used to generate one GMM and one tree in the density forest. Thereafter, an acoustic model forest is built by replacing...... the data of each leaf (cluster) in each tree with the corresponding GMM adapted by the leaf data using the MAP method. The results show that the proposed approach achieves 3:8% (absolute) lower phone error rate compared with the standard HMM/GMM and 0:8% (absolute) lower PER compared with bagged HMM/GMM....

  2. Waveform LiDAR across forest biomass gradients

    Science.gov (United States)

    Montesano, P. M.; Nelson, R. F.; Dubayah, R.; Sun, G.; Ranson, J.

    2011-12-01

    Detailed information on the quantity and distribution of aboveground biomass (AGB) is needed to understand how it varies across space and changes over time. Waveform LiDAR data is routinely used to derive the heights of scattering elements in each illuminated footprint, and the vertical structure of vegetation is related to AGB. Changes in LiDAR waveforms across vegetation structure gradients can demonstrate instrument sensitivity to land cover transitions. A close examination of LiDAR waveforms in footprints across a forest gradient can provide new insight into the relationship of vegetation structure and forest AGB. In this study we use field measurements of individual trees within Laser Vegetation Imaging Sensor (LVIS) footprints along transects crossing forest to non-forest gradients to examine changes in LVIS waveform characteristics at sites with low (field AGB measurements to original and adjusted LVIS waveforms to detect the forest AGB interval along a forest - non-forest transition in which the LVIS waveform lose the ability to discern differences in AGB. Our results help identify the lower end the forest biomass range that a ~20m footprint waveform LiDAR can detect, which can help infer accumulation of biomass after disturbances and during forest expansion, and which can guide the use of LiDAR within a multi-sensor fusion biomass mapping approach.

  3. An integrated analysis of the effects of past land use on forest herb colonization at the landscape scale

    Science.gov (United States)

    Verheyen, K.; Guntenspergen, Glenn R.; Biesbrouck, B.; Hermy, M.

    2003-01-01

    A framework that summarizes the direct and indirect effects of past land use on forest herb recolonization is proposed, and used to analyse the colonization patterns of forest understorey herbaceous species in a 360-ha mixed forest, grassland and arable landscape in the Dijle river valley (central Belgium).Fine-scale distribution maps were constructed for 14 species. The species were mapped in 15 946 forest plots and outside forests (along parcel margins) in 5188 plots. Forest stands varied in age between 1 and more than 224 years. Detailed land-use history data were combined with the species distribution maps to identify species-specific colonization sources and to calculate colonization distances.The six most frequent species were selected for more detailed statistical analysis.Logistic regression models indicated that species frequency in forest parcels was a function of secondary forest age, distance from the nearest colonization source and their interaction. Similar age and distance effects were found within hedgerows.In 199 forest stands, data about soils, canopy structure and the cover of competitive species were collected. The relative importance of habitat quality and spatio-temporal isolation for the colonization of the forest herb species was quantified using structural equation modelling (SEM), within the framework proposed for the effects of past land use.The results of the SEM indicate that, except for the better colonizing species, the measured habitat quality variables are of minor importance in explaining colonization patterns, compared with the combination of secondary forest age and distance from colonization sources.Our results suggest the existence of a two-stage colonization process in which diaspore availability determines the initial pattern, which is affected by environmental sorting at later stages.

  4. Thermokarst rates intensify due to climate change and forest fragmentation in an Alaskan boreal forest lowland

    Science.gov (United States)

    Lara, M.; Genet, Helene; McGuire, A. David; Euskirchen, Eugénie S.; Zhang, Yujin; Brown, Dana R. N.; Jorgenson, M.T.; Romanovsky, V.; Breen, Amy L.; Bolton, W.R.

    2016-01-01

    Lowland boreal forest ecosystems in Alaska are dominated by wetlands comprised of a complex mosaic of fens, collapse-scar bogs, low shrub/scrub, and forests growing on elevated ice-rich permafrost soils. Thermokarst has affected the lowlands of the Tanana Flats in central Alaska for centuries, as thawing permafrost collapses forests that transition to wetlands. Located within the discontinuous permafrost zone, this region has significantly warmed over the past half-century, and much of these carbon-rich permafrost soils are now within ~0.5 °C of thawing. Increased permafrost thaw in lowland boreal forests in response to warming may have consequences for the climate system. This study evaluates the trajectories and potential drivers of 60 years of forest change in a landscape subjected to permafrost thaw in unburned dominant forest types (paper birch and black spruce) associated with location on elevated permafrost plateau and across multiple time periods (1949, 1978, 1986, 1998, and 2009) using historical and contemporary aerial and satellite images for change detection. We developed (i) a deterministic statistical model to evaluate the potential climatic controls on forest change using gradient boosting and regression tree analysis, and (ii) a 30 × 30 m land cover map of the Tanana Flats to estimate the potential landscape-level losses of forest area due to thermokarst from 1949 to 2009. Over the 60-year period, we observed a nonlinear loss of birch forests and a relatively continuous gain of spruce forest associated with thermokarst and forest succession, while gradient boosting/regression tree models identify precipitation and forest fragmentation as the primary factors controlling birch and spruce forest change, respectively. Between 1950 and 2009, landscape-level analysis estimates a transition of ~15 km² or ~7% of birch forests to wetlands, where the greatest change followed warm periods. This work highlights that the vulnerability and resilience of

  5. Blue Carbon distribution in mangrove forests of the Americas

    Science.gov (United States)

    Simard, M.; Rivera-Monroy, V.; Fatoyinbo, T. E.; Roy Chowdhury, R.

    2013-12-01

    Globally, coastal ecosystems are critical to maintaining human livelihood and biodiversity. These ecosystems including mangroves, salt marshes, and sea grasses provide essential ecosystem services, such as supporting fisheries by providing important spawning grounds, filtering pollutants and contaminants from coastal waters, and protecting coastal development and communities against storms, floods and erosion. Additionally, recent research indicates that these vegetated coastal ecosystems are highly efficient carbon sinks (i.e. 'Blue Carbon') and can potentially play a significant role in ameliorating the effect of increasing global climate change by capturing significant amounts of carbon into sediments and plant biomass. The term blue carbon indicates the carbon stored in coastal vegetated wetlands (i.e., mangroves, intertidal marshes, and seagrass meadows). As a result of rapid global changes in coastal regions, it is crucial that we improve our understanding of the current and future state of the remaining coastal ecosystems and associated ecosystem services and their vulnerability to global climate change. In this study, we present a continental scale study of mangrove distribution and assess patterns of forest structural development associated to latitude and geomorphological setting. We produced a baseline map of mangrove canopy height and biomass for all mangrove forests of the Americas using data from the Shuttle Radar Topography Mission (SRTM) and publicly available land cover maps (Figure 1). The resulting canopy height map was calibrated using ICEsat/Geoscience Laser Altimeter system (GLAS). Biomass was derived from field data and allometry. The maps were validated with field data and results in accuracies that vary spatially around 2 to 3m in height and 20% in biomass. Figure 1: Global distribution of mangrove forests (green) and SRTM elevation data. These data were used to produce large scale maps of mangrove canopy height and biomass.

  6. Predisposition to depressive symptoms in patients with paranoid schizophrenia: constitutional-biological, socio-demographic factors and the debut of the disease

    Directory of Open Access Journals (Sweden)

    Kh. S. Zhyvago

    2016-12-01

    Full Text Available Aim. To identify the constitutional-biological, socio-demographic (microsocial and clinical-dynamic (the debut of the disease factors of predisposition to the depressive symptoms development in patients with paranoid schizophrenia. Materials and methods. A clinical-anamnestic, socio-demographic, clinical-psychopathological and pathopsychological examinations of 82 patients with paranoid schizophrenia with depressive symptoms identified and compared with 47 patients with paranoid schizophrenia without depressive symptoms. The study was managed using the PANSS, CDSS, HDRS scales and a questionnaire for the assessment of social functioning and quality of the mentally ill life. Groups did not differ in the basic demographic indicators. The study of constitutional and biological predisposition factors included the study of heredity and premorbid characterological features of patients. Socio-demographic (before the onset of the disease microsocial conditions and the current stage factors –family relationships; characteristics of living conditions; financial position; the quality of nutrition. To factors of the disease onset were attributed: age debut; factors that preceded the first episode; syndromes of the first episode; the first reference to a psychiatrist; suicidal statements and intentions. Results. It was evaluated the prognostic significance of individual predisposing factors to depression in patients with paranoid schizophrenia and found the following factors of predisposition (p<0.05: the heredity of schizophrenia and affective disorders; low level of erudition, combined with emotional and volitional immaturity, anxiety, prone to mood swings; low income and the cost of food, clothing and leisure; poor living conditions; unstable or conflictual family relationships; the presence of the first episode of affective symptoms, such as depressive, which is stored in the further course of the disease, as well as anhedonia, sleep and appetite

