WorldWideScience

Sample records for forest mapping debuting

  1. Rapid mapping of hurricane damage to forests

    Science.gov (United States)

    Erik M. Nielsen

    2009-01-01

    The prospects for producing rapid, accurate delineations of the spatial extent of forest wind damage were evaluated using Hurricane Katrina as a test case. A damage map covering the full spatial extent of Katrina?s impact was produced from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery using higher resolution training data. Forest damage...

  2. 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...

  3. 75 FR 16719 - Information Collection; Forest Landscape Value and Special Place Mapping for National Forest...

    Science.gov (United States)

    2010-04-02

    ...; ] DEPARTMENT OF AGRICULTURE Forest Service Information Collection; Forest Landscape Value and Special Place Mapping for National Forest Planning AGENCY: Forest Service, USDA. ACTION: Notice; request for comment. SUMMARY: In accordance with the Paperwork Reduction Act of 1995, the Forest Service is seeking comments...

  4. US Forest Service Motor Vehicle Use Map: Roads and Trails

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting Forest Service roads and trails that are designated for motor vehicle use under the official U.S. Government Code of Federal...

  5. 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.

  6. 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.

  7. 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...

  8. A Circa 2010 Thirty Meter Resolution Forest Map for China

    Directory of Open Access Journals (Sweden)

    Congcong Li

    2014-06-01

    Full Text Available This study examines the suitability of 30 m Landsat Thematic Mapper (TM, 250 m time-series Moderate Resolution Imaging Spectrometer (MODIS Enhanced Vegetation Index (EVI and other auxiliary datasets for mapping forest extent in China at 30 m resolution circa 2010. We calculated numerous spectral features, EVI time series, and topographical features that are helpful for forest/non-forest distinction. In this research, extensive efforts have been made in developing training samples over difficult to map or complex regions. Scene by scene quality checking was done on the initial forest extent results and low quality results were refined until satisfactory. Based on the forest extent mask, we classified the forested area into 6 types (evergreen/deciduous broadleaf, evergreen/deciduous needleleaf, mixed forests, and bamboos. Accuracy assessment of our forest/non-forest classification using 2195 test sample units independent of the training sample indicates that the producer’s accuracy (PA and user’s accuracy (UA are 92.0% and 95.7%, respectively. According to this map, the total forested area in China was 164.90 million ha (Mha circa 2010. It is close to the forest area of 7th National Forest Resource Inventory with the same definition of forest. The overall accuracy for the more detailed forest type classification is 72.7%.

  9. Mapping Terpenes over the Teakettle Experimental Forest

    Science.gov (United States)

    Tycner, J.; Ustin, S.; Grigsby, S.

    2015-12-01

    Terpenes are a category of biogenic volatile organic compounds (BVOC) produced by many plants, most notably coniferous plants. Commonly, these terpenes are aromatic compounds. The intensity of terpene emission varies depending greatly on light and temperature. Through remote sensing data as well as ASD spectroradiometry data this study focuses on locating sources of terpene emissions in the Teakettle Experimental Forest. These emissions are of particular concern because of their influence on the chemical concentration of the lower troposphere, as well as being an indicator of tree health. A novel approach has been designed through this study in order to locate and further understand these terpene emissions. Terpenes such as camphene have been reported to have subtle spectral features located at around 1.7 μm. For the first time, a map of terpene sources has been constructed by accentuating this particular feature. A continuum interpolated band ratio (CIBR) was used in order to compute a relative abundance of terpenes from the AVIRIS data. The CIBR equation showed promise, as terpenes were most strongly concentrated in areas of coniferous vegetation (a primary source of terpenes) and were less prominent over bodies of water or industrialized areas. The greatest concentrations were focused over treetops and other woody vegetation. Although it is known that terpenes have weak absorption features in the SWIR, there is little information available regarding the mapping of terpene emissions. This project addresses a novel approach to observing biochemical components in the lower troposphere and could potentially give more information to explain the health of forest ecosystems.

  10. Choice of forest map has implications for policy analysis

    DEFF Research Database (Denmark)

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

    2012-01-01

    and harmonised approach at the European level. However, they possess different characteristics in terms of spatial detail or thematic accuracy. Little attention has been paid to the effect of these characteristics on simulation models and the resultant policy implications. In this study we tested whether...... the choice of a forest map has substantial influence on model output, i.e. if output differences can be related to the input differences. A sensitivity analysis of the spatially explicit Global Forest Model (G4M) was performed using four different forest maps: the pan-European high resolution forest...... utilization of forest biomass. The sensitivity analysis showed that the choice of the forest cover map has a major influence on the model outputs in particular at the country-level, while having less influence at the EU27 level. Differences between the input datasets are strongly reflected in the outputs...

  11. Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information

    Science.gov (United States)

    J. A. Blackard; M. V. Finco; E. H. Helmer; G. R. Holden; M. L. Hoppus; D.M. Jacobs; A. J. Lister; G. G. Moisen; M. D. Nelson; R. Riemann; B. Ruefenacht; D. Salajanu; D. L. Weyermann; K. C. Winterberger; T. J. Brandeis; R. L. Czaplewski; R. E. McRoberts; P. L. Patterson; R. P. Tymcio

    2008-01-01

    A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, we developed models relating field-measured response variables to plot attributes...

  12. Mapping spatial distribution of forest age in China

    Science.gov (United States)

    Zhang, Yuan; Yao, Yitong; Wang, Xuhui; Liu, Yongwen; Piao, Shilong

    2017-03-01

    Forest stand age is a meaningful metric, which reflects the past disturbance legacy, provides guidelines for forest management practices, and is an important factor in qualifying forest carbon cycles and carbon sequestration potential. Reliable large-scale forest stand age information with high spatial resolutions, however, is difficult to obtain. In this study, we developed a top-down method to downscale the provincial statistics of national forest inventory data into 1 km stand age map using climate data and light detection and ranging-derived forest height. We find that the distribution of forest stand age in China is highly heterogeneous across the country, with a mean value of 42.6 years old. The relatively young stand age for Chinese forests is mostly due to the large proportion of newly planted forests (0-40 years old), which are more prevailing in south China. Older forests (stand age > 60 years old) are more frequently found in east Qinghai-Tibetan Plateau and the central mountain areas of west and northeast China, where human activities are less intensive. Among the 15 forest types, forests dominated by species of Taxodiaceae, with the exception of Cunninghamia lanceolata stands, have the oldest mean stand age (136 years), whereas Pinus massoniana forests are the youngest (18 years). We further identified uncertainties associated with our forest age map, which are high in west and northeast China. Our work documents the distribution of forest stand age in China at a high resolution which is useful for carbon cycle modeling and the sustainable use of China's forest resources.

  13. Mapping forest soil organic matter on New Jersey's coastal plain

    Science.gov (United States)

    Brian J. Clough; Edwin J. Green; Richard B. Lathrop

    2012-01-01

    Managing forest soil organic matter (SOM) stocks is a vital strategy for reducing the impact of anthropogenic carbon dioxide emissions. However, the SOM pool is highly variable, and developing accurate estimates to guide management decisions has remained a difficult task. We present the results of a spatial model designed to map soil organic matter for all forested...

  14. 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.

  15. FOREST COVER MAPPING IN ISKANDAR MALAYSIA USING SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    K. D. Kanniah

    2016-09-01

    Full Text Available 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.

  16. 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...

  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 aboveground forest biomass combining dendrometric data and spectral signature of forest species

    Science.gov (United States)

    Avocat, H.; Tourneux, F.

    2013-12-01

    Accurate measures and explicit spatial representations of forest biomass compose an important aspect to model the forest productivity and crops, and to implement sustainable forest management. Several methods have been developed to estimate and to map forest biomass, combining point-sources measurements of biophysical variables such as diameter-at-breast height (DBH), tree height, crown size, crown length, crown volume and remote sensing data (spectral vegetation index values). In this study, we propose a new method for aboveground biomass (AGB) mapping of forests and isolated trees. This method is tested on a 1100 km2 area located in the eastern France. In contrast to most of studies, our model is not calibrated using field plot measurements or point-source inventory data. The primary goal of this model is to propose an accessible and reproducible method for AGB mapping of temperate forests, by combining standard biomass values coming from bibliography and remotely sensed data. This method relies on three steps. (1) The first step consists of produce a map of wooded areas including small woods and isolated trees, and to identify the major forest stands. To do this, we use an unsupervised classification of a Landsat 7 ETM+ image. Results are compared and improved with various land cover data. (2) The second step consists of extract the normalized difference vegetation index (NDVI) values of main forest stands. (3) Finally, these values are combined with standard AGB values provided by bibliography, to calibrate four AGB estimation models of different forest types (broadleaves, coniferous, coppices, and mixed stands). This method provides a map of aboveground biomass for forests and isolated trees with a 30 meters spatial resolution. Results demonstrate that 71 % of AGB values for hardwoods vary between 143 and 363 t.ha-1, i.e. × 1 standard deviation around the average. For coniferous stands, most of values of AGB range from 167 to 256 t.ha-1.

  19. 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

  20. Estimation of Stand Height and Forest Volume Using High Resolution Stereo Photography and Forest Type Map

    Science.gov (United States)

    Kim, K. M.

    2016-06-01

    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.

  1. 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.

  2. Current state of forest mapping with Landsat data in Siberia

    Science.gov (United States)

    Maksyutov, Shamil; Sedykh, Vladimir; Kuzmenko, Ekaterina; Farber, Sergey; Kalinicheva, Svetlana; Fedorov, Alexander; Schepaschenko, Dmitry

    2016-04-01

    We review a current state of a forest type mapping with Landsat data in Siberia. Target algorithm should be based on dynamic vegetation approach to be applicable to the analysis of the forest type distribution for Siberia, aiming at capability of mapping Siberian forest landscapes for applications such as predicting response of forest composition to climate change. We present data for several areas in West Siberian middle taiga, Central Siberia and East Siberia near Yakutsk. Analysis of the field survey, forest inventory data was made to produce forest type classification accounting for several stages for forest succession and variations in habitats and landforms. Supervised classification was applied to the areas were the ground truth and inventory data are available, including several limited area maps and vegetation survey transects. In Laryegan basin in West Siberia the upland forest areas are dominated by mix of Scots pine on sandy soils and Siberian pine with presence of fir and spruce on the others. Abundance of Scots pine decreases to the west due to change in soils. Those types are separable using Landsat spectral data. In the permafrost area around Yakutsk the most widespread succession type is birch to larch. Three stages of the birch to larch succession are detectable from Landsat image. When Landsat data is used in both West and East Siberia, distinction between deciduous broad-leaved species (birch, aspen, and willow) is generally difficult. Similar problem exist for distinguishing between dark coniferous species (Siberian pine, fir and spruce). Image classification can be improved by applying landform type analysis, such as separation into floodplain, terrace, sloping hills. Additional layers of information can be a promising way to complement Landsat data.

  3. 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.

  4. Mapping regional forest fire probability using artificial neural network model in a Mediterranean forest ecosystem

    Directory of Open Access Journals (Sweden)

    Onur Satir

    2016-09-01

    Full Text Available Forest fires are one of the most important factors in environmental risk assessment and it is the main cause of forest destruction in the Mediterranean region. Forestlands have a number of known benefits such as decreasing soil erosion, containing wild life habitats, etc. Additionally, forests are also important player in carbon cycle and decreasing the climate change impacts. This paper discusses forest fire probability mapping of a Mediterranean forestland using a multiple data assessment technique. An artificial neural network (ANN method was used to map forest fire probability in Upper Seyhan Basin (USB in Turkey. Multi-layer perceptron (MLP approach based on back propagation algorithm was applied in respect to physical, anthropogenic, climate and fire occurrence datasets. Result was validated using relative operating characteristic (ROC analysis. Coefficient of accuracy of the MLP was 0.83. Landscape features input to the model were assessed statistically to identify the most descriptive factors on forest fire probability mapping using the Pearson correlation coefficient. Landscape features like elevation (R = −0.43, tree cover (R = 0.93 and temperature (R = 0.42 were strongly correlated with forest fire probability in the USB region.

  5. 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.

  6. Mapping Successional Stages in a Wet Tropical Forest Using Landsat ETM+ and Forest Inventory Data

    Science.gov (United States)

    Goncalves, Fabio G.; Yatskov, Mikhail; dos Santos, Joao Roberto; Treuhaft, Robert N.; Law, Beverly E.

    2010-01-01

    In 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 wet tropical 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 height 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 (12.9%). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and advanced successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels.

  7. Mapping Successional Stages in a Wet Tropical Forest Using Landsat ETM+ and Forest Inventory Data

    Science.gov (United States)

    Goncalves, Fabio G.; Yatskov, Mikhail; dos Santos, Joao Roberto; Treuhaft, Robert N.; Law, Beverly E.

    2010-01-01

    In 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 wet tropical 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 height 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 (12.9%). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and advanced successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels.

  8. Mapping forest succesion types in Siberia with Landsat data

    Science.gov (United States)

    Maksyutov, S. S.; Sedykh, V.; Kleptsova, I.; Frolov, A.; Silaev, A.; Kuzmenko, E.; Farber, S.; Kuzmik, N.; Sokolov, V. A.; Fedorov, A.; Nikolaeva, S.

    2013-12-01

    We develop a forest typology system based on dynamic vegetation approach and apply it to the analysis of the forest type distribution for several test areas in Siberia, aiming at capability of mapping whole Siberian forests based on Landsat data. Test region locations are: two in West Siberian middle taiga (Laryegan and Nyagan), one in Central Siberia and one in East Siberia near Yakutsk. The ground truth data are based on analysis of the field survey, forest inventory data from the point of view of the successional forest type classification. Supervised classification was applied to the areas covered with analysis of the ground truth and inventory data, using several limited area maps and vegetation survey transects published in literature. In Laryegan basin the upland forest areas are dominated (as climax forest species) by Scots pine on sandy soils and Siberian pine with presence of fir and spruce on the others. Those types are separable using Landsat spectral data alone. In the permafrost area around Yakutsk the most widespread succession type is birch to larch succession. Three stages of the birch to larch succession are detectable from Landsat image. When Landsat data is used in both West and East Siberia, distinction between deciduous broad-leaved species (birch, aspen, and willow) is difficult due to similarity in spectral signatures. Same problem exist for distinguishing between dark coniferous species (Siberian pine, fir and spruce). Image classification can be improved by applying landscape type analysis, such as separation into floodplain, terrace, sloping hills. Additional layers of information seem to be a promising way to complement Landsat data, including SAR-based biomass maps and terrain data

  9. 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.

  10. Mapping hardwood forests through a two-stage unsupervised classification by integrating Landsat Thematic Mapper and forest inventory data

    Science.gov (United States)

    Shao, Gang; Pauli, Benjamin P.; Haulton, G. Scott; Zollner, Patrick A.; Shao, Guofan

    2014-01-01

    Sound forest management requires accurate forest maps at an appropriate scale. Forest cover data developed at a national scale may be too coarse for forest management at a local level. We demonstrated a two-stage unsupervised classification, integrating Continuous Forest Inventory (CFI) data and Landsat imageries, to classify forest types for Indiana State Forests (ISF) and 8-km surrounding areas. In the first stage, an automatic unsupervised classification assisted by CFI data was applied in ISF. In the second stage, the resultant forest cover information from the first stage was used to expand the classification area into the 8-km surrounding areas. Splitting the classification procedure into two stages made it possible to expand the classification area beyond the coverage of the CFI data. This data-aided unsupervised classification approach increased the repeatability of forest mapping. The resultant map contains five forest types: conifer, conifer-hardwood, maple, mixed hardwood, and oak-hickory forests. The overall accuracy was 81.9%, and the total disagreement was 0.176. The accuracies of conifer, conifer-hardwood, maple, mixed hardwood, and oak-hickory forests were 81.6, 63.4, 75.0, 33.3, and 90%, respectively. This forest mapping technique is suitable for automated mapping of forest areas where extensive plot data are available.

  11. Mapping wetland and forest landscapes in Siberia with Landsat data

    Science.gov (United States)

    Maksyutov, Shamil; Kleptsova, Irina; Glagolev, Mikhail; Sedykh, Vladimir; Kuzmenko, Ekaterina; Silaev, Anton; Frolov, Alexander; Nikolaeva, Svetlana; Fedorov, Alexander

    2014-05-01

    Landsat data availability provides opportunity for improving the knowledge of the Siberian ecosystems necessary for quantifying the response of the regional carbon cycle to the climate change. We developed a new wetland map based on Landsat data for whole West Siberia aiming at scaling up the methane emission observations. Mid-summer Landsat scenes were used in supervised classification method, based on ground truth data obtained during multiple field surveys. The method allows distinguishing following wetland types: pine-dwarf shrubs-sphagnum bogs or ryams, ridge-hollows complexes, shallow-water complexes, sedge-sphagnum poor fens, herbaceous-sphagnum poor fens, sedge-(moss) poor fens and fens, wooded swamps or sogra, palsa complexes. In our estimates wetlands cover 36% of the taiga area. Total methane emission from WS taiga mires is estimated as 3.6 TgC/yr,which is 77% larger as compared to the earlier estimate based on partial Landsat mapping combined with low resolution map due to higher fraction of fen area. We make an attempt to develop a forest typology system useful for a dynamic vegetation modeling and apply it to the analysis of the forest type distribution for several test areas in West and East Siberia, aiming at capability of mapping whole Siberian forests based on Landsat data. Test region locations are: two in West Siberian middle taiga (Laryegan and Nyagan), and one in East Siberia near Yakutsk. The ground truth data are based on analysis of the field survey, forest inventory data from the point of view of the successional forest type classification. Supervised classification was applied to the areas where ample ground truth and inventory data are available, using several limited area maps and vegetation survey. In Laryegan basin the upland forest areas are dominated (as climax forest species) by Scots pine on sandy soils and Siberian pine with presence of fir and spruce on the others. Those types are separable using Landsat spectral data alone. In

  12. 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. PMID:24489686

  13. 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...

  14. 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…

  15. TEDA·MSD’s Beijing Debut

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    0n April 20, the Modern Service District (MSD) of the Tianjin Economic-Technological Development Area (TEDA) held a property promotion meeting in Beijing. Leaders of TEDA Development Co. and its business partners in Beijing attended the event. MSD’s Beijing debut signals

  16. Mapping organic carbon stocks of Swiss forest soil

    Science.gov (United States)

    Nussbaum, M.; Papritz, A.; Baltensweiler, A.; Walthert, L.

    2012-04-01

    Carbon (C) sequestration into forest sinks offsets greenhouse gas emissions under the Kyoto protocol. Therefore, quantifying C stocks and fluxes in forest ecosystems is of interest for reporting greenhouse gas emissions. In Switzerland, the National Forest Inventory offers comprehensive data to quantify the above ground forest biomass and its change in time. Estimating stocks of soil organic C (SOC) in forests is more difficult because of its high spatial variability. To date the greenhouse gas inventory relies only on sparse data and regionally differentiated predictions of SOC stocks in forest soils are currently not possible. Recently, more soil data and new explanatory variables for statistical modeling like high resolution elevation data and satellite images became available. Based on data from 1'033 sites, we modeled SOC stocks to a depth of 1 m including the organic layer for the Swiss forested area. We used a novel robust restricted maximum likelihood method to fit a linear regression model with spatially correlated errors to the C stock data. For the regression analysis we used a broad range of covariates derived from climate data (precipitation, temperature, radiation), two elevation models (resolutions 25 and 2 m) and spectral variables representing vegetation. Furthermore, the main cartographic categories of an overview soil map were used to broadly represent the parent material. The numerous covariates, that partly correlated strongly, were reduced to a first subset using LASSO (Least Absolute Shrinkage and Selection Operator). This subset of covariates was then further reduced based on cross validation of the robustly fitted spatial model. The levels of categorical covariates were partly aggregated during this process and interactions between covariates were explored to account for nonlinear dependence of C stocks on the covariates. Using the final model, robust kriging prediction and error maps were computed with a resolution of one hectare.