  7. Proceedings from a workshop on Sustainable forest management in tropical forests of Guyana

    Energy Technology Data Exchange (ETDEWEB)

    Hagner, Mats [ed.] [Swedish Univ. of Agricultural Sciences, Umeaa (Sweden). Dept. of Silviculture; Maluenda, J. [ed.] [ORGUT Consulting AB, Stockholm (Sweden)

    1998-12-31

    Guyana officials were certain that an efficient forest management could yield economic benefits to the country, while still allowing for the sustainability of its forest resources. Standards will be set in a Code of Practice (COP). Lectures, presented in the proceeding, were mixed with group discussions and finally the 26 participants gave their written view of `What has to be done in Guyana and by whom?`. Amerindians wanted their own foresters should be recruited to oversee the activities on their own land. Bushmilling need to be controlled but not banned. Monitoring timber products and control of hunting should be stricter. COP should set standards for the residual stand. Environmental Protection Agency wanted more research and training, with aim of self-monitoring capability for forest users. Forest Products Association recommended government to co-operate for refinement of: training, mapping of resources, harvesting plans, concession agreements, road building, and bushmilling. Forestry Commission wanted concession allocation procedures to be reviewed: zonation of chainsaw activities, protection of small-scale operators, management plans. COP should be revised and tested in practice. Suggestion about standards for residual stand should be considered. ORGUT Lecturers recommended a standard for residual stand, a vertical and horizontal spot density measure. Based on that the concession holder could harvest what, where and when be preferred and chose the most efficient technique

  8. Proceedings from a workshop on Sustainable forest management in tropical forests of Guyana

    Energy Technology Data Exchange (ETDEWEB)

    Hagner, Mats [ed.; Swedish Univ. of Agricultural Sciences, Umeaa (Sweden). Dept. of Silviculture; Maluenda, J [ed.; ORGUT Consulting AB, Stockholm (Sweden)

    1999-12-31

    Guyana officials were certain that an efficient forest management could yield economic benefits to the country, while still allowing for the sustainability of its forest resources. Standards will be set in a Code of Practice (COP). Lectures, presented in the proceeding, were mixed with group discussions and finally the 26 participants gave their written view of `What has to be done in Guyana and by whom?`. Amerindians wanted their own foresters should be recruited to oversee the activities on their own land. Bushmilling need to be controlled but not banned. Monitoring timber products and control of hunting should be stricter. COP should set standards for the residual stand. Environmental Protection Agency wanted more research and training, with aim of self-monitoring capability for forest users. Forest Products Association recommended government to co-operate for refinement of: training, mapping of resources, harvesting plans, concession agreements, road building, and bushmilling. Forestry Commission wanted concession allocation procedures to be reviewed: zonation of chainsaw activities, protection of small-scale operators, management plans. COP should be revised and tested in practice. Suggestion about standards for residual stand should be considered. ORGUT Lecturers recommended a standard for residual stand, a vertical and horizontal spot density measure. Based on that the concession holder could harvest what, where and when be preferred and chose the most efficient technique

  9. Tree mortality based fire severity classification for forest inventories: A Pacific Northwest national forests example

    Science.gov (United States)

    Thomas R. Whittier; Andrew N. Gray

    2016-01-01

    Determining how the frequency, severity, and extent of forest fires are changing in response to changes in management and climate is a key concern in many regions where fire is an important natural disturbance. In the USA the only national-scale fire severity classification uses satellite image changedetection to produce maps for large (>400 ha) fires, and is...

  10. Object-oriented classification of forest structure from light detection and ranging data for stand mapping

    Science.gov (United States)

    Alicia A. Sullivan; Robert J. McGaughey; Hans-Erik Andersen; Peter. Schiess

    2009-01-01

    Stand delineation is an important step in the process of establishing a forest inventory and provides the spatial framework for many forest management decisions. Many methods for extracting forest structure characteristics for stand delineation and other purposes have been researched in the past, primarily focusing on high-resolution imagery and satellite data. High-...

  11. Spatial and Temporal Analysis of Industrial Forest Clearcuts in the Conterminous United States

    Science.gov (United States)

    Huo, L. Z.; Boschetti, L.

    2015-12-01

    Remote sensing has been widely used for mapping and characterizing changes in forest cover, but the available remote sensing forest change products are not discriminating between deforestation (permanent transition from forest to non forest) and industrial forest management (logging followed by regrowth, with no land cover/ land use class change) (Hansen et al, 2010). Current estimates of carbon-equivalent emissions report the contribution of deforestation as 12% of total anthropogenic carbon emissions (van der Werf et al., 2009), but accurate monitoring of forest carbon balance should discriminate between land use change related to forest natural disturbances, and forest management. The total change in forest cover (Gross Forest Cover Loss, GFLC) needs to be characterized based on the cause (natural/human) and on the outcome of the change (regeneration to forest/transition to non/forest)(Kurtz et al, 2010). This paper presents the methodology used to classify the forest loss detected by the University of Maryland Global Forest Change product (Hansen, 2013) into deforestation, disturbances (fires, insect outbreaks) and industrial forest clearcuts. The industrial forest clearcuts were subsequently analysed by converting the pixel based detections into objects, and applying patch level metrics (e.g. size, compactness, straightness of boundaries) and contextual measures. The analysis is stratified by region and by dominant forest specie, to highlight changes in the rate of forest resource utilization in the 2003-2013 period covered by the Maryland Forest Cover Change Product. References Hansen, M.C., Stehman, S.V., & Potapov, P.V. (2010). Reply to Wernick et al.: Global scale quantification of forest change. Proceedings of the National Academy of Sciences, 107, E148-E148 Hansen, M.C., Potapov, P.V., Moore, R et al., (2013), "High resolution Global Maps for the 21stCentury Forest Cover Change", Science 342: 850-853 Kurz, W.A. (2010). An ecosystem context for global

  12. The role of knowledge management tools in supporting sustainable forest management

    Directory of Open Access Journals (Sweden)

    H. Vacik

    2013-12-01

    Full Text Available Aim of study: Knowledge Management (KM tools facilitate the implementation of knowledge processes by identifying, creating, structuring, and sharing knowledge through use of information technology in order to improve decision-making. In this contribution, we review the way in which KM tools and techniques are used in forest management, and categorize a selected set of them according to their contribution to support decision makers in the phases of problem identification, problem modelling, and problem solving.Material and Methods: Existing examples of cognitive mapping tools, web portals, workflow systems, best practices, and expert systems as well as intelligent agents are screened for their applicability and use in the context of decision support for sustainable forest management. Evidence from scientific literature and case studies is utilized to evaluate the contribution of the different KM tools to support problem identification, problem modelling, and problem solving.Main results: Intelligent agents, expert systems and cognitive maps support all phases of the forest planning process strongly. Web based tools have good potential to support participatory forest planning. Based on the needs of forest management decision support and the thus-far underutilized capabilities of KM tools it becomes evident that future decision analysis will have to consider the use of KM more intensively. Research highlights: As the problem-solving process is the vehicle for connecting both knowledge and decision making performance, the next generation of DSS will need to better encapsulate practices that enhance and promote knowledge management. Web based tools will substitute desktop applications by utilizing various model libraries on the internet.Keywords: best practices; cognitive mapping; expert systems; intelligent agents; web portals; workflow systems; Decision Support Systems. 

  13. METHOD OF FOREST FIRES PROBABILITY ASSESSMENT WITH POISSON LAW

    Directory of Open Access Journals (Sweden)

    A. S. Plotnikova

    2016-01-01

    Full Text Available The article describes the method for the forest fire burn probability estimation on a base of Poisson distribution. The λ parameter is assumed to be a mean daily number of fires detected for each Forest Fire Danger Index class within specific period of time. Thus, λ was calculated for spring, summer and autumn seasons separately. Multi-annual daily Forest Fire Danger Index values together with EO-derived hot spot map were input data for the statistical analysis. The major result of the study is generation of the database on forest fire burn probability. Results were validated against EO daily data on forest fires detected over Irkutsk oblast in 2013. Daily weighted average probability was shown to be linked with the daily number of detected forest fires. Meanwhile, there was found a number of fires which were developed when estimated probability was low. The possible explanation of this phenomenon was provided.

  14. Carbon emissions risk map from deforestation in the tropical Amazon

    Science.gov (United States)

    Ometto, J.; Soler, L. S.; Assis, T. D.; Oliveira, P. V.; Aguiar, A. P.

    2011-12-01

    Assis, Pedro Valle This work aims to estimate the carbon emissions from tropical deforestation in the Brazilian Amazon associated to the risk assessment of future land use change. The emissions are estimated by incorporating temporal deforestation dynamics, accounting for the biophysical and socioeconomic heterogeneity in the region, as well secondary forest growth dynamic in abandoned areas. The land cover change model that supported the risk assessment of deforestation, was run based on linear regressions. This method takes into account spatial heterogeneity of deforestation as the spatial variables adopted to fit the final regression model comprise: environmental aspects, economic attractiveness, accessibility and land tenure structure. After fitting a suitable regression models for each land cover category, the potential of each cell to be deforested (25x25km and 5x5 km of resolution) in the near future was used to calculate the risk assessment of land cover change. The carbon emissions model combines high-resolution new forest clear-cut mapping and four alternative sources of spatial information on biomass distribution for different vegetation types. The risk assessment map of CO2 emissions, was obtained by crossing the simulation results of the historical land cover changes to a map of aboveground biomass contained in the remaining forest. This final map represents the risk of CO2 emissions at 25x25km and 5x5 km until 2020, under a scenario of carbon emission reduction target.

  15. Small area estimation in forests affected by wildfire in the Interior West

    Science.gov (United States)

    G. G. Moisen; J. A. Blackard; M. Finco

    2004-01-01

    Recent emphasis has been placed on estimating amount and characteristics of forests affected by wildfire in the Interior West. Data collected by FIA is intended for estimation over large geographic areas and is too sparse to construct sufficiently precise estimates within burn perimeters. This paper illustrates how recently built MODISbased maps of forest/nonforest and...

  16. Modeling grain-size dependent bias in estimating forest area: a regional application

    Science.gov (United States)

    Daolan Zheng; Linda S. Heath; Mark J. Ducey

    2008-01-01

    A better understanding of scaling-up effects on estimating important landscape characteristics (e.g. forest percentage) is critical for improving ecological applications over large areas. This study illustrated effects of changing grain sizes on regional forest estimates in Minnesota, Wisconsin, and Michigan of the USA using 30-m land-cover maps (1992 and 2001)...

  17. Using Forest Inventory and Analysis data to model plant-climate relationships

    Science.gov (United States)

    Nicholas L. Crookston; Gerald E. Rehfeldt; Marcus V. Warwell

    2007-01-01

    Forest Inventory and Analysis (FIA) data from 11 Western conterminous States were used to (1) estimate and map the climatic profiles of tree species and (2) explore how to include climate variables in individual tree growth equations used in the Forest Vegetation Simulator (FVS). On the first front, we found the FIA data to be useful as training data in Breiman's...

  18. SRTM-DEM and Landsat ETM+ data for mapping tropical dry forest cover and biodiversity assessment in Nicaragua

    Science.gov (United States)

    S.E. Sesnie; S.E. Hagell; S.M. Otterstrom; C.L. Chambers; B.G. Dickson

    2008-01-01

    Tropical dry and deciduous forest comprises as much as 42% of the world’s tropical forests, but has received far less attention than forest in wet tropical areas. Land use change threatens to greatly reduce the extent of dry forest that is known to contain high levels of plant and animal diversity. Forest fragmentation may further endanger arboreal mammals that play...

  19. A MICRO-UAV SYSTEM FOR FOREST MANAGEMENT

    Directory of Open Access Journals (Sweden)

    T. Hormigo

    2013-08-01

    Full Text Available Spin.Works has developed a complete micro-UAV system with the purpose of supporting forest management activities. The aircraft is based on a winged-body design spanning 1.8 m with a maximum take-off weight of 2 kg, and can carry out missions lasting up to 2 h at a cruise speed of about 60 km/h. The corresponding ground station ensures the mission planning functions, real-time flight monitoring and visualization, and serves also as a real-time and post-flight data exploitation platform. A particular emphasis is placed on image processing techniques applied to two operational concepts: a fire detection service and a forest mapping service. The real-time operations related to fire detection consist on object tracking and geo-referencing functions, which can be operated by a user directly over the video stream, enabling the quick estimation of the 3D location (latitude, longitude, altitude of suspected fires. The post-flight processing consists of extracting valuable knowledge from the payload data, in particular tree coverage maps, orthophoto mosaics and Digital Surface Models (DSMs, which can be used for further forest characterization such as wood and cork volume estimation. The system is currently entering initial operations, with expanded operations expected during Q3 2013.

  20. Integrating Vegetation Classification, Mapping, and Strategic Inventory for Forest Management

    Science.gov (United States)

    C. K. Brewer; R. Bush; D. Berglund; J. A. Barber; S. R. Brown

    2006-01-01

    Many of the analyses needed to address multiple resource issues are focused on vegetation pattern and process relationships and most rely on the data models produced from vegetation classification, mapping, and/or inventory. The Northern Region Vegetation Mapping Project (R1-VMP) data models are based on these three integrally related, yet separate processes. This...

  1. Texas Disasters II: Utilizing NASA Earth Observations to Assist the Texas Forest Service in Mapping and Analyzing Fuel Loads and Phenology in Texas Grasslands

    Science.gov (United States)

    Brooke, Michael; Williams, Meredith; Fenn, Teresa

    2016-01-01

    The risk of severe wildfires in Texas has been related to weather phenomena such as climate change and recent urban expansion into wild land areas. During recent years, Texas wild land areas have experienced sequences of wet and dry years that have contributed to increased wildfire risk and frequency. To prevent and contain wildfires, the Texas Forest Service (TFS) is tasked with evaluating and reducing potential fire risk to better manage and distribute resources. This task is made more difficult due to the vast and varied landscape of Texas. The TFS assesses fire risk by understanding vegetative fuel types and fuel loads. To better assist the TFS, NASA Earth observations, including Landsat and Moderate Resolution Imaging Specrtoradiometer (MODIS) data, were analyzed to produce maps of vegetation type and specific vegetation phenology as it related to potential wildfire fuel loads. Fuel maps from 2010-2011 and 2014-2015 fire seasons, created by the Texas Disasters I project, were used and provided alternating, complementary map indicators of wildfire risk in Texas. The TFS will utilize the end products and capabilities to evaluate and better understand wildfire risk across Texas.

  2. Spatiotemporal Change Detection in Forest Cover Dynamics Along Landslide Susceptible Region of Karakoram Highway, Pakistan

    Science.gov (United States)

    Rashid, Barira; Iqbal, Javed

    2018-04-01

    Forest Cover dynamics and its understanding is essential for a country's social, environmental, and political engagements. This research provides a methodical approach for the assessment of forest cover along Karakoram Highway. It has great ecological and economic significance because it's a part of China-Pakistan Economic Corridor. Landsat 4, 5 TM, Landsat 7 ETM and Landsat 8 OLI imagery for the years 1990, 2000, 2010 and 2016 respectively were subjected to supervised classification in ArcMap 10.5 to identify forest change. The study area was categorized into five major land use land cover classes i.e., Forest, vegetation, urban, open land and snow cover. Results from post classification forest cover change maps illustrated notable decrease of almost 26 % forest cover over the time period of 26 years. The accuracy assessment revealed the kappa coefficients 083, 0.78, 0.77 and 0.85, respectively. Major reason for this change is an observed replacement of native forest cover with urban areas (12.5 %) and vegetation (18.6 %) However, there is no significant change in the reserved forests along the study area that contributes only 2.97 % of the total forest cover. The extensive forest degradation and risk prone topography of the region has increased the environmental risk of landslides. Hence, effective policies and forest management is needed to protect not only the environmental and aesthetic benefits of the forest cover but also to manage the disaster risks. Apart from the forest assessment, this research gives an insight of land cover dynamics, along with causes and consequences, thereby showing the forest degradation hotspots.

  3. Long-term fragmentation effects on the distribution and dynamics of canopy gaps in a tropical montane forest

    Science.gov (United States)

    Nicholas R. Vaughn; Gregory P. Asner; Christian P. Giardina

    2015-01-01

    Fragmentation alters forest canopy structure through various mechanisms, which in turn drive subsequent changes to biogeochemical processes and biological diversity. Using repeated airborne LiDAR (Light Detection and Ranging) mappings, we investigated the size distribution and dynamics of forest canopy gaps across a topical montane forest landscape in Hawaii naturally...

  4. Soil carbon storage estimation in a forested watershed using quantitative soil-landscape modeling

    Science.gov (United States)

    James A. Thompson; Randall K. Kolka

    2005-01-01

    Carbon storage in soils is important to forest ecosystems. Moreover, forest soils may serve as important C sinks for ameliorating excess atmospheric CO2. Spatial estimates of soil organic C (SOC) storage have traditionally relied upon soil survey maps and laboratory characterization data. This approach does not account for inherent variability...