  17. 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

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

    Science.gov (United States)

    Dong, Jinwei; Xiao, Xiangming; Sheldon, Sage; Biradar, Chandrashekhar; Zhang, Geli; Duong, Nguyen Dinh; Hazarika, Manzul; Wikantika, Ketut; Takeuhci, Wataru; Moore, Berrien

    2014-01-01

    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 biodiversity.

  19. Forest Roads Mapped Using LiDAR in Steep Forested Terrain

    Directory of Open Access Journals (Sweden)

    Russell A. White

    2010-04-01

    Full Text Available LiDAR-derived digital elevation models can reveal road networks located beneath dense forest canopy. This study tests the accuracy of forest road characteristics mapped using LiDAR in the Santa Cruz Mountains, CA. The position, gradient, and total length of a forest haul road were accurately extracted using a 1 m DEM. In comparison to a field-surveyed centerline, the LiDAR-derived road exhibited a positional accuracy of 1.5 m, road grade measurements within 0.53% mean absolute difference, and total road length within 0.2% of the field-surveyed length. Airborne LiDAR can provide thorough and accurate road inventory data to support forest management and watershed assessment activities.

  20. 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

  1. 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

  2. Mapping forest fire risk zones with spatial data and principal component analysis

    Institute of Scientific and Technical Information of China (English)

    XU; Dong; Guofan; Shao; DAI; Limin; HAO; Zhanqing; TANG; Lei; WANG; Hui

    2006-01-01

    By integrating forest inventory data with remotely sensed data, new data layers for factors that affect forest fire potentials were generated for Baihe Forestry Bureau in Jilin Province of China. The principle component analysis was used to sort out the relationships between forest fire potentials and environmental factors. The classifications of these factors were performed with GIS, generating three maps: a fuel-based fire risk map, a topography-based fire risk map, and an anthropogenic-factor fire risk map. These three maps were then synthesized to generate the final fire risk map. The linear regression method was used to analyze the relationship between an area-weighted value of forest fire risks and the frequency of historical forest fires at each forest farm. The results showed that the most important factor contributing to forest fire ignition was topography, followed by anthropogenic factors.

  3. Mapping Deforestation area in North Korea Using Phenology-based Multi-Index and Random Forest

    Science.gov (United States)

    Jin, Y.; Sung, S.; Lee, D. K.; Jeong, S.

    2016-12-01

    Forest ecosystem provides ecological benefits to both humans and wildlife. Growing global demand for food and fiber is accelerating the pressure on the forest ecosystem in whole world from agriculture and logging. In recently, North Korea lost almost 40 % of its forests to crop fields for food production and cut-down of forest for fuel woods between 1990 and 2015. It led to the increased damage caused by natural disasters and is known to be one of the most forest degraded areas in the world. The characteristic of forest landscape in North Korea is complex and heterogeneous, the major landscape types in the forest are hillside farm, unstocked forest, natural forest and plateau vegetation. Remote sensing can be used for the forest degradation mapping of a dynamic landscape at a broad scale of detail and spatial distribution. Confusion mostly occurred between hillside farmland and unstocked forest, but also between unstocked forest and forest. Most previous forest degradation that used focused on the classification of broad types such as deforests area and sand from the perspective of land cover classification. The objective of this study is using random forest for mapping degraded forest in North Korea by phenological based vegetation index derived from MODIS products, which has various environmental factors such as vegetation, soil and water at a regional scale for improving accuracy. The model created by random forest resulted in an overall accuracy was 91.44%. Class user's accuracy of hillside farmland and unstocked forest were 97.2% and 84%%, which indicate the degraded forest. Unstocked forest had relative low user accuracy due to misclassified hillside farmland and forest samples. Producer's accuracy of hillside farmland and unstocked forest were 85.2% and 93.3%, repectly. In this case hillside farmland had lower produce accuracy mainly due to confusion with field, unstocked forest and forest. Such a classification of degraded forest could supply essential

  4. Mapping the Philippines' mangrove forests using Landsat imagery

    Science.gov (United States)

    Long, J.B.; Giri, C.

    2011-01-01

    Current, accurate, and reliable information on the areal extent and spatial distribution of mangrove forests in the Philippines is limited. Previous estimates of mangrove extent do not illustrate the spatial distribution for the entire country. This study, part of a global assessment of mangrove dynamics, mapped the spatial distribution and areal extent of the Philippines' mangroves circa 2000. We used publicly available Landsat data acquired primarily from the Global Land Survey to map the total extent and spatial distribution. ISODATA clustering, an unsupervised classification technique, was applied to 61 Landsat images. Statistical analysis indicates the total area of mangrove forest cover was approximately 256,185 hectares circa 2000 with overall classification accuracy of 96.6% and a kappa coefficient of 0.926. These results differ substantially from most recent estimates of mangrove area in the Philippines. The results of this study may assist the decision making processes for rehabilitation and conservation efforts that are currently needed to protect and restore the Philippines' degraded mangrove forests. ?? 2011 by the authors; licensee MDPI, Basel, Switzerland.

  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. Mapping dynamics of deforestation and forest degradation in tropical forests using radar satellite data

    DEFF Research Database (Denmark)

    Joshi, Neha; Mitchard, Edward TA; Woo, Natalia

    2015-01-01

    Mapping anthropogenic forest disturbances has largely been focused on distinct delineations of events of deforestation using optical satellite images. In the tropics, frequent cloud cover and the challenge of quantifying forest degradation remain problematic. In this study, we detect processes...... of deforestation, forest degradation and successional dynamics, using long-wavelength radar (L-band from ALOS PALSAR) backscatter. We present a detection algorithm that allows for repeated disturbances on the same land, and identifies areas with slow- and fast-recovering changes in backscatter in close spatial...... along the tri-national Interoceanic Highway, as well as in mining areas and areas under no land use allocation. A continuous spatial gradient of disturbance was observed, highlighting artefacts arising from imposing discrete boundaries on deforestation events. The magnitude of initial radar backscatter...

  7. Mapping dynamics of deforestation and forest degradation in tropical forests using radar satellite data

    DEFF Research Database (Denmark)

    Joshi, Neha; Mitchard, Edward TA; Woo, Natalia;

    2015-01-01

    Mapping anthropogenic forest disturbances has largely been focused on distinct delineations of events of deforestation using optical satellite images. In the tropics, frequent cloud cover and the challenge of quantifying forest degradation remain problematic. In this study, we detect processes...... of deforestation, forest degradation and successional dynamics, using long-wavelength radar (L-band from ALOS PALSAR) backscatter. We present a detection algorithm that allows for repeated disturbances on the same land, and identifies areas with slow- and fast-recovering changes in backscatter in close spatial...... along the tri-national Interoceanic Highway, as well as in mining areas and areas under no land use allocation. A continuous spatial gradient of disturbance was observed, highlighting artefacts arising from imposing discrete boundaries on deforestation events. The magnitude of initial radar backscatter...

  8. Spatial Vegetation Data for Petrified Forest National Park Vegetation Mapping Project

    Data.gov (United States)

    National Park Service, Department of the Interior — The Petrified Forest National Park Vegetation Map Database was developed as a primary product in the Petrified Forest National Park Vegetation Classification,...

  9. US Forest Service Motor Vehicle Use Map: Roads and Trails (With Labels)

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting Forest Service roads and trails that are designated for motor vehicle use under the official U.S. Government Code of Federal...

  10. Mapping Clearances in Tropical Dry Forests Using Breakpoints, Trend, and Seasonal Components from MODIS Time Series: Does Forest Type Matter?

    Directory of Open Access Journals (Sweden)

    Kenneth Grogan

    2016-08-01

    Full Text Available Tropical environments present a unique challenge for optical time series analysis, primarily owing to fragmented data availability, persistent cloud cover and atmospheric aerosols. Additionally, little is known of whether the performance of time series change detection is affected by diverse forest types found in tropical dry regions. In this paper, we develop a methodology for mapping forest clearing in Southeast Asia using a study region characterised by heterogeneous forest types. Moderate Resolution Imaging Spectroradiometer (MODIS time series are decomposed using Breaks For Additive Season and Trend (BFAST and breakpoints, trend, and seasonal components are combined in a binomial probability model to distinguish between cleared and stable forest. We found that the addition of seasonality and trend information improves the change model performance compared to using breakpoints alone. We also demonstrate the value of considering forest type in disturbance mapping in comparison to the more common approach that combines all forest types into a single generalised forest class. By taking a generalised forest approach, there is less control over the error distribution in each forest type. Dry-deciduous and evergreen forests are especially sensitive to error imbalances using a generalised forest model i.e., clearances were underestimated in evergreen forest, and overestimated in dry-deciduous forest. This suggests that forest type needs to be considered in time series change mapping, especially in heterogeneous forest regions. Our approach builds towards improving large-area monitoring of forest-diverse regions such as Southeast Asia. The findings of this study should also be transferable across optical sensors and are therefore relevant for the future availability of dense time series for the tropics at higher spatial resolutions.

  11. 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.

  12. 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

  13. Digitizing the Forest Resource Map Using ArcGIS

    Directory of Open Access Journals (Sweden)

    K. R. Manjula

    2010-11-01

    Full Text Available The major challenges we face in the real world today is overpopulation, pollution, deforestation, natural disasters which have a critical geographic dimension and also have a geographical component. Geographical Decision Support System (Geo-DSS is a demanding field, since enormous amount of spatial data have been collected in various applications, ranging form Remote Sensing to GIS, Computer Cartography, Environmental Assessment and Planning. Although some efforts were made to combine spatial mining with Spatial Decision Support System but mostly researchers are using a spatial database for popular data mining approach. GIS will give you the power to create maps, integrate information, visualize scenarios, solve complicated problems, present powerful ideas, and develop effective solutions like never before so that it supports strategic decision making. With GIS application we can open digital maps on computer, create new spatial information to add to a map, create printed maps customized to our needs and perform spatial analysis on it. There is a great deal of geographic data available in formats that can not be immediately integrated with other GIS data. In order to use these types of data in GIS it is necessary to align it with existing geographically referenced data. This process is also called georeferencing. Georeferencing is a necessary step in the digitizing process. Digitizing in GIS is the process of "tracing", in a geographically correct way, information from images or maps. In this paper the processing of digitizing the forest map and the converting the georeferenced map into attribute data is depicted which can be further used to construct spatial database and on which spatial analysis can be performed.

  14. 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.

  15. Voids in Ly{\\alpha} Forest Tomographic Maps

    CERN Document Server

    Stark, Casey W; White, Martin; Lee, Khee-Gan

    2015-01-01

    We present a new method of finding cosmic voids using tomographic maps of Ly{\\alpha} forest flux. We identify cosmological voids with radii of 2 - 12 $h^{-1}$Mpc in a large N-body simulation at $z = 2.5$, and characterize the signal of the high-redshift voids in density and Ly{\\alpha} forest flux. The void properties are similar to what has been found at lower redshifts, but they are smaller and have steeper radial density profiles. Similarly to what has been found for low-redshift voids, the radial velocity profiles have little scatter and agree very well with the linear theory prediction. We run the same void finder on an ideal Ly{\\alpha} flux field and tomographic reconstructions at various spatial samplings. We compare the tomographic map void catalogs to the density void catalog and find good agreement even with modest-sized voids ($r > 6 \\, h^{-1}$Mpc). Using our simple void-finding method, the configuration of the ongoing CLAMATO survey covering 1 deg$^2$ would provide a sample of about 100 high-redshi...

  16. Noxubee National Wildlife Refuge Forest Compartment 8 Winter Burns and TSI Map 1977

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — Noxubee National Wildlife Refuge Forest Compartment 8 Winter Burns and TSI Map 1977. map also contains locations of know RCW trees in the compartment.

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

    Science.gov (United States)

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

    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...

  18. 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.

  19. 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.

  20. 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.

    2013-01-01

    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.

  1. 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

    Proactive forest conservation planning requires spatially accurate information about the potential distribution of tree species. The most cost-efficient way to obtain this information is habitat suitability modelling i.e. predicting the potential distribution of biota as a function of environmental...... 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...... for map applicability. The European forest suitability map is now available for further applications in forest conservation and climate change issues....

  2. Map of the natural and semi-natural environments and forest types map for the Latium region (Italy

    Directory of Open Access Journals (Sweden)

    Chirici G

    2014-04-01

    Full Text Available Map of the natural and semi-natural environments and forest types map for the Latium region (Italy. The paper presents the main methodological aspects and the most important results achieved in the implementation of the “Map of natural and semi-natural environments” and of the “Forest types map” in Lazio region at a scale of 1:10.000. The project was carried out for the Agenzia dei Parchi and for the Area Foreste of Regione Lazio through a collaboration between e-GEOS , the University of Rome "La Sapienza", the University of Tuscia and Forestlab Centre , a spin- off of the University of Molise . The project is based on the integrated use of high-resolution satellite imagery and ADS40 false-color infrared digital orthophotos and led to the creation of two maps geometrically and thematically consistent with each other. The “Map of natural and semi-natural environments” is integrated with the pre-existing land use map of the Lazio region deepening the thematic detail up to the 6th Corine level. The “Forest types map” is based on a typological system organized in 17 categories and 36 forest types .

  3. 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.

  4. Mapping site index and volume increment from forest inventory, Landsat, and ecological variables in Tahoe National Forest, California, USA

    Science.gov (United States)

    Huang, Shengli; Ramirez, Carlos; Conway, Scott; Kennedy, Kama; Kohler, Tanya; Liu, Jinxun

    2016-01-01

    High-resolution site index (SI) and mean annual increment (MAI) maps are desired for local forest management. We integrated field inventory, Landsat, and ecological variables to produce 30 m SI and MAI maps for the Tahoe National Forest (TNF) where different tree species coexist. We converted species-specific SI using adjustment factors. Then, the SI map was produced by (i) intensifying plots to expand the training sets to more climatic, topographic, soil, and forest reflective classes, (ii) using results from a stepwise regression to enable a weighted imputation that minimized the effects of outlier plots within classes, and (iii) local interpolation and strata median filling to assign values to pixels without direct imputations. The SI (reference age is 50 years) map had an R2 of 0.7637, a root-mean-square error (RMSE) of 3.60, and a mean absolute error (MAE) of 3.07 m. The MAI map was similarly produced with an R2 of 0.6882, an RMSE of 1.73, and a MAE of 1.20 m3·ha−1·year−1. Spatial patterns and trends of SI and MAI were analyzed to be related to elevation, aspect, slope, soil productivity, and forest type. The 30 m SI and MAI maps can be used to support decisions on fire, plantation, biodiversity, and carbon.

  5. RS AND GIS-BASED FOREST FIRE RISK ZONE MAPPING IN DA HINGGAN MOUNTAINS

    Institute of Scientific and Technical Information of China (English)

    YIN Hai-wei; KONG Fan-hua; LI Xiu-zhen

    2004-01-01

    The Da Hinggan Mountains is one of the most important forest areas in China,but forest fire there is also of high frequency.So it is completely necessary to map forest fire risk zones in order to effectively manage and protect the forest resources.Two forest farms of Tuqiang Forest Bureau (53°34′-52°15′N,124°05′- 122°18′E) were chosen as typical areas in this study.Remote sensing (RS) and Geographic Information System (GIS) play a vital role and can be used effectively to obtain and combine different forest-fire-causing factors for demarcating the forest fire risk zone map.Forest fire risk zones were described by assigning subjective weights to the classes of all the coverage layers according to their sensitivity to fire,using the ARC/INFO GIS software.Four classes of forest fire risk ranging from low to extremely high were generated automatically in ARC/INFO.The results showed that about 60.33% of the study area were predicted to be upper moderate risk zones,indicating that the forest fire management task in this area is super onerous.The RS and GIS-based forest fire risk model of the study area was found to be highly compatible with the actual fire-affected sites in 1987.Therefore the forest fire risk zone map can be used for guidance of forest fire management,and as basis for fire prevention strategies.

  6. Measuring and mapping threats to forests: issues and opportunities with an empirical study from Bangladesh

    Science.gov (United States)

    Mukul, S. A.; Herbohn, J.

    2015-12-01

    Spatially explicit tools for prioritizing conservation and land-use in human dominated landscapes are becoming common in recent years. Such efforts are also efficient in minimizing management costs and to provide future possible scenarios to aid management decisions. We propose and develop a spatially explicit framework and novel tool - Future Forest - for simulating scenarios for future forest management actions. We integrate both forest/vegetation characteristics, selected ecosystem services provided by corresponding forest/vegetation and nineteen possible threats and/or disturbances to forests that are either anthropogenic or occurring naturally, and may influence forest/vegetation characteristics and expected outcomes from forests. Our modelling framework provides options for necessary future actions either from conservation or from production forestry perspectives, and to ensure sustainable forest management in an area. In addition to that our threat assessment and mapping tool are useful in indentifying vulnerable zone of forests to specific anthropogenic, natural or other threats, and to take precautionary actions against each identified threats. We applied our modelling framework and spatial tool for measuring and mapping threats to a Bangladesh forest, with recommended actions to ensure sustainable forest management and to spatially prioritize zones for special management needs. We finally discuss issues and opportunities that our spatially explicit framework and novel tool may offer.

  7. 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

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

    NARCIS (Netherlands)

    Cho, M.A.; Skidmore, A.K.; Sobhan, I.

    2009-01-01

    Estimating forest structural attributes using multispectral remote sensing is challenging because of the saturation of multispectral indices at high canopy cover. The objective of this study was to assess the utility of hyperspectral data in estimating and mapping forest structural parameters includ

  9. 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...

  10. Mapping East African tropical forests and woodlands : a comparison of classifiers

    NARCIS (Netherlands)

    Nangendo, G.; Skidmore, A.K.; Oosten, van H.

    2007-01-01

    In mapping the forest¿woodland¿savannah mosaic of Budongo Forest Reserve, Uganda, four classification methods were compared, i.e. Maximum Likelihood classifier (MLC), Spectral Angle Mapper (SAM), Maximum Likelihood combined with an Expert System (MaxExpert) and Spectral Angle Mapper combined with an

  11. New approaches to forest planning: inventorying and mapping place values in the Pacific Northwest Region

    Science.gov (United States)

    Troy E. Hall; Jennifer O. Farnum; Terry C. Slider; Kathy Ludlow

    2009-01-01

    This report chronicles a large-scale effort to map place values across the Pacific Northwest Region (Washington and Oregon) of the U.S. Forest Service. Through workshops held with Forest Service staff, 485 socioculturally meaningful places were identified. Staff also generated corresponding descriptions of the places’ unique social and biophysical elements—in other...