  5. BOREAS SERM Forest Cover Data of Saskatchewan in Vector Format

    Data.gov (United States)

    National Aeronautics and Space Administration — A condensed forest cover type digital map of Saskatchewan and is a product of the Saskatchewan Environment and Resource Management, Forestry Branch-Inventory Unit...

  6. Identifying grain-size dependent errors on global forest area estimates and carbon studies

    Science.gov (United States)

    Daolan Zheng; Linda S. Heath; Mark J. Ducey

    2008-01-01

    Satellite-derived coarse-resolution data are typically used for conducting global analyses. But the forest areas estimated from coarse-resolution maps (e.g., 1 km) inevitably differ from a corresponding fine-resolution map (such as a 30-m map) that would be closer to ground truth. A better understanding of changes in grain size on area estimation will improve our...

  7. Monitoring and estimating tropical forest carbon stocks: making REDD a reality

    International Nuclear Information System (INIS)

    Gibbs, Holly K; Brown, Sandra; Niles, John O; Foley, Jonathan A

    2007-01-01

    Reducing carbon emissions from deforestation and degradation in developing countries is of central importance in efforts to combat climate change. Key scientific challenges must be addressed to prevent any policy roadblocks. Foremost among the challenges is quantifying nations' carbon emissions from deforestation and forest degradation, which requires information on forest clearing and carbon storage. Here we review a range of methods available to estimate national-level forest carbon stocks in developing countries. While there are no practical methods to directly measure all forest carbon stocks across a country, both ground-based and remote-sensing measurements of forest attributes can be converted into estimates of national carbon stocks using allometric relationships. Here we synthesize, map and update prominent forest biomass carbon databases to create the first complete set of national-level forest carbon stock estimates. These forest carbon estimates expand on the default values recommended by the Intergovernmental Panel on Climate Change's National Greenhouse Gas Inventory Guidelines and provide a range of globally consistent estimates

  8. Forest extent and deforestation in tropical Africa since 1900.

    Science.gov (United States)

    Aleman, Julie C; Jarzyna, Marta A; Staver, A Carla

    2018-01-01

    Accurate estimates of historical forest extent and associated deforestation rates are crucial for quantifying tropical carbon cycles and formulating conservation policy. In Africa, data-driven estimates of historical closed-canopy forest extent and deforestation at the continental scale are lacking, and existing modelled estimates diverge substantially. Here, we synthesize available palaeo-proxies and historical maps to reconstruct forest extent in tropical Africa around 1900, when European colonization accelerated markedly, and compare these historical estimates with modern forest extent to estimate deforestation. We find that forests were less extensive in 1900 than bioclimatic models predict. Resultantly, across tropical Africa, ~ 21.7% of forests have been deforested, yielding substantially slower deforestation than previous estimates (35-55%). However, deforestation was heterogeneous: West and East African forests have undergone almost complete decline (~ 83.3 and 93.0%, respectively), while Central African forests have expanded at the expense of savannahs (~ 1.4% net forest expansion, with ~ 135,270 km 2 of savannahs encroached). These results suggest that climate alone does not determine savannah and forest distributions and that many savannahs hitherto considered to be degraded forests are instead relatively old. These data-driven reconstructions of historical biome distributions will inform tropical carbon cycle estimates, carbon mitigation initiatives and conservation planning in both forest and savannah systems.

  9. Normalizing Landsat and ASTER Data Using MODIS Data Products for Forest Change Detection

    Science.gov (United States)

    Gao, Feng; Masek, Jeffrey G.; Wolfe, Robert E.; Tan, Bin

    2010-01-01

    Monitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one "standard" date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates.

  10. Spatio-temporal evolution of forest fires in Portugal

    Science.gov (United States)

    Tonini, Marj; Pereira, Mário G.; Parente, Joana

    2017-04-01

    A key issue in fire management is the ability to explore and try to predict where and when fires are more likely to occur. This information can be useful to understand the triggering factors of ignitions and for planning strategies to reduce forest fires, to manage the sources of ignition and to identify areas and frame period at risk. Therefore, producing maps displaying forest fires location and their occurrence in time can be of great help for accurately forecasting these hazardous events. In a fire prone country as Portugal, where thousands of events occurs each year, it is involved to drive information about fires over densities and recurrences just by looking at the original arrangement of the mapped ignition points or burnt areas. In this respect, statistical methods originally developed for spatio-temporal stochastic point processes can be employed to find a structure within these large datasets. In the present study, the authors propose an approach to analyze and visualize the evolution in space and in time of forest fires occurred in Portugal during a long frame period (1990 - 2013). Data came from the Portuguese mapped burnt areas official geodatabase (by the Institute for the Conservation of Nature and Forests), which is the result of interpreted satellite measurements. The following statistical analyses were performed: the geographically-weighted summary statistics, to analyze the local variability of the average burned area; the space-time Kernel density, to elaborate smoothed density surfaces representing over densities of fires classed by size and on North vs South region. Finally, we emploied the volume rendering thecnique to visualize the spatio-temporal evolution of these events into a unique map: this representation allows visually inspecting areas and time-step more affected from a high aggregation of forest fires. It results that during the whole investigated period over densities are mainly located in the northern regions, while in the

  11. Predictive Mapping of Dwarf Shrub Vegetation in an Arid High Mountain Ecosystem Using Remote Sensing and Random Forests

    Directory of Open Access Journals (Sweden)

    Kim André Vanselow

    2014-07-01

    Full Text Available In many arid mountains, dwarf shrubs represent the most important fodder and firewood resources; therefore, they are intensely used. For the Eastern Pamirs (Tajikistan, they are assumed to be overused. However, empirical evidence on this issue is lacking. We aim to provide a method capable of mapping vegetation in this mountain desert. We used random forest models based on remote sensing data (RapidEye, ASTER GDEM and 359 plots to predictively map total vegetative cover and the distribution of the most important firewood plants, K. ceratoides and A. leucotricha. These species were mapped as present in 33.8% of the study area (accuracy 90.6%. The total cover of the dwarf shrub communities ranged from 0.5% to 51% (per pixel. Areas with very low cover were limited to the vicinity of roads and settlements. The model could explain 80.2% of the total variance. The most important predictor across the models was MSAVI2 (a spectral vegetation index particularly invented for low-cover areas. We conclude that the combination of statistical models and remote sensing data worked well to map vegetation in an arid mountainous environment. With this approach, we were able to provide tangible data on dwarf shrub resources in the Eastern Pamirs and to relativize previous reports about their extensive depletion.

  12. ShapeSelectForest: a new r package for modeling landsat time series

    Science.gov (United States)

    Mary Meyer; Xiyue Liao; Gretchen Moisen; Elizabeth Freeman

    2015-01-01

    We present a new R package called ShapeSelectForest recently posted to the Comprehensive R Archival Network. The package was developed to fit nonparametric shape-restricted regression splines to time series of Landsat imagery for the purpose of modeling, mapping, and monitoring annual forest disturbance dynamics over nearly three decades. For each pixel and spectral...

  13. Relating LANDSAT ETM+ and forest inventory data for mapping successional stages in a tropical wet forest / Relacionando LANDSAT ETM+ e dados de inventário florestal para mapeamento estádios sucessionais em uma floresta tropical úmida

    Directory of Open Access Journals (Sweden)

    Fábio G. Gonçalves

    2010-10-01

    Full Text Available AbstractIn this study, we test whether an existing classification technique based on the integration of LANDSAT ETM+ and forest inventory data enables detailed characterization of successional stages in a tropical wet forest site. The specific objectives were: (1 to map forest age classes across the La Selva Biological Station in Costa Rica; and (2 to quantify uncertainties in the proposed approach in relation to field data and existing vegetation maps. Although significant relationships between vegetation hight entropy (a surrogate for forest age and ETM+ data were detected, the classification scheme tested in this study was not suitable for characterizing spatial variation in age at La Selva, as evidenced by the error matrix and the low Kappa coefficient (0.129. Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and late successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels. ResumoNesse estudo, testamos se uma técnica de classificação existente, baseada na integração de imagens LANDSAT ETM+ e os dados de inventário florestal, permite a caracterização detalhada dos estádios sucessionais em uma área de floresta tropical úmida. Os objetivos específicos foram: (1 mapear classes de idade florestal na Estação Biológica La Selva, na Costa Rica, e (2 quantificar as incertezas da abordagem proposta em relação aos dados de campo e mapas de vegetação existente. Apesar de terem sido detectadas relações significativas entre dados ETM+ e medidas de entropia da altura da vegetação (um substituto para a idade florestal o sistema de classificação testados nesse estudo não se demonstrou adequado para caracterizar a variação espacial em idade em La Selva, como evidenciado pela matriz de erro e o baixo coeficiente Kappa (0,129. Fatores que afetam o desempenho da

  14. Development of a Methodology for Predicting Forest Area for Large-Area Resource Monitoring

    Science.gov (United States)

    William H. Cooke

    2001-01-01

    The U.S. Department of Agriculture, Forest Service, Southcm Research Station, appointed a remote-sensing team to develop an image-processing methodology for mapping forest lands over large geographic areds. The team has presented a repeatable methodology, which is based on regression modeling of Advanced Very High Resolution Radiometer (AVHRR) and Landsat Thematic...