  12. Age at menarche, schooling, and sexual debut in northern Malawi.

    Directory of Open Access Journals (Sweden)

    Judith R Glynn

    Full Text Available BACKGROUND: Age at sexual debut is a key behavioural indicator used in HIV behavioural surveillance. Early age at menarche may precipitate early sex through perceived readiness for sex, or through school drop-out, but this is rarely studied. We investigated trends and circumstances of sexual debut in relation to schooling and age at menarche. METHODS AND FINDINGS: A cross-sectional sexual behaviour survey was conducted on all individuals age 15-59 within a demographic surveillance site in Karonga District, Malawi. Time trends were assessed using birth cohorts. Survival analysis was used to estimate the median age at menarche, sexual debut and first marriage. The 25(th centile was used to define "early" sex, and analyses of risk factors for early sex were restricted to those who had reached that age, and were done using logistic regression. Of the 8232 women and 7338 men resident in the area, 88% and 78%, respectively, were seen, and, 94% and 92% of these were interviewed. The median reported age at first sex was 17.5 for women and 18.8 for men. For women, ages at menarche, sexual debut and first marriage did not differ by birth cohort. For men, age at sexual debut and first marriage decreased slightly in later birth cohorts. For both men and women increased schooling was associated with later sexual debut and a longer delay between sexual debut and first marriage, but the associations were stronger for women. Earlier age at menarche was strongly associated with earlier sexual debut and marriage and lower schooling levels. In women early sexual debut (<16 years was less likely in those with menarche at age 14-15 (odds ratio (OR 0.31, 95%CI 0.26-0.36, and ≥16 (OR 0.04, 95%CI 0.02-0.05 compared to those with menarche at <14. The proportion of women who completed primary school was 46% in those with menarche at <14, 60% in those with menarche at 14-15 and 70% in those with menarche at ≥16. The association between age at menarche and schooling

  13. Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation.

    Science.gov (United States)

    Asner, G P; Martin, R E; Knapp, D E; Tupayachi, R; Anderson, C B; Sinca, F; Vaughn, N R; Llactayo, W

    2017-01-27

    Functional biogeography may bridge a gap between field-based biodiversity information and satellite-based Earth system studies, thereby supporting conservation plans to protect more species and their contributions to ecosystem functioning. We used airborne laser-guided imaging spectroscopy with environmental modeling to derive large-scale, multivariate forest canopy functional trait maps of the Peruvian Andes-to-Amazon biodiversity hotspot. Seven mapped canopy traits revealed functional variation in a geospatial pattern explained by geology, topography, hydrology, and climate. Clustering of canopy traits yielded a map of forest beta functional diversity for land-use analysis. Up to 53% of each mapped, functionally distinct forest presents an opportunity for new conservation action. Mapping functional diversity advances our understanding of the biosphere to conserve more biodiversity in the face of land use and climate change. Copyright © 2017, American Association for the Advancement of Science.

  14. Spaceborne Radar for Mapping Forest and Land Use Changes

    DEFF Research Database (Denmark)

    Joshi, Neha Pankaj

    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...... the radar backscatter and forest AGV/AGB relation. The papers in the thesis show that radar is able to pick up forest disturbances to larger extent than traditional optical-based detection approaches, the radar to AGV/AGB relation is strongly driven by spatial scale of assessments and age- and management...

  15. Mangrove forest exploration of Tambelan And Serasan Islands: Species composition, mapping of mangrove forest distribution and potential threat

    Directory of Open Access Journals (Sweden)

    YAYA IHYA ULUMUDDIN

    2017-03-01

    Full Text Available Abstract. Ulumuddin YI, Setyawan AD. 2017. Mangrove forest exploration of Tambelan And Serasan Islands: Species composition, mapping of mangrove forest distribution and potential threat. Pros Sem Nas Masy Biodiv Indon 3: 45-55. Knowledge of the exact species plant composition of mangroves in any country or government is a basic and an important prerequisite to understanding all the aspects of structure and function of mangroves, as well as their conservation and management. The present study is going to describe the results of Natuna Sea Expedition, involving the inventory of mangrove species, mangrove forest mapping, and interview about mangrove use. This expedition has been conducted at 4th-16th November 2010 in Tambelan and Serasan Islands, Natuna Waters, Riau Archipelago. The inventory was conducted by survey method through the mangrove area, and the mapping was conducted by satellite imagery interpretation of ALOS AVNIR-2 acquisitions year 2009 and 2010, combined with the data field of mangrove position. There were 18 mangrove species and 31 associates species in Tambelan and Serasan Islands, which were the destination of the expedition. The vegetation was distributed in mangrove forests in the bays, the stream narrows, and covered islands. Mangrove forests in such two islands have not been treated significantly, but there was threat potential regarding of the tendency to occupy mangrove area for the homeland.

  16. Smoothing point data into maps using SAS/GRAPH (trade name) software. Forest Service research note

    Energy Technology Data Exchange (ETDEWEB)

    Chojnacky, D.C.; Rubey, M.E.

    1996-01-01

    Point of plot data are commonly available for mapping forest landscapes. Because such data are sampled, mapping a complete coverage usually requires some type of interpolation between plots. SAS/GRAPH software includes the G3GRID procedure for interpolating or smoothing this type of data to map with G3D or GCONTOUR procedures. However, the smoothing process in G3GRID is not easily controlled, nor can it be used to display missing data within rectangular grid maps. These shortcomings motivated development of SAS code that prepares point data for display in mapping units. This code links well with the rest of the SAS system to allow for powerful, easily controlled data analysis within mapping units. Examples are given for mapping forest vegetation with the GMAP procedure.

  17. Mapping Local Effects of Forest Properties on Fire Risk across Canada

    Directory of Open Access Journals (Sweden)

    Pierre Y. Bernier

    2016-07-01

    Full Text Available Fire is a dominant mechanism of forest renewal in most of Canada’s forests and its activity is predicted to increase over the coming decades. Individual fire events have been considered to be non-selective with regards to forest properties, but evidence now suggests otherwise. Our objective was therefore to quantify the effect of forest properties on fire selectivity or avoidance, evaluate the stability of these effects across varying burn rates, and use these results to map local fire risk across the forests of Canada. We used Canada-wide MODIS-based maps of annual fires and of forest properties to identify burned and unburned pixels for the 2002–2011 period and to bin them into classes of forest composition (% conifer and broadleaved deciduous, above-ground tree biomass and stand age. Logistic binomial regressions were then used to quantify fire selectivity by forest properties classes and by zones of homogeneous fire regime (HFR. Results suggest that fire exhibits a strong selectivity for conifer stands, but an even stronger avoidance of broadleaved stands. In terms of age classes, fire also shows a strong avoidance for young (0 to 29 year stands. The large differences among regional burn rates do not significantly alter the overall preference and avoidance ratings. Finally, we combined these results on relative burn preference with regional burn rates to map local fire risks across Canada.

  18. 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.

  19. 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...

  20. 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...

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

    Science.gov (United States)

    Ozdogan, Mutlu

    2014-01-01

    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 forest cover

  2. 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

  3. 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.

  4. 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 < 100-m resolution using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+). These "Landsat-class" sensors offer precise calibration, but they provide observations only over the past three decades—a relatively short period for delineating the long-term changes of forests. Starting in 1971, the Multispectral Scanner (MSS) was the first generation of sensors aboard the Landsat satellites. MSS thus provides a unique resource to extend observations by at least a decade longer in history than records based on Landsat TM and ETM+. Leveraging more recent Landsat-based forest-cover products 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

  5. 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

  6. Mapping growing stock at 1-km spatial resolution for Spanish forest areas from ground forest inventory data and GLAS canopy height

    Science.gov (United States)

    Sánchez-Ruiz, S.; Chiesi, M.; Maselli, F.; Gilabert, M. A.

    2016-10-01

    National forest inventories provide measurements of forest variables (e.g. growing stock) that can be used for the estimation of above ground biomass (AGB). Mapping growing stock brings knowledge about spatial distribution and temporal dynamics of ABG, which is necessary for carbon cycle analysis. Several studies have been conducted on the integration of ground and optical remote sensing data to map forest biomass over Europe. Nevertheless, more direct information on forest biomass could be obtained by LiDAR techniques, which directly assess vertical forest structure by measuring the distance between the sensor and the scattering elements located inside the canopy volume. Thus, global 1-km maps of forest canopy height have been recently obtained from the Geoscience Laser Altimeter System (GLAS). The current study aims to produce a forest growing stock map in Spain. Five different forest type areas were identified in three provinces along a North - South gradient accounting for different ecosystems and climatic conditions. Growing stock ground data from the Third Spanish National Forest Inventory were assigned to each forest type and aggregated to 1-km spatial resolution. GLAS-derived canopy height was extracted for the locations of selected ground data. A relationship between inventory growing stock and satellite canopy height was found for each class. The obtained relationships were then extended all over Spain. The accuracy of the resulting growing stock map was assessed at province level against the Third Spanish National Forest Inventory growing stock estimations (R = 0.85, RMSE = 21 m3 ha-1).

  7. 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.

  8. Accuracy assessment of GPS and surveying technique in forest road mapping

    Directory of Open Access Journals (Sweden)

    Ehsan Abdi

    2012-12-01

    Full Text Available Forest road networks provide access to the forest as a source of timber production and tourism services. Moreover, it is considered the main tool to protect forests from fire and smuggling. The prerequisite of road management and maintenance planning is to have spatial distribution and map of the roads. But newly constructed or some other forest road segments are not available in national maps. Therefore, mapping these networks is raised as a priority for a forest manager. The aim of this study was to assess accuracy of routine methods in road mapping. For this purpose, Patom district forest road was selected and road network map was extracted from the National Cartographic Center maps as the ground truth or base map. The map of the network was acquired using two methods, a GPS receiver and survey technique. Selecting 70 sample points on the network and considering the National Cartographic Center map as base map, accuracy was determined for two methods. The results showed that while the survey method was more accurate at the beginning of the path (first 500 meters, accumulation of errors resulted in higher rates of error in this method (up to 263 meters compared to GPS. Mann-Whitney test revealed significant differences in accuracy of two methods and mean accuracies were 38.86 and 147.90 for GPS and surveying respectively. The results showed that for samples 1-15 there was no significant difference between the survey and GPS data but for samples 28-42 and 56-70 statistically significant difference were existed between the survey and GPS data. Regression analysis showed that the relation between GPS and surveying accuracies and distance were best defined by cubic (R2 adj = 0.65 and linear (R2 adj = 0.83 regression models respectively. Applying 10 and 5 meters buffers around base map, 68 and 41% of GPS and 44 and 21% of surveying derived road were overlapped with buffer zones. The time required to complete the survey was found to increase the

  9. A Project to Map and Monitor Baldcypress Forests in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

    Science.gov (United States)

    Spruce, Joseph; Sader, Steven; Smoot, James

    2012-01-01

    Cypress swamp forests of Louisiana offer many important ecological and economic benefits: wildlife habitat, forest products, storm buffers, water quality, and recreation. Such forests are also threatened by multiple factors: subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, hurricanes, insect and nutria damage, timber harvesting, and land use conversion. Unfortunately, there are many information gaps regarding the type, location, extent, and condition of these forests. Better more up to date swamp forest mapping products are needed to aid coastal forest conservation and restoration work (e.g., through the Coastal Forest Conservation Initiative or CFCI). In response, a collaborative project was initiated to develop, test and demonstrate cypress swamp forest mapping products, using NASA supported Landsat, ASTER, and MODIS satellite data. Research Objectives are: Develop, test, and demonstrate use of Landsat and ASTER data for computing new cypress forest classification products and Landsat, ASTER, and MODIS satellite data for detecting and monitoring swamp forest change

  10. Forest type mapping using incorporation of spatial models and ETM+ data.

    Science.gov (United States)

    Joibary, Shaban Shataee; Darvishsefat, Ali A; Kellenberger, Tobias W

    2007-07-15

    Results of former researches have shown that spectrally based analysis alone could not satisfy forest type classification in mountainous mixed forests. Forest type based on composed different parameters such as topography elements like aspect, elevation and slop. These elements that are affected on occurrences of forest type can be stated as spatial distribution models. Using ancillary data integrated with spectral data could help to separate forest type. In order to find the abilities of using topographic spatial predictive models to improve forest type classification, an investigation was carried out to classify forest type using ETM+ data in a part of northern forests of Iran. The Tasseled Cap, Ratioing transformations and Principal Component Analysis were applied to the spectral bands. The best spectral and predictive data sets for classifying forest type using maximum likelihood classification were chosen using the Bhattacharya seperability index. Primary analysis between forest type and topographic parameters showed that elevation and aspect are most correlated with the occurrences of type. Probability occurrence rates of forest type were extracted in the aspect; elevation, integrated aspect and elevation as well as homogeneous units structured on elevation and aspect classes. Based on occurrence rates of forest type, spatial predictive distribution models were generated for each type individually. Classification of the best spectral data sets was accomplished by maximum likelihood classifier and using these spatial predictive models. Results were assessed using a sample ground truth of forest type. This study showed that spatial predictive models could considerably improve the results compared with spectral data alone from 49 to 60%. Among spatial models used, the spatial predictive models constructed based on the homogeneous units could improve results in comparison to other models. Applying other parameters related to forest type like soil maps would

  11. 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.

  12. 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

    2014-01-10

    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.

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

    African Journals Online (AJOL)

    DR. ALEX O. ONOJEGHUO

    From the results generated we were able to determine the effectiveness level of forest protected ... expansion of large rubber and oil-palm plantations within the reserve, .... Mapper Plus (ETM+) and United Kingdom - Disaster Monitoring and ...

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

    African Journals Online (AJOL)

    EJIRO

    The study was conducted in the Afram Headwaters Forest Reserve. (Figure 1) ... Stated below are steps involved in the ... distribution of the training samples is the basic requirement of the ..... Thus its implementation is less laborious and.

  15. Mapping a burned forest area from Landsat TM data by multiple methods

    Directory of Open Access Journals (Sweden)

    W. Chen

    2016-01-01

    Full Text Available Forest fire is one of the dominant disturbances in boreal forests. It is the primary process responsible for organizing the physical and biological attributes of the boreal biome, shaping landscape diversity and influencing biogeochemical cycles. The Greater Hinggan Mountain of China is rich in forest resources while suffers from a high incidence of forest fires simultaneously. In this study, focusing on the most serious forest fire in the history of P. R. China which occurred in this region, we made use of two Landsat-5 TM (Thematic Mapper images, and proposed to map the overall burned area and burned forest area by multiple methods. During the mapping, the fire perimeter, as well as rivers, roads and urban areas were first extracted and masked visually, and then four indices of Normalized Difference Vegetation Index, Enhanced Vegetation Index, Vegetation Fractional Cover and Disturbance Index were calculated. For each index, the optimal threshold for separating burned from unburned forest area was determined using their histograms. For comparison, threshold segmentation using single-band reflectance was performed, in addition to a Maximum Likelihood Classifier (MLC based supervised classification of all features and forest area alone; their accuracies were also evaluated and analysed. Among all the methods compared here, mapping by EVI threshold segmentation proved to be optimal by the comparisons of overall accuracy (99.78% and the kappa coefficient (0.9946. Finally, the calculated burned area and burned forest area were compared with the values from official statistics. Compared with the classical methods used to report official statistics on burned areas, the remote sensing-based mapping is more objective and efficient, less labour- and time-consuming, and more repeatable.

  16. [GIS-based forest fire risk zone mapping in Daxing'an Mountains].

    Science.gov (United States)

    Yin, Haiwei; Kong, Fanhua; Li, Xiuzhen

    2005-05-01

    In this study, the Yuying and Fendou forest farms of Tuqiang Forest Bureau in Daxing'an Mountains were chosen as test areas, and their vegetation type, altitude, slop, aspect, and settlement buffer were selected as the main forest fire factors. The circumstances of forest fire risk were quantified by the factor-weights union method with the support of GIS. Four classes of forest fire risk ranging from low to extreme were generated. The none-, low, moderate, high, and extremely high fire risk zones accounted for 0.37%, 0.63%, 38.67%, 58.63% and 1.70%, respectively, which was in corresponding with normal distribution. About 60.33% of the test areas were predicted to be upper moderate risk zones, indicating that the forest fire management task in these areas is super onerous. There was an obvious regional difference in the distribution of forest fire risk zones, being higher in the center and lower around the center, and the difference in fire factors was also obvious. The GIS-based forest fire risk model of test areas strongly cohered with the actual fire-affected sites in 1987, which suggested that the forest fire risk zone mapping had a higher reliability, and could be used as the reference and guidance of forest fire management.

  17. Mapping stand-age distribution of Russian forests from satellite data

    Science.gov (United States)

    Chen, D.; Loboda, T. V.; Hall, A.; Channan, S.; Weber, C. Y.

    2013-12-01

    Russian boreal forest is a critical component of the global boreal biome as approximately two thirds of the boreal forest is located in Russia. Numerous studies have shown that wildfire and logging have led to extensive modifications of forest cover in the region since 2000. Forest disturbance and subsequent regrowth influences carbon and energy budgets and, in turn, affect climate. Several global and regional satellite-based data products have been developed from coarse (>100m) and moderate (10-100m) resolution imagery to monitor forest cover change over the past decade, record of forest cover change pre-dating year 2000 is very fragmented. Although by using stacks of Landsat images, some information regarding the past disturbances can be obtained, the quantity and locations of such stacks with sufficient number of images are extremely limited, especially in Eastern Siberia. This paper describes a modified method which is built upon previous work to hindcast the disturbance history and map stand-age distribution in the Russian boreal forest. Utilizing data from both Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS), a wall-to-wall map indicating the estimated age of forest in the Russian boreal forest is created. Our previous work has shown that disturbances can be mapped successfully up to 30 years in the past as the spectral signature of regrowing forests is statistically significantly different from that of mature forests. The presented algorithm ingests 55 multi-temporal stacks of Landsat imagery available over Russian forest before 2001 and processes through a standardized and semi-automated approach to extract training and validation data samples. Landsat data, dating back to 1984, are used to generate maps of forest disturbance using temporal shifts in Disturbance Index through the multi-temporal stack of imagery in selected locations. These maps are then used as reference data to train a decision tree classifier on 50 MODIS

  18. Wall-to-Wall Forest Mapping Based on Digital Surface Models from Image-Based Point Clouds and a NFI Forest Definition

    Directory of Open Access Journals (Sweden)

    Lars T. Waser

    2015-12-01

    Full Text Available Forest mapping is an important source of information for assessing woodland resources and a key issue for any National Forest Inventory (NFI. In the present study, a detailed wall-to-wall forest cover map was generated for all of Switzerland, which meets the requirement of the Swiss NFI forest definition. The workflow is highly automated and based on digital surface models from image-based point clouds of airborne digital sensor data. It fully takes into account the four key criteria of minimum tree height, crown coverage, width, and land use. The forest cover map was validated using almost 10,000 terrestrial and stereo-interpreted NFI plots, which verified 97% agreement overall. This validation implies different categories such as five production regions, altitude, tree type, and distance to the forest border. Overall accuracy was lower at forest borders but increased with increasing distance from the forest border. Commission errors remained stable at around 10%, but increased to 17.6% at the upper tree line. Omission errors were low at 1%–10%, but also increased with altitude and mainly occurred at the upper tree line (19.7%. The main reasons for this are the lower image quality and the NFI height definition for forest which apparently excludes shrub forest from the mask. The presented forest mapping approach is superior to existing products due to its national coverage, high level of detail, regular updating, and implementation of the land use criteria.

  19. Thematic Mapper simulator research for forest resource mapping in the Clearwater National Forest, Idaho

    Science.gov (United States)

    Brass, J. A.; Peterson, D. L.; Spanner, M. A.; Ambrosia, V. G.; Ulliman, J. J.; Brockhaus, J.