  15. SRTM-DEM AND LANDSAT ETM+ DATA FOR MAPPING TROPICAL DRY FOREST COVER AND BIODIVERSITY ASSESSMENT IN NICARAGUA

    OpenAIRE

    Brett G. Dickson; Carol L. Chambers; Sarah M. Otterstrom; Suzanne E. Hagell; Steven E. Sesnie

    2008-01-01

    Tropical dry and deciduous forest comprises as much as 42% of the world’s tropical forests, but hasreceived far less attention than forest in wet tropical areas. Land use change threatens to greatly reducethe extent of dry forest that is known to contain high levels of plant and animal diversity. Forest fragmentationmay further endanger arboreal mammals that play principal role in the dispersal of large seeded fruits, plantcommunity assembly and diversity in these systems. Data on the spatial...

  16. CASA Forest Cover Change Data Sets

    Science.gov (United States)

    Potter, Christopher S.

    2012-01-01

    Deforestation and forest fires are global land cover changes that can be caused by both natural and human factors. Although monitoring forest fires in near-real time is critical for operational wildfire management, mapping historical wildfires in a spatially explicit fashion is also important for a number of reasons, including climate change studies (e.g., examining the relationship between rising temperatures and frequency of fires), fuel load management (e.g., deciding when and where to conduct controlled burns), and carbon cycle studies (e.g., quantifying how much CO2 is emitted by fires and for emissions reduction efforts under the United Nations programs for Reducing Emissions from Deforestation and Degradation -- REDD).

  17. Modeling Precipitation Dependent Forest Resilience in India

    Science.gov (United States)

    Das, P.; Behera, M. D.; Roy, P. S.

    2018-04-01

    The impact of long term climate change that imparts stress on forest could be perceived by studying the regime shift of forest ecosystem. With the change of significant precipitation, forest may go through density change around globe at different spatial and temporal scale. The 100 class high resolution (60 meter spatial resolution) Indian vegetation type map was used in this study recoded into four broad categories depending on phrenology as (i) forest, (ii) scrubland, (iii) grassland and (iv) treeless area. The percentage occupancy of forest, scrub, grass and treeless were observed as 19.9 %, 5.05 %, 1.89 % and 7.79 % respectively. Rest of the 65.37 % land area was occupied by the cropland, built-up, water body and snow covers. The majority forest cover were appended into a 5 km × 5 km grid, along with the mean annual precipitation taken from Bioclim data. The binary presence and absence of different vegetation categories in relates to the annual precipitation was analyzed to calculate their resilience expressed in probability values ranging from 0 to 1. Forest cover observed having resilience probability (Pr) < 0.3 in only 0.3 % (200 km2) of total forest cover in India, which was 4.3 % < 0.5 Pr. Majority of the scrubs and grass (64.92 % Pr < 0.5) from North East India which were the shifting cultivation lands showing low resilience, having their high tendency to be transform to forest. These results have spatial explicitness to highlight the resilient and non-resilient distribution of forest, scrub and grass, and treeless areas in India.

  18. Remote sensing-based landscape indicators for the evaluation of threatened-bird habitats in a tropical forest.

    Science.gov (United States)

    Singh, Minerva; Tokola, Timo; Hou, Zhengyang; Notarnicola, Claudia

    2017-07-01

    Avian species persistence in a forest patch is strongly related to the degree of isolation and size of a forest patch and the vegetation structure within a patch and its matrix are important predictors of bird habitat suitability. A combination of space-borne optical (Landsat), ALOS-PALSAR (radar), and airborne Light Detection and Ranging (LiDAR) data was used for assessing variation in forest structure across forest patches that had undergone different levels of forest degradation in a logged forest-agricultural landscape in Southern Laos. The efficacy of different remote sensing (RS) data sources in distinguishing forest patches that had different seizes, configurations, and vegetation structure was examined. These data were found to be sensitive to the varying levels of degradation of the different patch categories. Additionally, the role of local scale forest structure variables (characterized using the different RS data and patch area) and landscape variables (characterized by distance from different forest patches) in influencing habitat preferences of International Union for Conservation of Nature (IUCN) Red listed birds found in the study area was examined. A machine learning algorithm, MaxEnt, was used in conjunction with these data and field collected geographical locations of the avian species to identify the factors influencing habitat preference of the different bird species and their suitable habitats. Results show that distance from different forest patches played a more important role in influencing habitat suitability for the different avian species than local scale factors related to vegetation structure and health. In addition to distance from forest patches, LiDAR-derived forest structure and Landsat-derived spectral variables were important determinants of avian habitat preference. The models derived using MaxEnt were used to create an overall habitat suitability map (HSM) which mapped the most suitable habitat patches for sustaining all the

  19. Evaluating Anthropogenic Risk of Grassland and Forest Habitat Degradation using Land-Cover Data

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    Kurt Riitters

    2009-09-01

    Full Text Available The effects of landscape context on habitat quality are receiving increased attention in conservation biology. The objective of this research is to demonstrate a landscape-level approach to mapping and evaluating the anthropogenic risks of grassland and forest habitat degradation by examining habitat context as defined by intensive anthropogenic land uses at multiple spatial scales. A landscape mosaic model classifies a given location according to the amounts of intensive agriculture and intensive development in its surrounding landscape, providing measures of anthropogenic risks attributable to habitat isolation and edge effects at that location. The model is implemented using a land-cover map (0.09 ha/pixel of the conterminous United States and six landscape sizes (4.4, 15.2, 65.6, 591, 5300, and 47800 ha to evaluate the spatial scales of anthropogenic risk. Statistics for grassland and forest habitat are extracted by geographic overlays of the maps of land-cover and landscape mosaics. Depending on landscape size, 81 to 94 percent of all grassland and forest habitat occurs in landscapes that are dominated by natural land-cover including habitat itself. Within those natural-dominated landscapes, 50 percent of grassland and 59 percent of forest is within 590 m of intensive agriculture and/or intensive developed land which is typically a minor component of total landscape area. The conclusion is that anthropogenic risk attributable to habitat patch isolation affects a small proportion of the total grassland or forest habitat area, while the majority of habitat area is exposed to edge effects.

  20. Deforestation Analysis of Riverine Forest of Sindh Using Remote Sensing Techniques

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    Habibullah Abbasi

    2011-07-01

    Full Text Available During recent decades the large scale deterioration of forests and natural resources is an eye opener. The degradation of forests and other natural resources has affected the ecology, environment, health and economy. The ecological problems with living organisms such as animals and plants and environmental problems such as increase in temperature and carbon dioxide, these factors have contributed to change in regional climate, health problems such as skin, eye diseases and sunstroke and economic problems such as loss of income to rural population and resources which depend on forests such as livestock. Therefore, it was necessary to carry out land cover/use research focusing on the monitoring and management of the present and past state of forests cover and other related objects using RS (Remote Sensing technologies. The RS is a way of mapping and monitoring the changes taking place in forests cover and other objects on a continuing basis. Sukkur and Shikarpur riverine forests are vanishing quickly due to the construction of barrages /dams on upper streams to produce hydroelectricity and irrigation installations which reduce the discharge of fresh water into the downstream Indus basin. Moreover, anthropogenic activities, livestock population, increased grazing, load and illegal tree cutting have contributed to this. The riverine forests are turning into barren land and most of the land is used for agriculture. These uncontrolled changes contribute to climate change and global warming. These changes are difficult to monitor and control without using RS technology. Assessment of deforestation of the Sukkur and Shikarpur to find temporal changes in the forests cover from April, 1979 to April, 2009 is presented in this paper. The integrated classes such as water body, grass/agriculture land, dry/barren land and forest cover maps show the temporal changes taking place in the forests cover for the last 30 years period. RS has been employed in the

  1. Bayesian mapping of HIV infection among women of reproductive age in Rwanda.

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    François Niragire

    Full Text Available HIV prevalence is rising and has been consistently higher among women in Rwanda whereas a decreasing national HIV prevalence rate in the adult population has stabilised since 2005. Factors explaining the increased vulnerability of women to HIV infection are not currently well understood. A statistical mapping at smaller geographic units and the identification of key HIV risk factors are crucial for pragmatic and more efficient interventions. The data used in this study were extracted from the 2010 Rwanda Demographic and Health Survey data for 6952 women. A full Bayesian geo-additive logistic regression model was fitted to data in order to assess the effect of key risk factors and map district-level spatial effects on the risk of HIV infection. The results showed that women who had STIs, concurrent sexual partners in the 12 months prior to the survey, a sex debut at earlier age than 19 years, were living in a woman-headed or high-economic status household were significantly associated with a higher risk of HIV infection. There was a protective effect of high HIV knowledge and perception. Women occupied in agriculture, and those residing in rural areas were also associated with lower risk of being infected. This study provides district-level maps of the variation of HIV infection among women of child-bearing age in Rwanda. The maps highlight areas where women are at a higher risk of infection; the aspect that proximate and distal factors alone could not uncover. There are distinctive geographic patterns, although statistically insignificant, of the risk of HIV infection suggesting potential effectiveness of district specific interventions. The results also suggest that changes in sexual behaviour can yield significant results in controlling HIV infection in Rwanda.