    1984-01-01

    Per-pixel maximum likelihood digital classification and photo interpretation of Thematic Mapper Simulator (TMS) composited images for a managed conifer forest were used to evaluate both land cover and forest structure characteristics. TMS channels 4, 7, 5 and 3, which were found to be optimal for forest vegetation analysis, used the full range of the Thematic Mapper's spectral capability. Photo interpretation results indicate that a false color composite from TMS channels 4, 7, and 2 provided the highest accuracies; the combination of improved spatial, spectral and radiometric resolution of the Thematic Mapper yielded greater sensitivity to forest structural characteristics.

  20. 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.

  1. High-resolution Mapping of Forest Carbon Stocks in the Colombian Amazon

    Directory of Open Access Journals (Sweden)

    G. P. Asner

    2012-03-01

    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 mapping samples had 14.6 % uncertainty at 1 ha resolution, and regional maps based on stratification and regression approaches had 25.6 % and 29.6 % uncertainty, respectively, in any given hectare. High-resolution approaches with reported local-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.

  2. Geologic mapping of Indonesian rain forest with analysis of multiple SIR-B incidence angles

    Science.gov (United States)

    Ford, J. P.; Sabins, F. F., Jr.; Asmoro, P., Jr.

    1984-01-01

    The discrimination and mapping capabilities are to be evaluated for shuttle imaging radar-B (SIR-B) images of geologic features in Indonesia that are covered by equatorial rain forest canopy. The SIR-B backscatter from the rain forest at L-band is to be compared to backscatter acquired by the SEASAT scatterometer system at Ku-band ever corresponding areas. The approach for data acquisition, handling, and analysis and the expected results of the investigation are discussed.

  3. National Forest Aboveground Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China

    Directory of Open Access Journals (Sweden)

    Hong Chi

    2015-05-01

    Full Text Available Forest aboveground biomass (AGB was mapped throughout China using large footprint LiDAR waveform data from the Geoscience Laser Altimeter System (GLAS onboard NASA’s Ice, Cloud, and land Elevation Satellite (ICESat, Moderate Resolution Imaging Spectro-radiometer (MODIS imagery and forest inventory data. The entire land of China was divided into seven zones according to the geographic characteristics of the forests. The forest AGB prediction models were separately developed for different forest types in each of the seven forest zones at GLAS footprint level from GLAS waveform parameters and biomass derived from height and diameter at breast height (DBH field observation. Some waveform parameters used in the prediction models were able to reduce the effects of slope on biomass estimation. The models of GLAS-based biomass estimates were developed by using GLAS footprints with slopes less than 20° and slopes ≥ 20°, respectively. Then, all GLAS footprint biomass and MODIS data were used to establish Random Forest regression models for extrapolating footprint AGB to a nationwide scale. The total amount of estimated AGB in Chinese forests around 2006 was about 12,622 Mt vs. 12,617 Mt derived from the seventh national forest resource inventory data. Nearly half of all provinces showed a relative error (% of less than 20%, and 80% of total provinces had relative errors less than 50%.

  4. NORMALIZED DIFFERENCE SNOW INDEX SIMULATION FOR SNOW-COVER MAPPING IN FOREST BY GEOSAIL MODEL

    Institute of Scientific and Technical Information of China (English)

    CAO Yun-gang; LIU Chuang

    2006-01-01

    The snow-cover mapping in forest area is always one of the difficult points for optical satellite remote sensing. To investigate reflectance variability and to improve the mapping of snow in forest area, GeoSail model was used to simulate the reflectance of a snow-covered forest. Using this model, the effects of varying canopy density, solar illumination and view geometry on the performance of the MODIS (Moderate-resolution Imaging Spectroradiometer)snow-cover mapping algorithm were investigated. The relationship between NDSI (Normalized Difference Snow Index), NDVI (Normalized Difference Vegetation Index) and snow fraction was discussed in detail. Results indicated that the weak performance would be achieved if fixed criteria were used for different regions especially in the complicated land cover components. Finally, some suggestions to MODIS SNOWMAP algorithm were put forward to improve snow mapping precision in forest area based on the simulation, for example, new criteria should be used in coniferous forest, that is, NDSI greater than 0.3 and NDVI greater than zero. Otherwise, a threshold on view zenith angle may be used in the criteria such as 45°.

  5. 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...

  6. Indiana forest cover mapping based on multi-stage integrated classification using satellite and in situ forest inventory data

    Science.gov (United States)

    Shao, Gang

    Forest species classification through remote sensing data is a complex process, which usually is done either at a coarse level or with low accuracy. This study examines a multi-stage classification algorithm combining supervised and unsupervised classifications to classify forest areas in Indiana. Integrated classification makes the procedures automatic and reduces human errors. Splitting the classification into two steps increases the accuracy with limited ground data. In the first step, in which the Indiana state forest area is classified, the point plug-in classification algorithm is employed, because plenty of ground data are available. In the second step the classifying of the state forest including a surrounding 8km buffer, the ground data are insufficient to process the point plug-in classification approach. In this case, the polygon plug-in classification algorithm is used to realize the extended area classification at the second stage. The resultant land cover map has six tree species (conifer, mixed forest, oak and hickory, mixed oak and hickory/ hardwood, maple and other hardwood). The overall accuracy is 81.93%.

  7. Ecosystem services of boreal forests - Carbon budget mapping at high resolution.

    Science.gov (United States)

    Akujärvi, Anu; Lehtonen, Aleksi; Liski, Jari

    2016-10-01

    The carbon (C) cycle of forests produces ecosystem services (ES) such as climate regulation and timber production. Mapping these ES using simple land cover -based proxies might add remarkable inaccuracy to the estimates. A framework to map the current status of the C budget of boreal forested landscapes was developed. The C stocks of biomass and soil and the annual change in these stocks were quantified in a 20 × 20 m resolution at the regional level on mineral soils in southern Finland. The fine-scale variation of the estimates was analyzed geo-statistically. The reliability of the estimates was evaluated by comparing them to measurements from the national multi-source forest inventory. The C stocks of forests increased slightly from the south coast to inland whereas the changes in these stocks were more uniform. The spatial patches of C stocks were larger than those of C stock changes. The patch size of the C stocks reflected the spatial variation in the environmental conditions, and that of the C stock changes the typical area of forest management compartments. The simulated estimates agreed well with the measurements indicating a good mapping framework performance. The mapping framework is the basis for evaluating the effects of forest management alternatives on C budget at high resolution across large spatial scales. It will be coupled with the assessment of other ES and biodiversity to study their relationships. The framework integrated a wide suite of simulation models and extensive inventory data. It provided reliable estimates of the human influence on C cycle in forested landscapes. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Fuzzy logic merger of spectral and ecological information for improved montane forest mapping.

    Science.gov (United States)

    White, Joseph D.; Running, Steven W.; Ryan, Kevin C.; Key, Carl H.

    2002-01-01

    Environmental data are often utilized to guide interpretation of spectral information based on context, however, these are also important in deriving vegetation maps themselves, especially where ecological information can be mapped spatially. A vegetation classification procedure is presented which combines a classification of spectral data from Landsat‐5 Thematic Mapper (TM) and environmental data based on topography and fire history. These data were combined utilizing fuzzy logic where assignment of each pixel to a single vegetation category was derived comparing the partial membership of each vegetation category within spectral and environmental classes. Partial membership was assigned from canopy cover for forest types measured from field sampling. Initial classification of spectral and ecological data produced map accuracies of less than 50% due to overlap between spectrally similar vegetation and limited spatial precision for predicting local vegetation types solely from the ecological information. Combination of environmental data through fuzzy logic increased overall mapping accuracy (70%) in coniferous forest communities of northwestern Montana, USA.

  9. The Price of Precision: Large-Scale Mapping of Forest Structure and Biomass Using Airborne Lidar

    Science.gov (United States)

    Dubayah, R.

    2015-12-01

    Lidar remote sensing provides one of the best means for acquiring detailed information on forest structure. However, its application over large areas has been limited largely because of its expense. Nonetheless, extant data exist over many states in the U.S., funded largely by state and federal consortia and mainly for infrastructure, emergency response, flood plain and coastal mapping. These lidar data are almost always acquired in leaf-off seasons, and until recently, usually with low point count densities. Even with these limitations, they provide unprecedented wall-to-wall mappings that enable development of appropriate methodologies for large-scale deployment of lidar. In this talk we summarize our research and lessons learned in deriving forest structure over regional areas as part of NASA's Carbon Monitoring System (CMS). We focus on two areas: the entire state of Maryland and Sonoma County, California. The Maryland effort used low density, leaf-off data acquired by each county in varying epochs, while the on-going Sonoma work employs state-of-the-art, high density, wall-to-wall, leaf-on lidar data. In each area we combine these lidar coverages with high-resolution multispectral imagery from the National Agricultural Imagery Program (NAIP) and in situ plot data to produce maps of canopy height, tree cover and biomass, and compare our results against FIA plot data and national biomass maps. Our work demonstrates that large-scale mapping of forest structure at high spatial resolution is achievable but products may be complex to produce and validate over large areas. Furthermore, fundamental issues involving statistical approaches, plot types and sizes, geolocation, modeling scales, allometry, and even the definitions of "forest" and "non-forest" must be approached carefully. Ultimately, determining the "price of precision", that is, does the value of wall-to-wall forest structure data justify their expense, should consider not only carbon market applications

  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FOREST COUNTY, WISCONSIN, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk;...

  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FOREST COUNTY, PA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FOREST COUNTY, WISCONSIN, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Floodplain Mapping/Redelineation study deliverables depict and quantify the flood risks for the study area. The primary risk classifications used are the...

  13. Structure and Evolution of Mediterranean Forest Research: A Science Mapping Approach

    OpenAIRE

    Pierfrancesco Nardi; Giovanni Di Matteo; Marc Palahi; Giuseppe Scarascia Mugnozza

    2016-01-01

    This study aims at conducting the first science mapping analysis of the Mediterranean forest research in order to elucidate its research structure and evolution. We applied a science mapping approach based on co-term and citation analyses to a set of scientific publications retrieved from the Elsevier's Scopus database over the period 1980-2014. The Scopus search retrieved 2,698 research papers and reviews published by 159 peer-reviewed journals. The total number of publications was around 1%...

  14. Mapping landscape scale variations of forest structure, biomass, and productivity in Amazonia

    Directory of Open Access Journals (Sweden)

    S. Saatchi

    2009-06-01

    Full Text Available Landscape and environmental variables such as topography, geomorphology, soil types, and climate are important factors affecting forest composition, structure, productivity, and biomass. Here, we combine a network of forest inventories with recently developed global data products from satellite observations in modeling the potential distributions of forest structure and productivity in Amazonia and examine how geomorphology, soil, and precipitation control these distributions. We use the RAINFOR network of forest plots distributed in lowland forests across Amazonia, and satellite observations of tree cover, leaf area index, phenology, moisture, and topographical variations. A maximum entropy estimation (Maxent model is employed to predict the spatial distribution of several key forest structure parameters: basal area, fraction of large trees, fraction of palms, wood density, productivity, and above-ground biomass at 5 km spatial resolution. A series of statistical tests at selected thresholds as well as across all thresholds and jackknife analysis are used to examine the accuracy of distribution maps and the relative contributions of environmental variables. The final maps were interpreted using soil, precipitation, and geomorphological features of Amazonia and it was found that the length of dry season played a key role in impacting the distribution of all forest variables except the wood density. Soil type had a significant impact on the wood productivity. Most high productivity forests were distributed either on less infertile soils of western Amazonia and Andean foothills, on crystalline shields, and younger alluvial deposits. Areas of low elevation and high density of small rivers of Central Amazonia showed distinct features, hosting mainly forests with low productivity and smaller trees.

  15. 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.

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

    Science.gov (United States)

    Cho, Moses Azong; Skidmore, Andrew K.; Sobhan, Istiak

    2009-06-01

    Estimating forest structural attributes using multispectral remote sensing is challenging because of the saturation of multispectral indices at high canopy cover. 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 ( Fagus sylvatica L.). Airborne HyMap images and data on forest structural attributes were collected from the Majella National Park, Italy in July 2004. The predictive performances of vegetation indices (VI) derived from all possible two-band combinations (VI ( i, j) = ( Ri - Rj)/( Ri + Rj), where Ri and Rj = reflectance in any two bands) were evaluated using calibration ( n = 33) and test ( n = 20) data sets. The potential of partial least squares (PLS) regression, a multivariate technique involving several bands was also assessed. New VIs based on the contrast between reflectance in the red-edge shoulder (756-820 nm) and the water absorption feature centred at 1200 nm (1172-1320 nm) were found to show higher correlations with the forest structural parameters than standard VIs derived from NIR and visible reflectance (i.e. the normalised difference vegetation index, NDVI). PLS regression showed a slight improvement in estimating the beech forest structural attributes (prediction errors of 27.6%, 32.6% and 46.4% for mean DBH, height and tree density, respectively) compared to VIs using linear regression models (prediction errors of 27.8%, 35.8% and 48.3% for mean DBH, height and tree density, respectively). Mean DBH was the best predicted variable among the stand parameters (calibration R2 = 0.62 for an exponential model fit and standard error of prediction = 5.12 cm, i.e. 25% of the mean). The predicted map of mean DBH revealed high heterogeneity in the beech forest structure in the study area. The spatial variability of mean DBH occurs at less than 450 m. The DBH

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

    NARCIS (Netherlands)

    Garzon-Lopez, Carol X.; Bohlman, Stephanie A.; Olff, Han; Jansen, Patrick 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

  18. 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...

  19. Mapping woody-biomass supply costs using forest inventory and competing industry data

    Energy Technology Data Exchange (ETDEWEB)

    Stasko, Timon H.; Conrado, Robert J.; Labatut, Rodrigo; Tasseff, Ryan; Mannion, John T.; Gao, H. Oliver [College of Engineering, Cornell University, Ithaca, NY 14853 (United States); Wankerl, Andreas [Innovation Interface, 126 Reach Run, Ithaca, NY 14850 (United States); Sanborn, Stephen D.; Knott, Gregory [General Electric Global Research, 1 Research Circle, Niskayuna, NY 12309 (United States)

    2011-01-15

    The goals of energy independence and sustainability have motivated many countries to consider biomass-based energy sources. The United States has substantial and increasing forest resources that could be used to produce both electricity and liquid fuel. However, these forest resources are highly heterogeneous in terms of the wood's properties, the logging cost, the spatial distribution, and the value to other industries. These factors make predicting costs and selecting plant locations particularly challenging. When dealing with forest biomass, feedstock cost and location have frequently been highly simplified in previous studies. This paper presents a methodology for combining highly resolved forest inventory and price data with records of competing industries to develop detailed maps of feedstock availability. The feedstock sourcing strategy of the proposed bioenergy plants is modeled by a cost-minimizing linear program, as is the feedstock selection of the competing mills. A case study is performed on the southeast United States. (author)

  20. 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

  1. A universal airborne LiDAR approach for tropical forest carbon mapping.

    Science.gov (United States)

    Asner, Gregory P; Mascaro, Joseph; Muller-Landau, Helene C; Vieilledent, Ghislain; Vaudry, Romuald; Rasamoelina, Maminiaina; Hall, Jefferson S; van Breugel, Michiel

    2012-04-01

    Airborne light detection and ranging (LiDAR) is fast turning the corner from demonstration technology to a key tool for assessing carbon stocks in tropical forests. With its ability to penetrate tropical forest canopies and detect three-dimensional forest structure, LiDAR may prove to be a major component of international strategies to measure and account for carbon emissions from and uptake by tropical forests. To date, however, basic ecological information such as height-diameter allometry and stand-level wood density have not been mechanistically incorporated into methods for mapping forest carbon at regional and global scales. A better incorporation of these structural patterns in forests may reduce the considerable time needed to calibrate airborne data with ground-based forest inventory plots, which presently necessitate exhaustive measurements of tree diameters and heights, as well as tree identifications for wood density estimation. Here, we develop a new approach that can facilitate rapid LiDAR calibration with minimal field data. Throughout four tropical regions (Panama, Peru, Madagascar, and Hawaii), we were able to predict aboveground carbon density estimated in field inventory plots using a single universal LiDAR model (r ( 2 ) = 0.80, RMSE = 27.6 Mg C ha(-1)). This model is comparable in predictive power to locally calibrated models, but relies on limited inputs of basal area and wood density information for a given region, rather than on traditional plot inventories. With this approach, we propose to radically decrease the time required to calibrate airborne LiDAR data and thus increase the output of high-resolution carbon maps, supporting tropical forest conservation and climate mitigation policy.

  2. 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.

  3. 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

  4. 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,

  5. Mapping Secondary Forest Succession on Abandoned Agricultural Land in the Polish Carpathians

    Science.gov (United States)

    Kolecka, N.; Kozak, J.; Kaim, D.; Dobosz, M.; Ginzler, Ch.; Psomas, A.

    2016-06-01

    Land abandonment and secondary forest succession have played a significant role in land cover changes and forest cover increase in mountain areas in Europe over the past several decades. Land abandonment can be easily observed in the field over small areas, but it is difficult to map over the large areas, e.g., with remote sensing, due to its subtle and spatially dispersed character. Our previous paper presented how the LiDAR (Light Detection and Ranging) and topographic data were used to detect secondary forest succession on abandoned land in one commune located in the Polish Carpathians by means of object-based image analysis (OBIA) and GIS (Kolecka et al., 2015). This paper proposes how the method can be applied to efficiently map secondary forest succession over the entire Polish Carpathians, incorporating spatial sampling strategy supported by various ancillary data. Here we discuss the methods of spatial sampling, its limitations and results in the context of future secondary forest succession modelling.

  6. MAPPING SECONDARY FOREST SUCCESSION ON ABANDONED AGRICULTURAL LAND IN THE POLISH CARPATHIANS

    Directory of Open Access Journals (Sweden)

    N. Kolecka

    2016-06-01

    Full Text Available Land abandonment and secondary forest succession have played a significant role in land cover changes and forest cover increase in mountain areas in Europe over the past several decades. Land abandonment can be easily observed in the field over small areas, but it is difficult to map over the large areas, e.g., with remote sensing, due to its subtle and spatially dispersed character. Our previous paper presented how the LiDAR (Light Detection and Ranging and topographic data were used to detect secondary forest succession on abandoned land in one commune located in the Polish Carpathians by means of object-based image analysis (OBIA and GIS (Kolecka et al., 2015. This paper proposes how the method can be applied to efficiently map secondary forest succession over the entire Polish Carpathians, incorporating spatial sampling strategy supported by various ancillary data. Here we discuss the methods of spatial sampling, its limitations and results in the context of future secondary forest succession modelling.

  7. Assessing the utility WorldView-2 imagery for tree species mapping in South African subtropical humid forest and the conservation implications: Dukuduku forest patch as case study

    Science.gov (United States)

    Cho, Moses Azong; Malahlela, Oupa; Ramoelo, Abel

    2015-06-01

    Indigenous forest biome in South Africa is highly fragmented into patches of various sizes (most patches non-timber resources by poor rural communities living around protected forest patches produce subtle changes in the forest canopy which can be hardly detected on a timely manner using traditional field surveys. The aims of this study were to assess: (i) the utility of very high resolution (VHR) remote sensing imagery (WorldView-2, 0.5-2 m spatial resolution) for mapping tree species and canopy gaps in one of the protected subtropical coastal forests in South Africa (the Dukuduku forest patch (ca.3200 ha) located in the province of KwaZulu-Natal) and (ii) the implications of the map products to forest conservation. Three dominant canopy tree species namely, Albizia adianthifolia, Strychnos spp. and Acacia spp., and canopy gap types including bushes (grass/shrubby), bare soil and burnt patches were accurately mapped (overall accuracy = 89.3 ± 2.1%) using WorldView-2 image and support vector machine classifier. The maps revealed subtle forest disturbances such as bush encroachment and edge effects resulting from forest fragmentation by roads and a power-line. In two stakeholders' workshops organised to assess the implications of the map products to conservation, participants generally agreed amongst others implications that the VHR maps provide valuable information that could be used for implementing and monitoring the effects of rehabilitation measures. The use of VHR imagery is recommended for timely inventorying and monitoring of the small and fragile patches of subtropical forests in Southern Africa.

  8. 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.

  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. Methodology for mapping non-forest wood elements using historic cadastral maps and aerial photographs as a basis for management.

    Science.gov (United States)

    Skalos, Jan; Engstová, Barbora

    2010-01-01

    The objective of this study was to test a method for analysing long-term structural changes in non-forest wood elements, using a newly developed classification system and relevant landscape characteristics. Although these non-forest wood elements are biotopes that have positive effects for the ecological stability of the landscape little is known about their long-term dynamics. The newly developed knowledge of the historical impact of various landscape management practices on non-forest wood elements can be applied in landscape planning procedures (e.g. planning ecological networks) in order to ensure relevant landscape management in the future. The method was applied in two contrasting study sites, Honbice (244 ha) and Krida (268 ha), located in east Bohemia and north Bohemia, in the Czech Republic. The study was based on old cadastral maps (from 1839 to 1843), black and white aerial photographs (from 1938, 1950, 1966, 1975 to 2006) and field control data from 2006. At the Honbice study site, the proportion of non-forest wood elements increased from 2.0 to 2.9% of the study site, due to large plantations of scattered vegetation in the open landscape. On the other hand, more than half of the wood vegetation in the village was cut down between 1966 and 2006. In addition, the relative length of the tree alleys decreased from 0.021 km ha(-1) to 0.018 km ha(-1) between 1950 and 1966. At the Krida study site, there was a significant increase in non-forest vegetation (from 2.4 to 8.2%), due to abandonment of the landscape (former military area). As the village disappeared, the total amount of scattered vegetation grew, due to the natural succession process. The relative length of the tree alleys decreased from 0.009 km ha(-1) to 0.005 km ha(-1). The method that was applied and based on the analysis of long-term structural changes in non-forest wood elements, using a (newly developed) classification system and relevant landscape characteristics has proved to be a suitable

  11. Mapping and Monitoring Forest Degradation in Indonesia Using Landsat time-series data sets from 1990 to 2010

    Science.gov (United States)

    Margono, B. A.; Potapov, P. V.; Hansen, M. C.

    2011-12-01

    Tropical deforestation and forest degradation accounts for over 18% of CO2 emissions globally. Timely and accurate information on forest extent and change is required for monitoring such changes to tropical forest. Remote sensing is perhaps the only effective means for tropical forest exploitation monitoring. Indonesian forests account for 2.3% of global forest cover, but monitoring in Indonesia faces challenges due to (i) unavailability of cloud free days due to climatic conditions, (ii) rapid reestablishment of tree cover by timber plantations, palm estates and subsequent secondary re-growth, and (iii) uncertainties in fractional land cover types in uneven terrain. A hybrid approach is presented here where an Intact Forest Landscape methodology, based on GIS-based buffering of observable disturbances is coupled with a per pixel mapping of old growth forest stands. Forest cover loss from 1990 to 2010 is mapped independently and trends in intact and degraded forest are quantified. Results advance the monitoring of forest cover and the carbon cycle required for UNFCCC REDD objectives to mitigate climate change by reducing carbon emissions from tropical forest exploitation.

  12. Structure and Evolution of Mediterranean Forest Research: A Science Mapping Approach.

    Directory of Open Access Journals (Sweden)

    Pierfrancesco Nardi

    Full Text Available This study aims at conducting the first science mapping analysis of the Mediterranean forest research in order to elucidate its research structure and evolution. We applied a science mapping approach based on co-term and citation analyses to a set of scientific publications retrieved from the Elsevier's Scopus database over the period 1980-2014. The Scopus search retrieved 2,698 research papers and reviews published by 159 peer-reviewed journals. The total number of publications was around 1% (N = 17 during the period 1980-1989 and they reached 3% (N = 69 in the time slice 1990-1994. Since 1995, the number of publications increased exponentially, thus reaching 55% (N = 1,476 during the period 2010-2014. Within the thirty-four years considered, the retrieved publications were published by 88 countries. Among them, Spain was the most productive country, publishing 44% (N = 1,178 of total publications followed by Italy (18%, N = 482 and France (12%, N = 336. These countries also host the ten most productive scientific institutions in terms of number of publications in Mediterranean forest subjects. Forest Ecology and Management and Annals of Forest Science were the most active journals in publishing research in Mediterranean forest. During the period 1980-1994, the research topics were poorly characterized, but they become better defined during the time slice 1995-1999. Since 2000s, the clusters become well defined by research topics. Current status of Mediterranean forest research (20092014 was represented by four clusters, in which different research topics such as biodiversity and conservation, land-use and degradation, climate change effects on ecophysiological responses and soil were identified. Basic research in Mediterranean forest ecosystems is mainly conducted by ecophysiological research. Applied research was mainly represented by land-use and degradation, biodiversity and conservation and fire research topics. The citation analyses

  13. Does early sexual debut reduce teenagers' participation in tertiary education? Evidence from the SHARE longitudinal study

    OpenAIRE

    Parkes, Alison; Wight, Daniel; Henderson, Marion; West, Patrick

    2010-01-01

    Negative effects of early sexual debut on academic outcomes can extend beyond secondary school, although concurrent changes in other psychosocial risk factors have not been investigated. Data from three waves of a longitudinal survey of Scottish teenagers were used to examine associations between early sexual debut (first heterosexual intercourse) and both expectations for (N = 5,061) and participation in (N = 2,130) tertiary education at college or university. Early debut was associated with...

  14. 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.

  15. Evaluation of Thematic Mapper data for mapping forest, agricultural and soil resources

    Science.gov (United States)

    Degloria, S.; Benson, A.; Dummer, K.; Fakhoury, E.

    1985-01-01

    Color composite TM film products which include TM5, TM4, and a visible band (TM1, TM2, or TM3) are superior to composites which exclude TM4 for discriminating most forest and agricultural cover types and estimating area proportions for inventory and sampling purposes. Clustering a subset of TM data results in a spectral class map which groups diverse forest cover types into spectrally and ecologically similar areas suitable for use as a stratification base in traditional forest inventory practices. Analysis of simulated Thematic Mapper data indicate that the location and number of TM spectral bands are suitable for detecting differences in major soil properties and characterizing soil spectral curve form and magnitude.

  16. A National, Detailed Map of Forest Aboveground Carbon Stocks in Mexico

    Directory of Open Access Journals (Sweden)

    Oliver Cartus

    2014-06-01

    Full Text Available A spatially explicit map of aboveground carbon stored in Mexico’s forests was generated from empirical modeling on forest inventory and spaceborne optical and radar data. Between 2004 and 2007, the Mexican National Forestry Commission (CONAFOR established a network of ~26,000 permanent inventory plots in the frame of their national inventory program, the Inventario Nacional Forestal y de Suelos (INFyS. INFyS data served as model response for spatially extending the field-based estimates of carbon stored in the aboveground live dry biomass to a wall-to-wall map, with 30 × 30 m2 pixel posting using canopy density estimates derived from Landsat, L-Band radar data from ALOS PALSAR, as well as elevation information derived from the Shuttle Radar Topography Mission (SRTM data set. Validation against an independent set of INFyS plots resulted in a coefficient of determination (R2 of 0.5 with a root mean square error (RMSE of 14 t∙C/ha in the case of flat terrain. The validation for different forest types showed a consistently low estimation bias (<3 t∙C/ha and R2s in the range of 0.5 except for mangroves (R2 = 0.2. Lower accuracies were achieved for forests located on steep slopes (>15° with an R2 of 0.34. A comparison of the average carbon stocks computed from: (a the map; and (b statistical estimates from INFyS, at the scale of ~650 km2 large hexagons (R2 of 0.78, RMSE of 5 t∙C/ha and Mexican states (R2 of 0.98, RMSE of 1.4 t∙C/ha, showed strong agreement.

  17. 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.

  18. Wide-Area Mapping of Forest with National Airborne Laser Scanning and Field Inventory Datasets

    Science.gov (United States)

    Monnet, J.-M.; Ginzler, C.; Clivaz, J.-C.

    2016-06-01

    Airborne laser scanning (ALS) remote sensing data are now available for entire countries such as Switzerland. Methods for the estimation of forest parameters from ALS have been intensively investigated in the past years. However, the implementation of a forest mapping workflow based on available data at a regional level still remains challenging. A case study was implemented in the Canton of Valais (Switzerland). The national ALS dataset and field data of the Swiss National Forest Inventory were used to calibrate estimation models for mean and maximum height, basal area, stem density, mean diameter and stem volume. When stratification was performed based on ALS acquisition settings and geographical criteria, satisfactory prediction models were obtained for volume (R2 = 0.61 with a root mean square error of 47 %) and basal area (respectively 0.51 and 45 %) while height variables had an error lower than 19%. This case study shows that the use of nationwide ALS and field datasets for forest resources mapping is cost efficient, but additional investigations are required to handle the limitations of the input data and optimize the accuracy.

  19. Phenology-Based Method for Mapping Tropical Evergreen Forests by Integrating of MODIS and Landsat Imagery

    Directory of Open Access Journals (Sweden)

    Weili Kou

    2017-01-01

    Full Text Available Updated extent, area, and spatial distribution of tropical evergreen forests from inventory data provides valuable knowledge for research of the carbon cycle, biodiversity, and ecosystem services in tropical regions. However, acquiring these data in mountainous regions requires labor-intensive, often cost-prohibitive field protocols. Here, we report about validated methods to rapidly identify the spatial distribution of tropical forests, and obtain accurate extent estimates using phenology-based procedures that integrate the Moderate Resolution Imaging Spectroradiometer (MODIS and Landsat imagery. Firstly, an analysis of temporal profiles of annual time-series MODIS Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, and Land Surface Water Index (LSWI was developed to identify the key phenology phase for extraction of tropical evergreen forests in five typical lands cover types. Secondly, identification signatures of tropical evergreen forests were selected and their related thresholds were calculated based on Landsat NDVI, EVI, and LSWI extracted from ground true samples of different land cover types during the key phenology phase. Finally, a map of tropical evergreen forests was created by a pixel-based thresholding. The developed methods were tested in Xishuangbanna, China, and the results show: (1 Integration of Landsat and MODIS images performs well in extracting evergreen forests in tropical complex mountainous regions. The overall accuracy of the resulting map of the case study was 92%; (2 Annual time series of high-temporal-resolution remote sensing images (MODIS can effectively be used for identification of the key phenology phase (between Julian Date 20 and 120 to extract tropical evergreen forested areas through analysis of NDVI, EVI, and LSWI of different land cover types; (3 NDVI and LSWI are two effective metrics (NDVI ≥ 0.670 and 0.447 ≥ LSWI ≥ 0.222 to depict evergreen forests from other land cover

  20. 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 ...

  1. Mapping Aboveground Biomass using Texture Indices from Aerial Photos in a Temperate Forest of Northeastern China

    Directory of Open Access Journals (Sweden)

    Shili Meng

    2016-03-01

    Full Text Available Optical remote sensing data have been considered to display signal saturation phenomena in regions of high aboveground biomass (AGB and multi-storied forest canopies. However, some recent studies using texture indices derived from optical remote sensing data via the Fourier-based textural ordination (FOTO approach have provided promising results without saturation problems for some tropical forests, which tend to underestimate AGB predictions. This study was applied to the temperate mixed forest of the Liangshui National Nature Reserve in Northeastern China and demonstrated the capability of FOTO texture indices to obtain a higher prediction quality of forest AGB. Based on high spatial resolution aerial photos (1.0 m spatial resolution acquired in September 2009, the relationship between FOTO texture indices and field-derived biomass measurements was calibrated using a support vector regression (SVR algorithm. Ten-fold cross-validation was used to construct a robust prediction model, which avoided the over-fitting problem. By further comparison the performance of the model estimates for greater coverage, the predicted results were compared with a reference biomass map derived from LiDAR metrics. This study showed that the FOTO indices accounted for 88.3% of the variance in ground-based AGB; the root mean square error (RMSE was 34.35 t/ha, and RMSE normalized by the mean value of the estimates was 22.31%. This novel texture-based method has great potential for forest AGB estimation in other temperate regions.

  2. 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.

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

    Science.gov (United States)

    Chen, Youhua; Peng, Shushi

    2017-01-01

    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. PMID:28300200

  4. 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.

  5. Consistent forest change maps 1981 – 2000 from the AVHRR time series. Case studies for South America and Indonesia

    NARCIS (Netherlands)

    Eberenz, J.; Herold, M.; Verbesselt, J.; Wijaya, A.; Lindquist, E.; Defourny, P.; Gibbs, H.K.; Arino, O.; Achard, F.

    2015-01-01

    This study predicts global forest cover change for the 1980s and 1990s from AVHRR time series metrics in order to show how the series of consistent land cover maps for climate modeling produced by the ESA climate change initiative land cover project can be extended back in time. A Random Forest mode

  6. On Clear-Cut Mapping with Time-Series of Sentinel-1 Data in Boreal Forest

    Science.gov (United States)

    Rauste, Yrjo; Antropov, Oleg; Mutanen, Teemu; Hame, Tuomas

    2016-08-01

    Clear-cutting is the most drastic and wide-spread change that affects the hydrological and carbon-balance proper- ties of forested land in the Boreal forest zone1.A time-series of 36 Sentinel-1 images was used to study the potential for mapping clear-cut areas. The time series covered one and half year (2014-10-09 ... 2016-03-20) in a 200-km-by-200-km study site in Finland. The Sentinel- 1 images were acquired in Interferometric Wide-swath (IW), dual-polarized mode (VV+VH). All scenes were acquired in the same orbit configuration. Amplitude im- ages (GRDH product) were used. The Sentinel-1 scenes were ortho-rectified with in-house software using a digi- tal elevation model (DEM) produced by the Land Survey of Finland. The Sentinel-1 amplitude data were radio- metrically corrected for topographic effects.The temporal behaviour of C-band backscatter was stud- ied for areas representing 1) areas clear-cut during the ac- quisition of the Sentinel-1 time-series, 2) areas remaining forest during the acquisition of the Sentinel-1 time-series, and 3) areas that had been clear-cut before the acquisition of the Sentinel-1 time-series.The following observations were made:1. The separation between clear-cut areas and forest was generally low;2. Under certain acquisition conditions, clear-cut areas were well separable from forest;3. The good scenes were acquired: 1) in winter during thick snow cover, and 2) in late summer towards the end of a warm and dry period;4. The separation between clear-cut and forest was higher in VH polarized data than in VV-polarized data.5. The separation between clear-cut and forest was higher in the winter/snow scenes than in the dry summer scenes.

  7. Aboveground biomass mapping in French Guiana by combining remote sensing, forest inventories and environmental data

    Science.gov (United States)

    Fayad, Ibrahim; Baghdadi, Nicolas; Guitet, Stéphane; Bailly, Jean-Stéphane; Hérault, Bruno; Gond, Valéry; El Hajj, Mahmoud; Tong Minh, Dinh Ho

    2016-10-01

    Mapping forest aboveground biomass (AGB) has become an important task, particularly for the reporting of carbon stocks and changes. AGB can be mapped using synthetic aperture radar data (SAR) or passive optical data. However, these data are insensitive to high AGB levels (>150 Mg/ha, and >300 Mg/ha for P-band), which are commonly found in tropical forests. Studies have mapped the rough variations in AGB by combining optical and environmental data at regional and global scales. Nevertheless, these maps cannot represent local variations in AGB in tropical forests. In this paper, we hypothesize that the problem of misrepresenting local variations in AGB and AGB estimation with good precision occurs because of both methodological limits (signal saturation or dilution bias) and a lack of adequate calibration data in this range of AGB values. We test this hypothesis by developing a calibrated regression model to predict variations in high AGB values (mean >300 Mg/ha) in French Guiana by a methodological approach for spatial extrapolation with data from the optical geoscience laser altimeter system (GLAS), forest inventories, radar, optics, and environmental variables for spatial inter- and extrapolation. Given their higher point count, GLAS data allow a wider coverage of AGB values. We find that the metrics from GLAS footprints are correlated with field AGB estimations (R2 = 0.54, RMSE = 48.3 Mg/ha) with no bias for high values. First, predictive models, including remote-sensing, environmental variables and spatial correlation functions, allow us to obtain "wall-to-wall" AGB maps over French Guiana with an RMSE for the in situ AGB estimates of ∼50 Mg/ha and R2 = 0.66 at a 1-km grid size. We conclude that a calibrated regression model based on GLAS with dependent environmental data can produce good AGB predictions even for high AGB values if the calibration data fit the AGB range. We also demonstrate that small temporal and spatial mismatches between field data and GLAS

  8. Large-scale 3D mapping of the intergalactic medium using the Lyman Alpha Forest

    CERN Document Server

    Ozbek, Melih; Khandai, Nishikanta

    2016-01-01

    Maps of the large-scale structure of the Universe at redshifts 2-4 can be made with the Lyman-alpha forest which are complementary to low redshift galaxy surveys. We apply the Wiener interpolation method of Caucci et al. to construct three-dimensional maps from sets of Lyman-alpha forest spectra taken from cosmological hydrodynamic simulations. We mimic some current and future quasar redshift surveys (BOSS, eBOSS and MS-DESI) by choosing similar sightline densities. We use these appropriate subsets of the Lyman-alpha absorption sightlines to reconstruct the full three dimensional Lyman-alpha flux field and perform comparisons between the true and the reconstructed fields. We study global statistical properties of the intergalactic medium (IGM) maps with auto-correlation and cross-correlation analysis, slice plots, local peaks and point by point scatter. We find that both the density field and the statistical proper- ties of the IGM are recovered well enough that the resulting IGM maps can be meaningfully cons...

  9. 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.

  10. 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…

  11. Father Knows Best: Paternal Presence and Sexual Debut in African-American Adolescents Living in Poverty.

    Science.gov (United States)

    Langley, Cheri

    2016-03-01

    Adolescents found within single-parent families without a residential father have reported higher levels of sexual debut and higher levels of reported pregnancy. Using data from the Mobile Youth Survey, the purpose of this study is to determine the impact of the presence of a father figure on the sexual debut of African-American adolescents living in poverty and to determine if gender moderates the relationship between the presence of a father figure and sexual debut. Additionally, this study will examine the family processes in which the presence of a father figure can affect the sexual debut of African-American adolescents who live within economically and socially disadvantaged communities. The results revealed that African-American adolescents reporting a father figure had lower rates of sexual debut than those youth reporting no father figure. Gender was not found to be a significant moderator in the relationship between father figure presence and sexual debut. However, existing curfews and family rules did account for some of the effects of presence of a father figure and sexual debut. The results suggest that when adolescents have a father figure in their lives, it may reduce the possibility of early sexual debut.