  2. Bayesian mapping of HIV infection among women of reproductive age in Rwanda.

    Science.gov (United States)

    Niragire, François; Achia, Thomas N O; Lyambabaje, Alexandre; Ntaganira, Joseph

    2015-01-01

    HIV prevalence is rising and has been consistently higher among women in Rwanda whereas a decreasing national HIV prevalence rate in the adult population has stabilised since 2005. Factors explaining the increased vulnerability of women to HIV infection are not currently well understood. A statistical mapping at smaller geographic units and the identification of key HIV risk factors are crucial for pragmatic and more efficient interventions. The data used in this study were extracted from the 2010 Rwanda Demographic and Health Survey data for 6952 women. A full Bayesian geo-additive logistic regression model was fitted to data in order to assess the effect of key risk factors and map district-level spatial effects on the risk of HIV infection. The results showed that women who had STIs, concurrent sexual partners in the 12 months prior to the survey, a sex debut at earlier age than 19 years, were living in a woman-headed or high-economic status household were significantly associated with a higher risk of HIV infection. There was a protective effect of high HIV knowledge and perception. Women occupied in agriculture, and those residing in rural areas were also associated with lower risk of being infected. This study provides district-level maps of the variation of HIV infection among women of child-bearing age in Rwanda. The maps highlight areas where women are at a higher risk of infection; the aspect that proximate and distal factors alone could not uncover. There are distinctive geographic patterns, although statistically insignificant, of the risk of HIV infection suggesting potential effectiveness of district specific interventions. The results also suggest that changes in sexual behaviour can yield significant results in controlling HIV infection in Rwanda.

  3. SPATIAL DEFORESTATION MODELILNG USING CELLULAR AUTOMATA (CASE STUDY: CENTRAL ZAGROS FORESTS

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    M. Naghdizadegan

    2013-09-01

    Full Text Available Forests have been highly exploited in recent decades in Iran and deforestation is going to be the major environmental concern due to its role in destruction of natural ecosystem and soil cover. Therefore, finding the effective parameters in deforestation and simulation of this process can help the management and preservation of forests. It helps predicting areas of deforestation in near future which is a useful tool for making socioeconomic disciplines in order to prevent deforestation in the area. Recently, GIS technologies are widely employed to support public policies in order to preserve ecosystems from undesirable human activities. The aim of this study is modelling the distribution of forest destruction in part of Central Zagros Mountains and predicting its process in future. In this paper we developed a Cellular Automata (CA model for deforestation process due to its high performance in spatial modelling, land cover change prediction and its compatibility with GIS. This model is going to determine areas with deforestation risk in the future. Land cover maps were explored using high spatial resolution satellite imageries and the forest land cover was extracted. In order to investigate the deforestation modelling, major elements of forest destruction relating to human activity and also physiographic parameters was explored and the suitability map was produced. Then the suitability map in combination with neighbourhood parameter was used to develop the CA model. Moreover, neighbourhood, suitability and stochastic disturbance term were calibrated in order to improve the simulation results. Regarding this, several neighbourhood configurations and different temporal intervals were tested. The accuracy of model was evaluated using satellite image. The results showed that the developed CA model in this research has proper performance in simulation of deforestation process. This model also predicted the areas with high potential for future

  4. Deforestation and Industrial Forest Patterns in Colombia: a Case Study

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    Huo, L. Z.; Boschetti, L.; Sparks, A. M.; Clerici, N.

    2017-12-01

    The recent peace agreement between the government and the Revolutionary Armed Forces of Colombia (FARC) offers new opportunities for peaceful and sustainable development, but at the same time requires a timely effort to protect biological resources, and ecosystem services (Clerici et al., 2016). In this context, we use the 2001-2017 Landsat data record to prototype a methodology to establish a baseline of deforestation, afforestation and industrial forest practices (i.e. establishment and harvest of forest plantations), and to monitor future changes. Two study areas, which have seen considerable deforestation in recent years, were selected: one in the South of the country, at the edge of the Amazon Forest (WRS path 008 row 059) and one in the center, in mixed forest (WRS path 008 row 055). The time series of all the available cloud free Landsat 5, Landsat 7 and Landsat 8 data was classified into a sequence of binary forest/non forest maps using a deep learning model, successfully used in the natural language processing field, trained to detect forest transitions. Recurrent Neural Networks (RNN) is a class of artificial neural network that extends the conventional neural network with loops in the connections (Graves et al., 2013). Unlike a feed-forward neural network, an RNN is able to process the sequential inputs by having a recurrent hidden state whose activation at each step depends on that of the previous steps. In this manner, the RNN provides a good framework to dynamically model time series data, and has been successfully applied to natural language processing in Google (Sutskever et al., 2014). The sequence of forest cover state maps was subsequently post-processed to differentiate between deforestation (e.g. transition from forest to non forest land use) and industrial forest harvest (i.e. timber harvest followed by regrowth), by integrating the detection of temporal patterns, and spatial patterns. References Clerici, N., et al., (2016). Colombia: Dealing

  5. Soil maps, field knowledge, forest inventory and Ecological-Economic Zoning as a basis for agricultural suitability of lands in Minas Gerais elaborated in GIS

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    Vladimir Antonio Silva

    2013-12-01

    Full Text Available Lands (broader concept than soils, including all elements of the environment: soils, geology, topography, climate, water resources, flora and fauna, and the effects of anthropogenic activities of the state of Minas Gerais are in different soil, climate and socio-economics conditions and suitability for the production of agricultural goods is therefore distinct and mapping of agricultural suitability of the state lands is crucial for planning guided sustainability. Geoprocessing uses geographic information treatment techniques and GIS allows to evaluate geographic phenomena and their interrelationships using digital maps. To evaluate the agricultural suitability of state lands, we used soil maps, field knowledge, forest inventories and databases related to Ecological-Economic Zoning (EEZ of Minas Gerais, to develop a map of land suitability in GIS. To do this, we have combined the maps of soil fertility, water stress, oxygen deficiency, vulnerability to erosion and impediments to mechanization. In terms of geographical expression, the main limiting factor of lands is soil fertility, followed by lack of water, impediments to mechanization and vulnerability to erosion. Regarding agricultural suitability, the group 2 (regular suitability for crops is the most comprehensive, representing 45.13% of the state. For management levels A and B, low and moderate technological level, respectively, the most expressive suitability class is the regular, followed by the restricted class and last, the adequate class, while for the management level C (high technological level the predominant class is the restricted. The predominant most intensive use type is for crops, whose area increases substantially with capital investment and technology (management levels B and C.

  6. Estimated carbon emission from recent rapid forest loss in Southeast Asia

    Science.gov (United States)

    Chen, A.; Zeng, Z.; Peng, L.; Fei, S.

    2017-12-01

    Driven by agricultural expansion, industrial logging, oil palm and rubber plantations, and urbanization, Southeast Asia (SEA) is one of the hotspots for tropical deforestation over recent decades. The extent of the tropical SEA deforestation rate, as well as its impacts on carbon cycle and biodiversity, however, is still highly uncertain. In relevant work using high resolution global maps of the 21st-century forest cover, we find tropical SEA lost 22 million hectares, or 9%, of forest area during 2000-2014, a much higher deforestation rate than previously reported. Here we further conduct research investigating carbon emissions from tropical deforestation in SEA with satellite data of forest cover, a global tropical forest biomass map, and Earth system models. Preliminary results suggest that deforestation in SEA causes about 2.8 Tg C emissions to the atmosphere during the same period, also higher than that of previous studies. Meanwhile, carbon emission from deforestation shows high variations across different countries, topography and between the insular and maritime SEA. Indonesia and Malaysia tops in both total carbon loss and loss from per unit land area. Our results indicates that previous studies have underestimated the carbon loss due to deforestation in SEA. And until further effective forest conservation measures can be adopted, tropical SEA will continue playing a role of atmospheric carbon source in the coming decades.