  12. 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…

  13. Overcoming Limitations with Landsat Imagery for Mapping of Peat Swamp Forests in Sundaland

    Directory of Open Access Journals (Sweden)

    Gopalasamy R. Clements

    2012-09-01

    Full Text Available Landsat can be used to map tropical forest cover at 15–60 m resolution, which is helpful for detecting small but important perturbations in increasingly fragmented forests. However, among the remaining Landsat satellites, Landsat-5 no longer has global coverage and, since 2003, a mechanical fault in the Scan-Line Corrector (SLC-Off of the Landsat-7 satellite resulted in a 22–25% data loss in each image. Such issues challenge the use of Landsat for wall-to-wall mapping of tropical forests, and encourage the use of alternative, spatially coarser imagery such as MODIS. Here, we describe and test an alternative method of post-classification compositing of Landsat images for mapping over 20.5 million hectares of peat swamp forest in the biodiversity hotspot of Sundaland. In order to reduce missing data to levels comparable to those prior to the SLC-Off error, we found that, for a combination of Landsat-5 images and SLC-off Landsat-7 images used to create a 2005 composite, 86% of the 58 scenes required one or two images, while 14% required three or more images. For a 2010 composite made using only SLC-Off Landsat-7 images, 64% of the scenes required one or two images and 36% required four or more images. Missing-data levels due to cloud cover and shadows in the pre SLC-Off composites (7.8% and 10.3% for 1990 and 2000 enhanced GeoCover mosaics are comparable to the post SLC-Off composites (8.2% and 8.3% in the 2005 and 2010 composites. The area-weighted producer’s accuracy for our 2000, 2005 and 2010 composites were 77%, 85% and 86% respectively. Overall, these results show that missing-data levels, classification accuracy, and geographic coverage of Landsat composites are comparable across a 20-year period despite the SLC-Off error since 2003. Correspondingly, Landsat still provides an appreciable utility for monitoring tropical forests, particularly in Sundaland’s rapidly disappearing peat swamp forests.

  14. 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.

  15. 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

  16. Predictors of sexual debut at age 16 or younger.

    Science.gov (United States)

    Cavazos-Rehg, Patricia A; Spitznagel, Edward L; Bucholz, Kathleen K; Nurnberger, John; Edenberg, Howard J; Kramer, John R; Kuperman, Samuel; Hesselbrock, Victor; Bierut, Laura Jean

    2010-06-01

    The present study examined the extent to which variables within the self system (i.e., symptoms of alcohol dependence and conduct disorder, gender, race, and metropolitan status) and the familial system (i.e., having an alcohol dependent biological parent or second-degree relative, religious background, educational background of parents, and being born to a teenage mother) were associated with sexual debut at 16 years old or earlier. Participants were 1,054 biological relatives, aged 18-25 years, of alcohol dependent probands who participated in the Collaborative Study on the Genetics of Alcoholism project. Comparison participants (N = 234) without alcohol dependent biological parents were also evaluated. Clinical and sociodemographic variables were assessed by structured, personal interviews. Parental history of alcohol dependence was evaluated by direct interview of parents in most cases and family history in uninterviewed parents. In a multivariate survival analysis, increased risk of becoming sexually active at 16 years of age or earlier was significantly associated with 6 of the 10 predictor variables, including race, one or more alcohol dependence symptoms, and/or one or more conduct disorder symptoms. Having an alcohol dependent biological parent or second-degree relative (e.g., aunt, uncle, or grandparent), educational background of mother, and being born to a teenage mother were also significantly associated with increased risk. These results provide evidence that specific variables in the self and familial systems of influence are important in predicting sexual debut at 16 years old or earlier.

  17. Mapping permanent preservation areas and natural forest fragments as subsidy to the registration of legal reserve areas in rural properties

    Directory of Open Access Journals (Sweden)

    Vicente Paulo Soares

    2011-12-01

    Full Text Available The major objective of this work was to identify and quantify forest fragments suitable to be used as private protected land in rural properties located in the São Bartolomeu creek watershed, State of Minas Gerais, Brazil. The methodological procedures included: mapping of 78 forest fragments through the visual interpretation of an Ikonos II satellite image; delineation of Permanent Preservation Areas (PPAs from a hydrographically conditioned digital elevation model and mapping of 292 rural properties through interviews with owners, with the aid of a printed Ikonos II image. The generated maps were overlapped (crossed, allowing the identification of forest fragments that could be used as private protected land in rural property. The result indicated that, from the total of properties evaluated, only 41 (14.04% have more than 20% of forest cover, and therefore, are in condition to attend the environmental law for private protected land.

  18. Using InSAR Coherence to Map Stand Age in a Boreal Forest

    Directory of Open Access Journals (Sweden)

    Naiara Pinto

    2012-12-01

    Full Text Available The interferometric coherence parameter γ estimates the degree of correlation between two Synthetic Aperture Radar (SAR images and can be influenced by vegetation structure. Here, we investigate the use of repeat-pass interferometric coherence γ to map stand age, an important parameter for the study of carbon stocks and forest regeneration. In August 2009 NASA’s L-band airborne sensor UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar acquired zero-baseline data over Quebec with temporal separation ranging between 45 min and 9 days. Our analysis focuses on a 66 km2 managed boreal forest and addresses three questions: (i Can coherence from L-band systems be used to model forest age? (ii Are models sensitive to weather events and temporal baseline? and (iii How is model accuracy impacted by the spatial scale of analysis? Linear regression models with 2-day baseline showed the best results and indicated an inverse relationship between γ and stand age. Model accuracy improved at 5 ha scale (R2 = 0.75, RMSE = 5.3 as compared to 1 ha (R2 = 0.67, RMSE = 5.8. Our results indicate that coherence measurements from L-band repeat-pass systems can estimate forest age accurately and with no saturation. However, empirical model relationships and their accuracy are sensitive to weather events, temporal baseline, and spatial scale of analysis.

  19. Mapping Social and Economic Vulnerability in Forest and Peatland Fire Disaster in Bengkalis Regency, Riau Province

    Directory of Open Access Journals (Sweden)

    Eko Ahmad Riyanto

    2015-08-01

    Full Text Available The aims of this research are (1 analyzing social and economic vulnerability of forest and peat land fire disaster in Bengkalis Regency; (2 Mapping social and economic vulnerability of forest and peat land fire disaster in Bengkalis Regency.  Research Variable is social and economic vulnerability. The data that used is primary and secondary data with survey method. Analysis method is scoring and weightings. After that classified based on the value of the score to determine the level of vulnerability. The analysis based on the head of National Agency for Disaster Management (Perka BNPB Number 02.2012 and literatures study. The results of research show that social vulnerability of forest and peat land fire in Bengkalis Regency is medium vulnerability because it has value of social vulnerability is 0.46663. While economic vulnerability in Bengkalis Regency is low vulnerability because economic vulnerability is 0.3333. In addition, required mitigation that is quick and appropriate by governments of Bengkalis Regency and the local community in management of forest and peat land fire disaster.

  20. Rapid, High-Resolution Forest Structure and Terrain Mapping over Large Areas using Single Photon Lidar.

    Science.gov (United States)

    Swatantran, Anu; Tang, Hao; Barrett, Terence; DeCola, Phil; Dubayah, Ralph

    2016-06-22

    Single photon lidar (SPL) is an innovative technology for rapid forest structure and terrain characterization over large areas. Here, we evaluate data from an SPL instrument - the High Resolution Quantum Lidar System (HRQLS) that was used to map the entirety of Garrett County in Maryland, USA (1700 km(2)). We develop novel approaches to filter solar noise to enable the derivation of forest canopy structure and ground elevation from SPL point clouds. SPL attributes are compared with field measurements and an existing leaf-off, low-point density discrete return lidar dataset as a means of validation. We find that canopy and ground characteristics from SPL are similar to discrete return lidar despite differences in wavelength and acquisition periods but the higher point density of the SPL data provides more structural detail. Our experience suggests that automated noise removal may be challenging, particularly over high albedo surfaces and rigorous instrument calibration is required to reduce ground measurement biases to accepted mapping standards. Nonetheless, its efficiency of data collection, and its ability to produce fine-scale, three-dimensional structure over large areas quickly strongly suggests that SPL should be considered as an efficient and potentially cost-effective alternative to existing lidar systems for large area mapping.

  1. Rapid, High-Resolution Forest Structure and Terrain Mapping over Large Areas using Single Photon Lidar

    Science.gov (United States)

    Swatantran, Anu; Tang, Hao; Barrett, Terence; Decola, Phil; Dubayah, Ralph

    2016-06-01

    Single photon lidar (SPL) is an innovative technology for rapid forest structure and terrain characterization over large areas. Here, we evaluate data from an SPL instrument - the High Resolution Quantum Lidar System (HRQLS) that was used to map the entirety of Garrett County in Maryland, USA (1700 km2). We develop novel approaches to filter solar noise to enable the derivation of forest canopy structure and ground elevation from SPL point clouds. SPL attributes are compared with field measurements and an existing leaf-off, low-point density discrete return lidar dataset as a means of validation. We find that canopy and ground characteristics from SPL are similar to discrete return lidar despite differences in wavelength and acquisition periods but the higher point density of the SPL data provides more structural detail. Our experience suggests that automated noise removal may be challenging, particularly over high albedo surfaces and rigorous instrument calibration is required to reduce ground measurement biases to accepted mapping standards. Nonetheless, its efficiency of data collection, and its ability to produce fine-scale, three-dimensional structure over large areas quickly strongly suggests that SPL should be considered as an efficient and potentially cost-effective alternative to existing lidar systems for large area mapping.

  2. Mapping species distribution of Canarian Monteverde forest by field spectroradiometry and satellite imagery

    Science.gov (United States)

    Martín-Luis, Antonio; Arbelo, Manuel; Hernández-Leal, Pedro; Arbelo-Bayó, Manuel

    2016-10-01

    Reliable and updated maps of vegetation in protected natural areas are essential for a proper management and conservation. Remote sensing is a valid tool for this purpose. In this study, a methodology based on a WorldView-2 (WV-2) satellite image and in situ spectral signatures measurements was applied to map the Canarian Monteverde ecosystem located in the north of the Tenerife Island (Canary Islands, Spain). Due to the high spectral similarity of vegetation species in the study zone, a Multiple Endmember Spectral Mixture Analysis (MESMA) was performed. MESMA determines the fractional cover of different components within one pixel and it allows for a pixel-by-pixel variation of endmembers. Two libraries of endmembers were collected for the most abundant species in the test area. The first library was collected from in situ spectral signatures measured with an ASD spectroradiometer during a field campaign in June 2015. The second library was obtained from pure pixels identified in the satellite image for the same species. The accuracy of the mapping process was assessed from a set of independent validation plots. The overall accuracy for the ASD-based method was 60.51 % compared to the 86.67 % reached for the WV-2 based mapping. The results suggest the possibility of using WV-2 images for monitoring and regularly updating the maps of the Monteverde forest on the island of Tenerife.

  3. Integration of satellite imagery and forest inventory in mapping dominant and associated species at a regional scale.

    Science.gov (United States)

    Zhang, Yangjian; He, Hong S; Dijak, William D; Yang, Jian; Shifley, Stephen R; Palik, Brian J

    2009-08-01

    To achieve the overall objective of restoring natural environment and sustainable resource usability, each forest management practice effect needs to be predicted using a simulation model. Previous simulation efforts were typically confined to public land. Comprehensive forest management practices entail incorporating interactions between public and private land. To make inclusion of private land into management planning feasible at the regional scale, this study uses a new method of combining Forest Inventory and Analysis (FIA) data with remotely sensed forest group data to retrieve detailed species composition and age information for the Missouri Ozark Highlands. Remote sensed forest group and land form data inferred from topography were integrated to produce distinct combinations (ecotypes). Forest types and size classes were assigned to ecotypes based on their proportions in the FIA data. Then tree species and tree age determined from FIA subplots stratified by forest type and size class were assigned to pixels for the entire study area. The resulting species composition map can improve simulation model performance in that it has spatially explicit and continuous information of dominant and associated species, and tree ages that are unavailable from either satellite imagery or forest inventory data. In addition, the resulting species map revealed that public land and private land in Ozark Highlands differ in species composition and stand size. Shortleaf pine is a co-dominant species in public land, whereas it becomes a minor species in private land. Public forest is older than private forest. Both public and private forests have deviated from historical forest condition in terms of species composition. Based on possible reasons causing the deviation discussed in this study, corresponding management avenues that can assist in restoring natural environment were recommended.

  4. Factors of Forest Loss using An Object-based Mapping Method -A Case Study in North America

    Science.gov (United States)

    Wang, L.; Ying, Q.; Potapov, P.; Hansen, M.

    2014-12-01

    Changes in forest cover affect the delivery of important ecosystem services, including biodiversity richness, climate regulation, carbon storage, and water supplies. In 2013, Hansen et al. published a scientific paper in Science. They mapped global tree cover extent, loss and gain for the period from 2000 to 2012 at a spatial resolution of 30m, with loss allocated annually. They found a total of 2.3 million km2 of forest loss and 0.8 million km 2 of new forest established. Concerning loss, all stand-replacement disturbances were mapped, including mechanical removal (logging), fire and other factors such as storms and disease. The implications on carbon cycle dynamics are very different for these various causes of forest loss. For example, emissions from the various change dynamics vary greatly, and labeling forest loss by change factor will improve carbon cycle and carbon accounting efforts. In this study, we will try to distinguish forest loss caused by fire and logging from other causes. We take Canada and the continental US as the study area, which were estimated to have lost 52.8 MHa forest from 2000 to 2012. Our preliminary results show that fire and logging are the dominant factors (>90%) of North American forest loss. We employ annual minimum NDVI band, annual ETM+ composites for band 3, band 4, band 5, band 7 from 1999 to 2012, and three derived bands from ETM+ composites (dataset A), together with the annual 30m global forest loss map (2001- 2012) (dataset B). The method can be divided into four parts: 1. Generate patches from dataset B. 2. Extract shape, spectral, texture and contextual features from dataset A, with a total of 445 features for each patch; 3. Classify the patches with those features using a bagged regression tree model; 4. Validate and evaluate the results. Mapping results and analysis will be presented at the meeting.

  5. Remote Sensing and GIS Based Risk Index Map For Predicting Forest Fire Danger - Evaluation From Forestry Datasets, India

    Science.gov (United States)

    Prasad, V. K.; Badarinath, K. V. S.

    Forest fires constitute one of the most serious ecological as well as environmental problems affecting most vegetation zones across the world, including India. In this study, we evaluated forest fire risk for sixteen different forest and vegetation types of India. Data from Normalized Difference Vegetation Index (NDVI) from NOAA AVHRR data has been integrated with bioclimatic data and fuel value index to quantify the forest fire risk. Biomass data for different forest types in different pools has been used as ancillary data. In using the fuel value index, calorific value of wood content for 60 species has been collected and aggregated, for specific species. Results from NDVI and precipitation correlations were found to be highly significant for tropical dry deciduous and moist deciduous forests. Spatial patterns in NDVI closely followed seasonal trends in precipitation for most of the forests. An integrated GIS framework with biophysical, biomass, thermo chemical and bioclimatic parameters allowed the calculation of risk indices for the different forest types. The methodology followed in the study and the maps produced are found to be useful for evaluating forest fire risk and for predicting forest fire danger in different vegetation zones in India.

  6. 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

  7. [Peer social pressure on the sexual debut of adolescents].

    Science.gov (United States)

    Borges, Ana Luiza Vilela

    2007-12-01

    Considering that scientific articles have emphasized the link between the onset of sexual life and peer pressure, the aim of this study was to identify peer pressure in the adolescents' sexual initiation from the point of view of their relationship with the group of friends. A cross-sectional study was conducted among 363 15-19 year-old teens that represented a sample ofthe adolescents enrolled in a family health unit in Sao Paulo City, Brazil. Results showed a relation between sexual initiation and age, being involved in physical experience with someone without wishing, having the majority of friends with sexual experience and dating. Eventually, data show that peers might play some influence on adolescents' option for sexual debut.

  8. Determinants of condom use at sexual debut among young Vietnamese.

    Science.gov (United States)

    Do, Trang H T; Le, Linh C; Burgess, John A; Bui, Dinh S

    2014-01-01

    Condom use at sexual debut is associated with subsequent condom use and with decreased risk of sexually transmitted infections. There is a dearth of data on determinants of condom use at first sexual intercourse. We aimed to determine factors associated with condom use at first sexual intercourse before marriage among Vietnamese adolescents and youths. The study involved the analysis of data from the Survey Assessment of Vietnamese Youth, 2003, the first nationally representative survey of young people in Vietnam. The survey included 7584 adolescents and youths aged 14-25 years. In this study, data of 605 adolescents and youths who had engaged in premarital sex were analyzed for factors associated with condom use using descriptive analyses, and regression techniques, allowing for sampling weights, clustering and stratification. Of 605 adolescents and youths who had engaged in premarital sex, 28.6% reported condom use at first sexual intercourse. Condom use at sexual debut was less common in females than males [odds ratio (OR)=0.15; 95% confidence interval (95% CI)=0.07-0.30] and less common in those who experienced peer pressure to engage in social higher risk behaviors (OR=0.57; 95% CI=0.32-0.99). Condom use was more common if a friend/acquaintance or a stranger/sex worker was the first sexual partner (OR=2.20; 95% CI=1.16-4.17 and OR=17.90; 95% CI=6.88-46.54) respectively, each compared with fiancé/boyfriend/girlfriend as first sexual partner. These data suggest that approximately one in three unmarried Vietnamese youths used a condom at first sexual intercourse. Gender, peer pressure and the nature of the relationship to the first sexual partner were independently associated with condom use. These results can inform programs directed at preventing HIV and other sexually transmitted infections among young Vietnamese.

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

    Science.gov (United States)

    Hengl, Tomislav; Heuvelink, Gerard B M; Kempen, Bas; Leenaars, Johan G B; Walsh, Markus G; Shepherd, Keith D; Sila, Andrew; MacMillan, Robert A; Mendes de Jesus, Jorge; Tamene, Lulseged; Tondoh, Jérôme E

    2015-01-01

    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 pedological

  10. Cadastre (forest maps) and spatial land uses planning, strategic tool for sustainable development

    Science.gov (United States)

    Drosos, Vasileios C.

    2014-08-01

    The rise in the living standards of the Greeks created, especially since 1970, along with other needs and the need for second or holiday home since 1990 after finding the first house on the outskirts of large urban centers. Trying to find land for the creation of new resorts or new type of permanent residences (maisonettes with or without garden, depending on the financial position of each) had the painful consequence of wasteful and uncontrolled use of land, without a program, without the fundamental rules of land planning and the final creation was usually unsightly buildings. The costs were to pay as usually the forest rural lands. The national spatial planning of land use requires that we know the existing land uses in this country, and based on that we can design and decide their land uses on the future in a rational way. On final practical level, this planning leads to mark the boundaries of specific areas of land that are permitted and may change uses. For this reason, one of the most valuable "tools" of that final marking the boundaries is also the forest maps. The paper aims the investigation to determine the modern views on the issues of Cadastre and Land Management with an ulterior view to placing the bases for creating a building plan of an immediate completion of forest maps. Sustainable development as a term denoting a policy of continued economic and social development that does not involve the destruction of the environment and natural resources, but rather guarantees their rational viability.

  11. Multi-Scale Mapping of Forest Growing Stock Volume Using Envisat ASAR, ALOS PALSAR Landsat, and ICESat GLAS

    Science.gov (United States)

    Cartus, Oliver; Santoro, Maurizio

    2016-08-01

    Multi-scale approaches for mapping aboveground biomass globally are evaluated that exploit the multi- temporal archive of low-resolution (1 km) ENVISAT ASAR C-band observations and ca. 30 m resolution ALOS PALSAR L-band and Landsat mosaics. The BIOMASAR algorithm, which was initially developed for ENVISAT ASAR C-band data and boreal forest [1], is deployed to map growing stock volume, a proxy for aboveground biomass, globally at 1 km resolution. We explore different options for improving ASAR based maps using high resolution data. Two approaches are pursued: 1) the BIOMASAR algorithm adopted for L- band, 2) a simple re-scaling of ASAR derived estimates of growing stock volume from 1 km pixel posting to 30 m using PALSAR and Landsat data [2]. The initial results for different forest ecosystems suggest that both approaches allow for improved estimates, albeit with the expected limitations in high biomass forests.

  12. 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

  13. Pan-Tropical Forest Mapping by Exploiting Textures of Multi-Temporal High Resolution SAR Data

    Science.gov (United States)

    Knuth, R.; Eckardt, R.; Richter, N.; Schmullius, C.

    2012-12-01

    radar images were processed using an operational processing chain that includes radiometric transformation, noise reduction, and georeferencing of the SAR data. In places with pronounced topography both satellites were used as single pass interferometer to derive a digital surface model in order to perform an orthorectification followed by a topographic normalization of the SAR backscatter values. As prescribed by the FAO, the final segment-based classification algorithm was fed by multi-temporal backscatter information, a set of textural features, and information on the degree of coherence between the multi-temporal acquisitions. Validation with available high resolution optical imagery suggests that the produced forest maps possess an overall accuracy of 75 percent or higher.

  14. Development of a Methodology for Mapping Forest Height and Biomass Using Satellite Based SAR and Lidar Data

    Science.gov (United States)

    Hilbert, Claudia; Schmullius, Christiane

    2010-12-01

    This paper presents first results of a study investigating satellite, multifrequent radar and lidar data for characterising the three-dimensional forest structure. Biomass is an important structural parameter to asses the carbon pool of forests. The synergy of lidar and SAR data for forest biomass mapping is promising. The study introduced here aims to combine TerraSAR-X, ALOS PALSAR and ICESat/GLAS data. Some preliminary results for the test site in Thuringian Forest, a low mountain range in eastern Germany, with a focus on the GLAS data will be described. Two methods for filtering invalid GLAS shots are investigated. Moreover, different ICESat/GLAS waveforms parameters were calculated and compared to an airborne lidar based Digital Height Model (DHM) and a forest inventory data base.

  15. Comparison of point counts and territory mapping for detecting effects of forest management on songbirds

    Science.gov (United States)

    Newell, Felicity L.; Sheehan, James; Wood, Petra Bohall; Rodewald, Amanda D.; Buehler, David A.; Keyser, Patrick D.; Larkin, Jeffrey L.; Beachy, Tiffany A.; Bakermans, Marja H.; Boves, Than J.; Evans, Andrea; George, Gregory A.; McDermott, Molly E.; Perkins, Kelly A.; White, Matthew; Wigley, T. Bently

    2013-01-01

    Point counts are commonly used to assess changes in bird abundance, including analytical approaches such as distance sampling that estimate density. Point-count methods have come under increasing scrutiny because effects of detection probability and field error are difficult to quantify. For seven forest songbirds, we compared fixed-radii counts (50 m and 100 m) and density estimates obtained from distance sampling to known numbers of birds determined by territory mapping. We applied point-count analytic approaches to a typical forest management question and compared results to those obtained by territory mapping. We used a before–after control impact (BACI) analysis with a data set collected across seven study areas in the central Appalachians from 2006 to 2010. Using a 50-m fixed radius, variance in error was at least 1.5 times that of the other methods, whereas a 100-m fixed radius underestimated actual density by >3 territories per 10 ha for the most abundant species. Distance sampling improved accuracy and precision compared to fixed-radius counts, although estimates were affected by birds counted outside 10-ha units. In the BACI analysis, territory mapping detected an overall treatment effect for five of the seven species, and effects were generally consistent each year. In contrast, all point-count methods failed to detect two treatment effects due to variance and error in annual estimates. Overall, our results highlight the need for adequate sample sizes to reduce variance, and skilled observers to reduce the level of error in point-count data. Ultimately, the advantages and disadvantages of different survey methods should be considered in the context of overall study design and objectives, allowing for trade-offs among effort, accuracy, and power to detect treatment effects.

  16. 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...

  17. Land cover mapping based on random forest classification of multitemporal spectral and thermal images.

    Science.gov (United States)

    Eisavi, Vahid; Homayouni, Saeid; Yazdi, Ahmad Maleknezhad; Alimohammadi, Abbas

    2015-05-01

    Thematic mapping of complex landscapes, with various phenological patterns from satellite imagery, is a particularly challenging task. However, supplementary information, such as multitemporal data and/or land surface temperature (LST), has the potential to improve the land cover classification accuracy and efficiency. In this paper, in order to map land covers, we evaluated the potential of multitemporal Landsat 8's spectral and thermal imageries using a random forest (RF) classifier. We used a grid search approach based on the out-of-bag (OOB) estimate of error to optimize the RF parameters. Four different scenarios were considered in this research: (1) RF classification of multitemporal spectral images, (2) RF classification of multitemporal LST images, (3) RF classification of all multitemporal LST and spectral images, and (4) RF classification of selected important or optimum features. The study area in this research was Naghadeh city and its surrounding region, located in West Azerbaijan Province, northwest of Iran. The overall accuracies of first, second, third, and fourth scenarios were equal to 86.48, 82.26, 90.63, and 91.82%, respectively. The quantitative assessments of the results demonstrated that the most important or optimum features increase the class separability, while the spectral and thermal features produced a more moderate increase in the land cover mapping accuracy. In addition, the contribution of the multitemporal thermal information led to a considerable increase in the user and producer accuracies of classes with a rapid temporal change behavior, such as crops and vegetation.

  18. Development of an object-based classification model for mapping mountainous forest cover at high elevation using aerial photography

    Science.gov (United States)

    Lateb, Mustapha; Kalaitzidis, Chariton; Tompoulidou, Maria; Gitas, Ioannis

    2016-08-01

    Climate change and overall temperature increase results in changes in forest cover in high elevations. Due to the long life cycle of trees, these changes are very gradual and can be observed over long periods of time. In order to use remote sensing imagery for this purpose it needs to have very high spatial resolution and to have been acquired at least 50 years ago. At the moment, the only type of remote sensing imagery with these characteristics is historical black and white aerial photographs. This study used an aerial photograph from 1945 in order to map the forest cover at the Olympus National Park, at that date. An object-based classification (OBC) model was developed in order to classify forest and discriminate it from other types of vegetation. Due to the lack of near-infrared information, the model had to rely solely on the tone of the objects, as well as their geometric characteristics. The model functioned on three segmentation levels, using sub-/super-objects relationships and utilising vegetation density to discriminate forest and non-forest vegetation. The accuracy of the classification was assessed using 503 visually interpreted and randomly distributed points, resulting in a 92% overall accuracy. The model is using unbiased parameters that are important for differentiating between forest and non-forest vegetation and should be transferrable to other study areas of mountainous forests at high elevations.

  19. Sexual debut in young adults in Cali as transition: keys for care

    OpenAIRE

    Claudia Patricia Valencia Molina; Gladys Eugenia Canaval Erazo; Teresita María Sevilla Peñuela; Linda Teresa Orcasita Pineda

    2015-01-01

    Objectives. This work sought to understand sexual debut as a transitional process in the lives of a group of young adults and to interpret the meaning of this transition for them. Methodology. This was a qualitative research with 18 life stories of students from different socio-economic backgrounds and with diverse sexual orientations. Results. According to the middle-range theory of transitions, sexual debut can be considered a developmental transition. The initiative can be their own, motiv...

  20. 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.

  1. Experimenting the design-based k-NN approach for mapping and estimation under forest management planning

    Directory of Open Access Journals (Sweden)

    Mattioli W

    2012-02-01

    Full Text Available Estimation and mapping of forest attributes are a fundamental support for forest management planning. This study describes a practical experimentation concerning the use of design-based k-Nearest Neighbors (k-NN approach to estimate and map selected attributes in the framework of inventories at forest management level. The study area was the Chiarino forest within the Gran Sasso and Monti della Laga National Park (central Italy. Aboveground biomass and current annual increment of tree volume were selected as the attributes of interest for the test. Field data were acquired within 28 sample plots selected by stratified random sampling. Satellite data were acquired by a Landsat 5 TM multispectral image. Attributes from field surveys and Landsat image processing were coupled by k-NN to predict the attributes of interest for each pixel of the Landsat image. Achieved results demonstrate the effectiveness of the k-NN approach for statistical estimation, that is compatible with the produced forest attribute raster maps and also proves to be characterized, in the considered study case, by a precision double than that obtained by conventional inventory based on field sample plots only.

  2. 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.

  3. Mapping forest height, foliage height profiles and disturbance characteristics with time series of gap-filled Landsat and ALI imagery

    Science.gov (United States)

    Helmer, E.; Ruzycki, T. S.; Wunderle, J. M.; Kwit, C.; Ewert, D. N.; Voggesser, S. M.; Brandeis, T. J.

    2011-12-01

    We mapped tropical dry forest height (RMSE = 0.9 m, R2 = 0.84, range 0.6-7 m) and foliage height profiles with a time series of gap-filled Landsat and Advanced Land Imager (ALI) imagery for the island of Eleuthera, The Bahamas. We also mapped disturbance type and age with decision tree classification of the image time series. Having mapped these variables in the context of studies of wintering habitat of an endangered Nearctic-Neotropical migrant bird, the Kirtland's Warbler (Dendroica kirtlandii), we then illustrated relationships between forest vertical structure, disturbance type and counts of forage species important to the Kirtland's Warbler. The ALI imagery and the Landsat time series were both critical to the result for forest height, which the strong relationship of forest height with disturbance type and age facilitated. Also unique to this study was that seven of the eight image time steps were cloud-gap-filled images: mosaics of the clear parts of several cloudy scenes, in which cloud gaps in a reference scene for each time step are filled with image data from alternate scenes. We created each cloud-cleared image, including a virtually seamless ALI image mosaic, with regression tree normalization of the image data that filled cloud gaps. We also illustrated how viewing time series imagery as red-green-blue composites of tasseled cap wetness (RGB wetness composites) aids reference data collection for classifying tropical forest disturbance type and age.

  4. Forest and land use mapping using Remote Sensing and Geographical Information System: A case study on model system

    Directory of Open Access Journals (Sweden)

    Prabhat Kumar Rai

    2013-09-01

    Full Text Available Remote sensing and geospatial technologies find tremendous application in rapid spatial and temporal monitoring as well as assessment of tropical forest resources and hence in formulation of concrete policy frameworks for their sustainable management. Present paper provides an overview on application of remote sensing in forestry and ecology with a case study which may be further extrapolated in other Indian Himalayan regions of North-East India. The case study used an IKONOS (2001 image, Arc View ver. 3.2, and ERDAS IMAGINE ver. 9.1 in order to investigate the forest/vegetation types/land cover mapping of Forest Research Institute campus (FRI, Dehradun, India (as model system through visual image interpretation. In the present case study, Chir pine was the dominant vegetation type covering major area of plantation inside FRI campus followed by Sal, Teak, Cassia, Cupressus and mixed vegetation with intermittent built up areas. Since FRI consists of huge plantations, separated in a segmented way, the site was feasible for learners of vegetation or forest mapping in an effective and systematic way. In nutshell, vegetation type/land use mapping through visual interpretation may be a valuable tool in monitoring, assessment and conservation planning of forests.

  5. 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

  6. Mapping Disturbance Dynamics in Wet Sclerophyll Forests Using Time Series Landsat

    Science.gov (United States)

    Haywood, A.; Verbesselt, J.; Baker, P. J.

    2016-06-01

    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. This study demonstrates the

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

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    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

  8. 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.

  9. Mapping of extreme wind speed for landscape modelling of the Bohemian Forest, Czech Republic

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    L. Pop

    2014-01-01

    Full Text Available Extreme wind events are among the most damaging weather-related hazards in the Czech Republic, forestry is heavily affected. In order to successfully run a landscape model dealing with such effects, spatial distribution of extreme wind speed statistics is needed. The presented method suggests using sector-wise wind field calculations together with extreme value statistics fitted at a reference station. A special algorithm is proposed to provide the data in the form expected by the landscape model, i.e. raster data of annual wind speed maxima. The method is demonstrated on the area of Bohemian Forest that represents one of largest and most compact forested mountains in Central Europe. The reference meteorological station Churáňov is located within the selected domain. Numerical calculations were based on linear model of WAsP Engineering methodology. Observations were cleaned of inhomogeneity and classified into convective and non-convective cases using index CAPE. Due to disjunct sampling of synoptic data, appropriate corrections were applied to the observed extremes. Finally they were fitted with Gumbel distribution. The output of numerical simulation is presented for the windiest direction sector. Another map shows probability that annual extreme exceeds required threshold. The method offers a tool for generation of spatially variable annual maxima of wind speed. It assumes a small limited model domain containing a reliable wind measurement. We believe that this is typical setup for applications similar to one presented in the paper.

  10. Mapping mangrove forests using multi-tidal remotely-sensed data and a decision-tree-based procedure

    Science.gov (United States)

    Zhang, Xuehong; Treitz, Paul M.; Chen, Dongmei; Quan, Chang; Shi, Lixin; Li, Xinhui

    2017-10-01

    Mangrove forests grow in intertidal zones in tropical and subtropical regions and have suffered a dramatic decline globally over the past few decades. Remote sensing data, collected at various spatial resolutions, provide an effective way to map the spatial distribution of mangrove forests over time. However, the spectral signatures of mangrove forests are significantly affected by tide levels. Therefore, mangrove forests may not be accurately mapped with remote sensing data collected during a single-tidal event, especially if not acquired at low tide. This research reports how a decision-tree -based procedure was developed to map mangrove forests using multi-tidal Landsat 5 Thematic Mapper (TM) data and a Digital Elevation Model (DEM). Three indices, including the Normalized Difference Moisture Index (NDMI), the Normalized Difference Vegetation Index (NDVI) and NDVIL·NDMIH (the multiplication of NDVIL by NDMIH, L: low tide level, H: high tide level) were used in this algorithm to differentiate mangrove forests from other land-cover and land-use types in Fangchenggang City, China. Additionally, the recent Landsat 8 OLI (Operational Land Imager) data were selected to validate the results and compare if the methodology is reliable. The results demonstrate that short-term multi-tidal remotely-sensed data better represent the unique nearshore coastal wetland habitats of mangrove forests than single-tidal data. Furthermore, multi-tidal remotely-sensed data has led to improved accuracies using two classification approaches: i.e. decision trees and the maximum likelihood classification (MLC). Since mangrove forests are typically found at low elevations, the inclusion of elevation data in the two classification procedures was tested. Given the decision-tree method does not assume strict data distribution parameters, it was able to optimize the application of multi-tidal and elevation data, resulting in higher classification accuracies of mangrove forests. When using multi

  11. A new computer tool "FastEmap" for mapping annual forest attributes from U.S. forest inventory at 30m resolution

    Science.gov (United States)

    Huang, S.; Ramirez, C.; Kennedy, K.; Mallory, J.

    2016-12-01

    Permanent field plots are surveyed by the USDA Forest Service Forest Inventory and Analysis (FIA) program to monitor the forest on a cyclical basis. Depending on the FIA region, a full re-measurement cycle ranges from 5-10 years. An algorithm has been developed to extrapolate field measurements to wall-to-wall data products at a moderate resolution ( 30 m) at annual steps. This temporal frequency is often a requirement for forest monitoring and temporal analysis. Based on this innovative algorithm, we have developed a tool called "Field And SatelliTe for Ecosystem MAPping (FastEmap)". The tool assimilates measured point-specific estimates of forest biophysical characteristics, Landsat images, and auxiliary datasets to map forest parameters at a 30-m pixel resolution. Seven major components are integrated into an automated production line: 1) automatically selecting field plots for a specific year with antecedent and subsequent years taken into account; 2) creating additional "virtual" field plots to intensify the density of field plots; 3) using stepwise regression to create a spatial prediction; 4) iteratively establishing groups that are comprised of similar pixels and imputing the group with the weighted mean (based on regression) of the plots that are within the group; 5) local interpolation and strata median filling for remaining pixels; 6) developing a temporal smoothing approach to solve the unrealistic elastic change; and 7) using the sequence of iteration as an indirect uncertainty indicator. Taking the complex Southern California area as an example, we used FastEmap to map aboveground live biomass (AGLB) from forest inventory plots. The accuracy evaluation revealed that an R2 of 0.78, a root-mean-square error (RMSE) of 28.3 tons/ha, and a mean absolute error (MAE) of 22.7 tons/ha could be achieved for this ecosystem. The FastEmap tool also successfully captured the temporal change in AGLB following fire disturbance. FastEmap may be applied to other

  12. Application of remote sensing and geographical information system in mapping forest fire risk zone at Bhadra wildlife sanctuary, India.

    Science.gov (United States)

    Sowmya, S V; Somashekar, R K

    2010-11-01

    Fire is the most spectacular natural disturbance that affects the forest ecosystem composition and diversity. Fire has a devastating effect on the landscape and its impact is felt at every level of the ecosystem and it is possible to map forest fire risk zone and thereby minimize the frequency of fire. There is a need for supranational approaches that analyze wide scenarios of factors involved and global fire effects. Fires can be monitored and analyzed over large areas in a timely and cost effective manner by using satellite imagery. Also Geographical Information System (GIS) can be used effectively to demarcate the fire risk zone map. Bhadra wildlife Sanctuary located in Kamataka, India was selected for this study. Vegetation, slope, distance from roads, settlements parameters were derived for a study area using topographic maps and field information. The Remote Sensing (RS) and Geographical Information System (GIS)-based forest fire risk model of the study area appeared to be highly compatible with the actual fire-affected sites. The temporal satellite data from 1989 to2006 have been analyzed to map the burnt areas. These classes were weighted according to their influence on forest fire. Four categories of fire risk regions such as Low, Moderate, High and Very high fire intensity zones were identified. It is predicted that around 10.31% of the area falls undermoderate risk zone.

  13. Enhancing hydrologic mapping using LIDAR and high resolution aerial photos on the Frances Marion National Forest in coastal South Carolina

    Science.gov (United States)

    Andy Maceyka; William F. Hansen

    2016-01-01

    Evaluating hydrology within coastal marine terrace features has always been problematic as watershed boundaries and stream detail are difficult to determine in low gradient terrain with dense bottomland forests. Various studies have improved hydrologic detail using USGS Topographic Contour Maps (Hansen 2001, Eidson and others 2005) or Light Detection and Ranging (LIDAR...