  7. An expert-based approach to forest road network planning by combining Delphi and spatial multi-criteria evaluation.

    Science.gov (United States)

    Hayati, Elyas; Majnounian, Baris; Abdi, Ehsan; Sessions, John; Makhdoum, Majid

    2013-02-01

    Changes in forest landscapes resulting from road construction have increased remarkably in the last few years. On the other hand, the sustainable management of forest resources can only be achieved through a well-organized road network. In order to minimize the environmental impacts of forest roads, forest road managers must design the road network efficiently and environmentally as well. Efficient planning methodologies can assist forest road managers in considering the technical, economic, and environmental factors that affect forest road planning. This paper describes a three-stage methodology using the Delphi method for selecting the important criteria, the Analytic Hierarchy Process for obtaining the relative importance of the criteria, and finally, a spatial multi-criteria evaluation in a geographic information system (GIS) environment for identifying the lowest-impact road network alternative. Results of the Delphi method revealed that ground slope, lithology, distance from stream network, distance from faults, landslide susceptibility, erosion susceptibility, geology, and soil texture are the most important criteria for forest road planning in the study area. The suitability map for road planning was then obtained by combining the fuzzy map layers of these criteria with respect to their weights. Nine road network alternatives were designed using PEGGER, an ArcView GIS extension, and finally, their values were extracted from the suitability map. Results showed that the methodology was useful for identifying road that met environmental and cost considerations. Based on this work, we suggest future work in forest road planning using multi-criteria evaluation and decision making be considered in other regions and that the road planning criteria identified in this study may be useful.

  8. Assessing the Sensitivity of Mountain Forests to Site Degradation in the Northern Limestone Alps, Europe

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    Birgit Reger

    2015-05-01

    Full Text Available Because of some land-use practices (such as overstocking with wild ungulates, historical clear-cuts for mining, and locally persisting forest pasture, protective forests in the montane vegetation belt of the Northern Limestone Alps are now frequently overaged and poorly structured over large areas. Windthrow and bark beetle infestations have generated disturbance areas in which forests have lost their protective functions. Where unfavorable site conditions hamper regeneration for decades, severe soil loss may ensue. To help prioritize management interventions, we developed a geographic information system-based model for assessing sensitivity to site degradation and applied it to 4 test areas in the Northern Limestone Alps of Austria and Bavaria. The model consists of (1 analysis of site conditions and forest stand structures that could increase sensitivity to degradation, (2 evaluation of the sensitivity of sites and stands, and (3 evaluation and mapping of mountain forests' sensitivity to degradation. Site conditions were modeled using regression algorithms with data on site parameters from pointwise soil and vegetation surveys as responses and areawide geodata on climate, relief, and substrate as predictors. The resulting predictor–response relationships were applied to test areas. Stand structure was detected from airborne laser scanning data. Site and stand parameters were evaluated according to their sensitivity to site degradation. Sensitivities of sites and stands were summarized in intermediate-scale sensitivity maps. High sensitivity was identified in 3 test areas with pure limestone and dolomite as the prevailing sensitivity level. Moderately sensitive forests dominate in the final test area, Grünstein, where the bedrock in some strata contains larger amounts of siliceous components (marl, mudstone, and moraines; degraded and slightly sensitive forests were rare or nonexistent in all 4 test areas. Providing a comprehensive overview

  9. Focused sunlight factor of forest fire danger assessment using Web-GIS and RS technologies

    Science.gov (United States)

    Baranovskiy, Nikolay V.; Sherstnyov, Vladislav S.; Yankovich, Elena P.; Engel, Marina V.; Belov, Vladimir V.

    2016-08-01

    Timiryazevskiy forestry of Tomsk region (Siberia, Russia) is a study area elaborated in current research. Forest fire danger assessment is based on unique technology using probabilistic criterion, statistical data on forest fires, meteorological conditions, forest sites classification and remote sensing data. MODIS products are used for estimating some meteorological conditions and current forest fire situation. Geonformation technologies are used for geospatial analysis of forest fire danger situation on controlled forested territories. GIS-engine provides opportunities to construct electronic maps with different levels of forest fire probability and support raster layer for satellite remote sensing data on current forest fires. Web-interface is used for data loading on specific web-site and for forest fire danger data representation via World Wide Web. Special web-forms provide interface for choosing of relevant input data in order to process the forest fire danger data and assess the forest fire probability.

  10. Evaluation of air pollution-related risks for Austrian mountain forests

    International Nuclear Information System (INIS)

    Smidt, Stefan; Herman, Friedl

    2004-01-01

    The present paper describes air pollution status and evaluation of risks related to effects of phytotoxic pollutants in the Austrian mountain forests. The results are based on Austrian networks (Forest Inventory, Forest Damage Monitoring System, Austrian Bioindicator Grid), the Austrian sample plots of the European networks of the UN-ECE (ICP Forests, Level I and Level II) and interdisciplinary research approaches. Based on the monitoring data and on modelling and mapping of Critical Thresholds, the evaluation of risk factors was possible. Cause-effect relationships between air pollution and tree responses were shown by tree-physiological measurements. Sulfur impact, proton and lead input, concentrations of nitrogen oxides, nitrogen input and ozone were evaluated. The risk was demonstrated at a regional and large-scale national level. Especially the increasing O 3 level and the accumulation of Pb with altitude present most serious risk for mountain forests. - Despite strong reduction of emissions in Europe, pollutants are still a potential stress factor, especially for sensitive mountain forest ecosystems in Austria

  11. Using the Landsat Archive to Estimate and Map Changes in Agriculture, Forests, and other Land Cover Types in East Africa

    Science.gov (United States)

    Healey, S. P.; Oduor, P.; Cohen, W. B.; Yang, Z.; Ouko, E.; Gorelick, N.; Wilson, S.

    2017-12-01

    Every country's land is distributed among different cover types, such as: agriculture; forests; rangeland; urban areas; and barren lands. Changes in the distribution of these classes can inform us about many things, including: population pressure; effectiveness of preservation efforts; desertification; and stability of the food supply. Good assessment of these changes can also support wise planning, use, and preservation of natural resources. We are using the Landsat archive in two ways to provide needed information about land cover change since the year 2000 in seven East African countries (Ethiopia, Kenya, Malawi, Rwanda, Tanzania, Uganda, and Zambia). First, we are working with local experts to interpret historical land cover change from historical imagery at a probabilistic sample of 2000 locations in each country. This will provide a statistical estimate of land cover change since 2000. Second, we will use the same data to calibrate and validate annual land cover maps for each country. Because spatial context can be critical to development planning through the identification of hot spots, these maps will be a useful complement to the statistical, country-level estimates of change. The Landsat platform is an ideal tool for mapping land cover change because it combines a mix of appropriate spatial and spectral resolution with unparalleled length of service (Landsat 1 launched in 1972). Pilot tests have shown that time series analysis accessing the entire Landsat archive (i.e., many images per year) improves classification accuracy and stability. It is anticipated that this project will meet the civil needs of both governmental and non-governmental users across a range of disciplines.

  12. Mapping critical levels of ozone, sulfur dioxide and nitrogen oxide for crops, forests and natural vegetation in the United States

    International Nuclear Information System (INIS)

    Rosenbaum, B.J.; Strickland, T.C.; McDowell, M.K.

    1994-01-01

    Air pollution abatement strategies for controlling nitrogen dioxide, sulfur dioxide, and ozone emissions in the United States focus on a 'standards-based' approach. This approach places limits on air pollution by maintaining a baseline value for air quality, no matter what the ecosystem can or cannot withstand. This paper, presents example critical levels maps for the conterminous U.S. developed using the 'effects-based' mapping approach as defined by the United Nations Economic Commission for Europe's Convention on Long-Range Transboundary Air Pollution, Task Force on Mapping. This approach emphasizes the pollution level or load capacity an ecosystem can accommodate before degradation occurs, and allows for analysis of cumulative effects. Presents the first stage of an analysis that reports the distribution of exceedances of critical levels for NO 2 , SO 2 , and O 3 in sensitive forest, crop, and natural vegetation ecosystems in the contiguous United States. It is concluded that extrapolation to surrounding geographic areas requires the analysis of diverse and compounding factors that preclude simple extrapolation methods. Pollutant data depicted in this analysis are limited to locationally specific data, and would be enhanced by utilizing spatial statistics, along with converging associated anthropogenic and climatological factors. Values used for critical levels were derived from current scientific knowledge. While not intended to be a definitive value, adjustments will occur as the scientific community gains new insight to pollutant/receptor relationships. We recommend future analysis to include a refinement of sensitive receptor data coverages and to report relative proportions of exceedances at varying grid scales. 27 refs., 4 figs., 1 tab

  13. [Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

    Science.gov (United States)

    Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

    2015-11-01

    With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

  14. Allometric Scaling and Resource Limitations Model of Total Aboveground Biomass in Forest Stands: Site-scale Test of Model

    Science.gov (United States)

    CHOI, S.; Shi, Y.; Ni, X.; Simard, M.; Myneni, R. B.

    2013-12-01

    Sparseness in in-situ observations has precluded the spatially explicit and accurate mapping of forest biomass. The need for large-scale maps has raised various approaches implementing conjugations between forest biomass and geospatial predictors such as climate, forest type, soil property, and topography. Despite the improved modeling techniques (e.g., machine learning and spatial statistics), a common limitation is that biophysical mechanisms governing tree growth are neglected in these black-box type models. The absence of a priori knowledge may lead to false interpretation of modeled results or unexplainable shifts in outputs due to the inconsistent training samples or study sites. Here, we present a gray-box approach combining known biophysical processes and geospatial predictors through parametric optimizations (inversion of reference measures). Total aboveground biomass in forest stands is estimated by incorporating the Forest Inventory and Analysis (FIA) and Parameter-elevation Regressions on Independent Slopes Model (PRISM). Two main premises of this research are: (a) The Allometric Scaling and Resource Limitations (ASRL) theory can provide a relationship between tree geometry and local resource availability constrained by environmental conditions; and (b) The zeroth order theory (size-frequency distribution) can expand individual tree allometry into total aboveground biomass at the forest stand level. In addition to the FIA estimates, two reference maps from the National Biomass and Carbon Dataset (NBCD) and U.S. Forest Service (USFS) were produced to evaluate the model. This research focuses on a site-scale test of the biomass model to explore the robustness of predictors, and to potentially improve models using additional geospatial predictors such as climatic variables, vegetation indices, soil properties, and lidar-/radar-derived altimetry products (or existing forest canopy height maps). As results, the optimized ASRL estimates satisfactorily

  15. Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA

    Science.gov (United States)

    Wenli Huang; Anu Swatantran; Kristofer Johnson; Laura Duncanson; Hao Tang; Jarlath O' Neil Dunne; George Hurtt; Ralph Dubayah

    2015-01-01

    Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-...

  16. Mapping wildfire and clearcut harvest disturbances in boreal forests with Landsat time series data

    Science.gov (United States)

    Todd Schroeder; Michael A. Wulder; Sean P. Healey; Gretchen G. Moisen

    2011-01-01

    Information regarding the extent, timing andmagnitude of forest disturbance are key inputs required for accurate estimation of the terrestrial carbon balance. Equally important for studying carbon dynamics is the ability to distinguish the cause or type of forest disturbance occurring on the landscape. Wildfire and timber harvesting are common disturbances occurring in...

  17. Using a remote sensing-based, percent tree cover map to enhance forest inventory estimation

    Science.gov (United States)

    Ronald E. McRoberts; Greg C. Liknes; Grant M. Domke

    2014-01-01

    For most national forest inventories, the variables of primary interest to users are forest area and growing stock volume. The precision of estimates of parameters related to these variables can be increased using remotely sensed auxiliary variables, often in combination with stratified estimators. However, acquisition and processing of large amounts of remotely sensed...

  18. Discrimination between acute and chronic decline of Central European forests using map algebra of the growth condition and forest biomass fuzzy sets: A case study.

    Science.gov (United States)

    Samec, Pavel; Caha, Jan; Zapletal, Miloš; Tuček, Pavel; Cudlín, Pavel; Kučera, Miloš

    2017-12-01

    Forest decline is either caused by damage or else by vulnerability due to unfavourable growth conditions or due to unnatural silvicultural systems. Here, we assess forest decline in the Czech Republic (Central Europe) using fuzzy functions, fuzzy sets and fuzzy rating of ecosystem properties over a 1×1km grid. The model was divided into fuzzy functions of the abiotic predictors of growth conditions (F pred including temperature, precipitation, acid deposition, soil data and relative site insolation) and forest biomass receptors (F rec including remote sensing data, density and volume of aboveground biomass, and surface humus chemical data). Fuzzy functions were designed at the limits of unfavourable, undetermined or favourable effects on the forest ecosystem health status. Fuzzy sets were distinguished through similarity in a particular membership of the properties at the limits of the forest status margins. Fuzzy rating was obtained from the least difference of F pred -F rec . Unfavourable F pred within unfavourable F rec indicated chronic damage, favourable F pred within unfavourable F rec indicated acute damage, and unfavourable F pred within favourable F rec indicated vulnerability. The model in the 1×1km grid was validated through spatial intersection with a point field of uniform forest stands. Favourable status was characterised by soil base saturation (BS)>50%, BCC/Al>1, C org >1%, MgO>6g/kg, and nitrogen depositionforests had BS humus 46-60%, BCC/Al 9-20 and NDVI≈0.42. Chronic forest damage occurs in areas with low temperatures, high nitrogen deposition, and low soil BS and C org levels. In the Czech Republic, 10% of forests were considered non-damaged and 77% vulnerable, with damage considered acute in 7% of forests and chronic in 5%. The fuzzy model used suggests that improvement in forest health will depend on decreasing environmental load and restoration concordance between growth conditions and tree species composition. Copyright © 2017 Elsevier

  19. National Scale Monitoring Reporting and Verification of Deforestation and Forest Degradation in Guyana

    Science.gov (United States)

    Bholanath, P.; Cort, K.

    2015-04-01

    Monitoring deforestation and forest degradation at national scale has been identified as a national priority under Guyana's REDD+ Programme. Based on Guyana's MRV (Monitoring Reporting and Verification) System Roadmap developed in 2009, Guyana sought to establish a comprehensive, national system to monitor, report and verify forest carbon emissions resulting from deforestation and forest degradation in Guyana. To date, four national annual assessments have been conducted: 2010, 2011, 2012 and 2013. Monitoring of forest change in 2010 was completed with medium resolution imagery, mainly Landsat 5. In 2011, assessment was conducted using a combination of Landsat (5 and 7) and for the first time, 5m high resolution imagery, with RapidEye coverage for approximately half of Guyana where majority of land use changes were taking place. Forest change in 2013 was determined using high resolution imagery for the whole of Guyana. The current method is an automated-assisted process of careful systematic manual interpretation of satellite imagery to identify deforestation based on different drivers of change. The minimum mapping unit (MMU) for deforestation is 1 ha (Guyana's forest definition) and a country-specific definition of 0.25 ha for degradation. The total forested area of Guyana is estimated as 18.39 million hectares (ha). In 2012 as planned, Guyana's forest area was reevaluated using RapidEye 5 m imagery. Deforestation in 2013 is estimated at 12 733 ha which equates to a total deforestation rate of 0.068%. Significant progress was made in 2012 and 2013, in mapping forest degradation. The area of forest degradation as measured by interpretation of 5 m RapidEye satellite imagery in 2013 was 4 352 ha. All results are subject to accuracy assessment and independent third party verification.

  20. Forest Delineation Based on Airborne LIDAR Data

    Directory of Open Access Journals (Sweden)

    Norbert Pfeifer

    2012-03-01

    Full Text Available The delineation of forested areas is a critical task, because the resulting maps are a fundamental input for a broad field of applications and users. Different national and international forest definitions are available for manual or automatic delineation, but unfortunately most definitions lack precise geometrical descriptions for the different criteria. A mandatory criterion in forest definitions is the criterion of crown coverage (CC, which defines the proportion of the forest floor covered by the vertical projection of the tree crowns. For loosely stocked areas, this criterion is especially critical, because the size and shape of the reference area for calculating CC is not clearly defined in most definitions. Thus current forest delineations differ and tend to be non-comparable because of different settings for checking the criterion of CC in the delineation process. This paper evaluates a new approach for the automatic delineation of forested areas, based on airborne laser scanning (ALS data with a clearly defined method for calculating CC. The new approach, the ‘tree triples’ method, is based on defining CC as a relation between the sum of the crown areas of three neighboring trees and the area of their convex hull. The approach is applied and analyzed for two study areas in Tyrol, Austria. The selected areas show a loosely stocked forest at the upper timberline and a fragmented forest on the hillside. The fully automatic method presented for delineating forested areas from ALS data shows promising results with an overall accuracy of 96%, and provides a beneficial tool for operational applications.