  14. Aerial detection of Ailanthus altissima: a cost-effective method to map an invasive tree in forested landscapes

    Science.gov (United States)

    Joanne Rebbeck; Aaron Kloss; Michael Bowden; Cheryl Coon; Todd F. Hutchinson; Louis Iverson; Greg Guess

    2015-01-01

    We present an aerial mapping method to efficiently and effectively identify seed clusters of the invasive tree, Ailanthus altissima (Mill.) Swingle across deciduous forest landscapes in the eastern United States. We found that the ideal time to conduct aerial digital surveys is early to middle winter, when Ailanthus seed...

  15. The Probation Period for Debutant Civil Servants. Influencing Expectancy

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    Leonina Emilia SUCIU

    2012-10-01

    Full Text Available This study is part of a broader research on work motivation in the Romanian local public administration, based on Vroom’s motivational model. The research has tried to diagnose Romanian local public institutions (city halls in particular regarding the work motivation level of their civil servants. Since the research was too broad to be presented entirely in this article, the authors will show only the findings obtained in one city hall from a city, county residence. Due to the same reason, this paper refers to just one of the Vroom’s model elements (the expectancy and to one of the aspects that could influence it: the probation period for the debutant civil servants. The probation period is critical in preparing civil servants for their future job and career within the local public administration. That is why it can influence the expectancy of civil servants, which in its turn, (from Vroom’s’ model perspective influences work motivation.

  16. SRTM-DEM AND LANDSAT ETM+ DATA FOR MAPPING TROPICAL DRY FOREST COVER AND BIODIVERSITY ASSESSMENT IN NICARAGUA

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    Brett G. Dickson

    2008-08-01

    Full Text Available 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 arrangement and extent of dryforest and other land cover types is greatly needed to enhance studies of forest fragmentation effects onanimal populations. To address this issue, we compared two Random Forest decision tree models forland cover classification in a Nicaraguan tropical dry forest landscape with and without the use of terrainvariables derived from Space Shuttle Radar and Topography Mission digital elevation data (SRTM-DEM.Landsat Enhanced Thematic Mapper (ETM+ bands and vegetation indices were the principle source ofspectral variables used. Overall classification accuracy for nine land cover types improved from 82.4% to87.4% once terrain and spectral predictor variables were combined. Error matrix comparisons showedthat class accuracy was significantly greater (z = 2.57, p-value < 0.05 with the inclusion of terrain variables(e.g., slope, elevation and topographic wetness index in decision tree models. Variable importance metricsindicated that a corrected Normalized Difference Vegetation Index (NDVIc and terrain variables improveddiscrimination of forest successional types and wetlands in the study area. Results from this study demonstratethe capability of terrain variables to enhance land cover classification and habitat mapping useful tobiodiversity assessment in tropical dry forest.

  17. 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

  18. 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

  19. Nonparametric 3D map of the IGM using the Lyman-alpha forest

    CERN Document Server

    Cisewski, Jessi; Freeman, Peter E; Genovese, Christopher R; Khandai, Nishikanta; Ozbek, Melih; Wasserman, Larry

    2014-01-01

    Visualizing the high-redshift Universe is difficult due to the dearth of available data; however, the Lyman-alpha forest provides a means to map the intergalactic medium at redshifts not accessible to large galaxy surveys. Large-scale structure surveys, such as the Baryon Oscillation Spectroscopic Survey (BOSS), have collected quasar (QSO) spectra that enable the reconstruction of HI density fluctuations. The data fall on a collection of lines defined by the lines-of-sight (LOS) of the QSO, and a major issue with producing a 3D reconstruction is determining how to model the regions between the LOS. We present a method that produces a 3D map of this relatively uncharted portion of the Universe by employing local polynomial smoothing, a nonparametric methodology. The performance of the method is analyzed on simulated data that mimics the varying number of LOS expected in real data, and then is applied to a sample region selected from BOSS. Evaluation of the reconstruction is assessed by considering various feat...

  20. Forest resources of the United States, 2002: mapping the renewable resource planning act data

    Science.gov (United States)

    Cassandra M. Kurtz; Daniel J. Kaisershot; Dale D. Gormanson; Jeffery S. Wazenegger

    2009-01-01

    Forest Inventory and Analysis (FIA), a national program of the Forest Service, U.S. Department of Agriculture conducts and maintains comprehensive inventories of the forest resources in the United States. The Forest and Rangeland Renewable Resources Planning Act (RPA) of 1974 mandates a comprehensive assessment of past trends, current status, and the future potential...

  1. The Utility of AISA Eagle Hyperspectral Data and Random Forest Classifier for Flower Mapping

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    Elfatih M. Abdel-Rahman

    2015-10-01

    Full Text Available Knowledge of the floral cycle and the spatial distribution and abundance of flowering plants is important for bee health studies to understand the relationship between landscape and bee hive productivity and honey flow. The key objective of this study was to show how AISA Eagle hyperspectral data and random forest (RF can be optimally utilized to produce flowering and spatially explicit land use/land cover (LULC maps for a study site in Kenya. AISA Eagle imagery was captured at the early flowering period (January 2014 and at the peak flowering season (February 2013. Data on white and yellow flowering trees as well as LULC classes in the study area were collected and used as ground-truth points. We utilized all 64 AISA Eagle bands and also used variable importance in RF to identify the most important bands in both AISA Eagle data sets. The results showed that flowering was most accurately mapped using the AISA Eagle data from the peak flowering period (85.71%–88.15% overall accuracy for the peak flowering season imagery versus 80.82%–83.67% for the early flowering season. The variable optimization (i.e., variable selection analysis showed that less than half of the AISA bands (n = 26 for the February 2013 data and n = 21 for the January 2014 data were important to attain relatively reliable classification accuracies. Our study is an important first step towards the development of operational flower mapping routines and for understanding the relationship between flowering and bees’ foraging behavior.

  2. MAPPING TROPICAL FOREST FOR SUSTAINABLE MANAGEMENT USING SPOT 5 SATELLITE IMAGE

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    H. T. T. Nguyen

    2016-06-01

    Full Text Available This paper describes the combination of multi-data in stratifying the natural evergreen broadleaved tropical forest of the Central Highlands of Vietnam. The forests were stratified using both unsupervised and supervised classification methods based on SPOT5 and field data. The forests were classified into 3 and 4 strata separably. Correlation between stratified forest classes and forest variables was analyzed in order to find out 1 how many classes is suitable to stratify for the forest in this area and 2 how closely the forest variables are related with forest classes. The correlation coefficient shows although all forest variables did have a significant correlation with the forest classes, stand volume appeared to have the strongest correlation with forest classes. These are 0.64 and 0.59 for four and three strata respectively. The results of supervised classification also show the four strata of heavily degraded forest, moderate disturbance, insignificant disturbance, and dense forest were discriminated more clearly comparing to the forest stratified into three classes. The proof is that overall accuracy of supervised classification was 86% with Kappa of 0.8 for four classes, meanwhile, these are 77% and 0.62 respectively for forest area classified into 3 classes.

  3. 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...

  4. First Results of the Performance of the Global Forest/Non-Forest Map derived from TanDEM-X Interferometric Data

    Science.gov (United States)

    Gonzalez, Carolina; Rizzoli, Paola; Martone, Michele; Wecklich, Christopher; Bueso Bello, Jose Luis; Krieger, Gerhard; Zink, Manfred

    2017-04-01

    The globally acquired interferometric synthetic aperture radar (SAR) data set, used for the recently completed primary goal of the TanDEM-X mission, enables a big opportunity for scientific geo-applications. Of great importance for land characterization, classification, and monitoring is that the data set is globally acquired without gaps and includes multiple acquisitions of every region, with comparable parameters. One of the most valuable maps that can be derived from interferometric SAR data for land classification describes the presence/absence of vegetation. In particular, here we report about the deployment of the Global Forest/Non-Forest Map, derived from TanDEM-X interferometric SAR quick-look data, at a ground resolution of 50 m by 50 m. Presence of structures and in particular vegetation produces multiple scattering known as volume decorrelation. Its contribution can be directly estimated from the assessment of coherence loss in the interferometric bistatic pair, by compensating for all other decorrelation sources, such as poor signal-to-noise ratio or quantization noise. Three different forest types have been characterized based on the estimated volume decorrelation: tropical, temperate, and boreal forest. This characterization was then used in a fuzzy clustering approach for the discrimination of vegetated areas on a global scale. Water and cities are filtered out from the generated maps in order to distinguish volume decorrelation from other decorrelation sources. The validation and performance comparison of the delivered product is also presented, and represents a fundamental tool for optimizing the whole algorithm at all different stages. Furtheremore, as the time interval of the acquisitions is almost 4 years, change detection can be performed as well and examples of deforestation are also going to be included in the final paper.

  5. 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.

  6. 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.

  7. 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

  8. Mapping tropical forests and deciduous rubber plantations in Hainan Island, China by integrating PALSAR 25-m and multi-temporal Landsat images

    Science.gov (United States)

    Chen, Bangqian; Li, Xiangping; Xiao, Xiangming; Zhao, Bin; Dong, Jinwei; Kou, Weili; Qin, Yuanwei; Yang, Chuan; Wu, Zhixiang; Sun, Rui; Lan, Guoyu; Xie, Guishui

    2016-08-01

    Updated and accurate maps of tropical forests and industrial plantations, like rubber plantations, are essential for understanding carbon cycle and optimal forest management practices, but existing optical-imagery-based efforts are greatly limited by frequent cloud cover. Here we explored the potential utility of integrating 25-m cloud-free Phased Array type L-band Synthetic Aperture Radar (PALSAR) mosaic product and multi-temporal Landsat images to map forests and rubber plantations in Hainan Island, China. Based on structure information detected by PALSAR and yearly maximum Normalized Difference Vegetation Index (NDVI), we first identified and mapped forests with a producer accuracy (PA) of 96% and user accuracy (UA) of 98%. The resultant forest map showed reasonable spatial and areal agreements with the optical-based forest maps of Fine Resolution Observation and Monitoring Global Land Clover (FROM-GLC) and GlobalLand30. We then extracted rubber plantations from the forest map according to their deciduous features (using minimum Land Surface Water Index, LSWI) and rapid changes in canopies during Rubber Defoliation and Foliation (RDF) period (using standard deviation of LSWI) and dense canopy in growing season (using maximum NDVI). The rubber plantation map yielded a high accuracy when validated by ground truth-based data (PA/UA > 86%) and evaluated with three farm-scale rubber plantation maps (PA/UA >88%). It is estimated that in 2010, Hainan Island had 2.11 × 106 ha of forest and 5.15 × 105 ha of rubber plantations. This study has demonstrated the potential of integrating 25-m PALSAR-based structure information, and Landsat-based spectral and phenology information for mapping tropical forests and rubber plantations.

  9. Integration of ALOS/PALSAR backscatter with a LiDAR-derived canopy height map to quantify forest fragmentation

    Science.gov (United States)

    Pinto, N.; Dubayah, R.; Simard, M.; Fatoyinbo, T. E.

    2011-12-01

    Habitat loss is the main predictor of species extinctions and must be characterized in high-biodiversity ecosystems where land cover change is pervasive. Forests' ability to support viable animal populations is typically modeled as a function of the presence of linkages or corridors, and quantified with fragmentation metrics. In this scenario, small forest patches and linear (e.g. riparian) zones can act as keystone structures. Fine-resolution, all-weather Synthetic Aperture Radar (SAR) data from ALOS/PALSAR is well-suited to resolve forest fragments in tropical sites. This study summarizes a technique for integrating fragmentation metrics from ALOS/PALSAR with vertical structure data from ICESat/GLAS to produce fine-resolution (30 m) forest habitat metrics that capture both local quality (canopy height) as well as spatial context and multi-scale connectivity. We illustrate our approach with backscatter images acquired over the Brazilian Atlantic Forest, a biodiversity hotspot. ALOS/PALSAR 1.1 images acquired over the dry season were calibrated to calculate gamma naught and map forest cover via tresholding. We employ network algorithms to locate dispersal bottlenecks between conservation units. The location of keystone structures is compared against a model that uses coarse (500m) percent tree cover as an input.

  10. Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.; Foster, James L.

    2009-01-01

    Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed

  11. Early Sexual Debut and Associated Factors among In-school Adolescents in Six Caribbean Countries

    Science.gov (United States)

    Peltzer, K; Pengpid, S

    2015-01-01

    ABSTRACT Objective: This report examines early sexual debut (< age 15 years) among 15-year old in-school adolescents in six Caribbean countries. Subjects and Methods: The total sample included 9948 school children aged primarily 13–16 years from nationally representative samples from six Caribbean countries. Univariate and multivariate analyses were conducted to assess the relationship between early sexual debut and substance use, unintentional injuries and violence, mental distress, physical activity, protective factors and socio-economic status variables. Results: Approximately one-fourth of the sample (26.9%) had experienced sexual debut before age 15 years, 37.2% among boys and 16.9% among girls. In multivariate logistic regression analysis, it was found that male gender, substance use (smoking and alcohol use), having been in a physical fight in the past 12 months, sedentary behaviour, truancy and lack of parental or guardian attachment were associated with early sexual debut. Conclusion: This study found a high prevalence of early sexual debut. The risk factors identified were consistent with the Problem Behaviour Theory, which can be incorporated into broader sexual health promotion programmes. PMID:26624586

  12. 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

  13. Regional forest and non-forest mapping using Envisat ASAR data%Envisat ASAR的区域森林-非森林制图

    Institute of Scientific and Technical Information of China (English)

    凌飞龙; 李增元; 陈尔学; 黄燕平; 田昕; SCHMULLIUS Christina; LEITERER Reik; REICHE Johannes; SANTORO Maurizio

    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 QEM and Land-sat TM image for geocoding in rugged terrain and smooth terrain areas, respectively. An object-oriented forest and non-forest classification method was then proposed based on the HH (horizontal transmit and horizontal receive) to HV (horizontal transmit and vertical receive) polarization intensity ratio and HV images of ASAR data at single acquisition time in winter. The developed method was applied to forest and non-forest mapping in Northeast China. The overall accuracy, the user's accuracy and the producer's accuracy of forest were 83.7%, 85.6% and 75.7%, respectively. These results indicate that the proposed method is promising for operational forest mapping at regional scale.%Envisat卫星ASAR传感器的双极化数据对区域森林监测十分有效.通过分别采用SRTM DEM和Landsat TM图像对地形起伏区域和平坦区域的SAR网像进行地理编码,发展了一种SAR图像自动预处理方法.基于冬季单时相ASAR数据的HH(水平发射,水平接收)、HV(水平发射,垂直接收)极化比值和HV极化图像,提出了一种面向对象的森林-非森林分类方法.将之应用于中国东北森林/非森林制图,分类总体精度、森林用户精度和生产者精度分别为83.7%,85.6%和75.7%.结果表明,本文提出的方法十分适合区域森林-非森林制图的业务化运行.

  14. 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.

  15. Spatio-Temporal Assessment and Mapping of the Landuse Landcover Dynamics in The Central Forest Belt of Southwestern Nigeria

    Directory of Open Access Journals (Sweden)

    R.O. Oyinloye

    2012-07-01

    Full Text Available The study examined the Landuse and Landcover (LULC dynamics of the central cocoa cultivation area of southwestern Nigeria between 1972 and 2002 using remotely sensed multi-temporal datasets. The datasets are Landsat 1972, 1986, 1991 and 2002 imageries. The datasets were each subjected to supervised classification techniques employing the maximum likelihood classifier using ILWIS software. This implies that field observation for identification and completion of ambiguous features and other details supported by GPS locations was carried out. Seven dominant classes of feature: agro-forest/light forest, built-up area, exposed rock surfaces/bare land, forest reserve, shrub and arable land, ridge forest and water body were identified. A time series analysis of the LULC changes was carried out to provide the necessary understanding of the changes required for policy formulation and decision-making with respect to cocoa production, forest reserve management and landuse planning, control, coordination and budgeting while being mindful of environmental conservation. This indispensable geo-information is yet lacking in the cocoa growing belt of southwestern Nigeria. ArcView software was used to prepare the corresponding time series LULC maps of the study area. The study showed that the forest reserves within the study area reduced at an average rate of 2.78% per year while agro-forest/light forest reduced to 46.39% (i.e., at an average rate of 1.55% per year and, shrub and arable land increased by 323.06% (i.e., at an average rate of 10.77% per year for food production farming to feed the rapidly increasing population between 1972 and 2002.

  16. 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.

  17. 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 are

  18. 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}.

  19. Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

    Science.gov (United States)

    Meng, Ran; Wu, Jin; Schwager, Kathy L.; Zhao, Feng; Dennison, Philip E.; Cook, Bruce D.; Brewster, Kristen; Green, Timothy M.; Serbin, Shawn P.

    2017-01-01

    As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and

  20. 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

  1. 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-...

  2. 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

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

    Science.gov (United States)

    Sangermano, Florencia; Bol, Leslie; Galvis, Pedro; Gullison, Raymond E; Hardner, Jared; Ross, Gail S.

    2015-01-01

    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 PMID:26217817

  4. 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

  5. Airborne and spaceborne radar images for geologic and environmental mapping in the Amazon rain forest, Brazil

    Science.gov (United States)

    Ford, John P.; Hurtak, James J.

    1986-01-01

    Spaceborne and airborne radar image of portions of the Middle and Upper Amazon basin in the state of Amazonas and the Territory of Roraima are compared for purposes of geological and environmental mapping. The contrasted illumination geometries and imaging parameters are related to terrain slope and surface roughness characteristics for corresponding areas that were covered by each of the radar imaging systems. Landforms range from deeply dissected mountain and plateau with relief up to 500 m in Roraima, revealing ancient layered rocks through folded residual mountains to deeply beveled pediplain in Amazonas. Geomorphic features provide distinct textural signatures that are characteristic of different rock associations. The principle drainages in the areas covered are the Rio Negro, Rio Branco, and the Rio Japura. Shadowing effects and low radar sensitivity to subtle linear fractures that are aligned parallel or nearly parallel to the direction of radar illumination illustrate the need to obtain multiple coverage with viewing directions about 90 degrees. Perception of standing water and alluvial forest in floodplains varies with incident angle and with season. Multitemporal data sets acquired over periods of years provide an ideal method of monitoring environmental changes.

  6. 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 (pclassifications using the RF algorithm. As for the object-based image analysis, there were also statistically significant differences (palgorithms. The object-based classification using RF provided a more visually adequate distribution of interested land cover types, while the object classifications based on the KNN algorithm showed noticeably commissions for forested wetlands 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.

  7. Stochastic gradient boosting classification trees for forest fuel types mapping through airborne laser scanning and IRS LISS-III imagery

    Science.gov (United States)

    Chirici, G.; Scotti, R.; Montaghi, A.; Barbati, A.; Cartisano, R.; Lopez, G.; Marchetti, M.; McRoberts, R. E.; Olsson, H.; Corona, P.

    2013-12-01

    This paper presents an application of Airborne Laser Scanning (ALS) data in conjunction with an IRS LISS-III image for mapping forest fuel types. For two study areas of 165 km2 and 487 km2 in Sicily (Italy), 16,761 plots of size 30-m × 30-m were distributed using a tessellation-based stratified sampling scheme. ALS metrics and spectral signatures from IRS extracted for each plot were used as predictors to classify forest fuel types observed and identified by photointerpretation and fieldwork. Following use of traditional parametric methods that produced unsatisfactory results, three non-parametric classification approaches were tested: (i) classification and regression tree (CART), (ii) the CART bagging method called Random Forests, and (iii) the CART bagging/boosting stochastic gradient boosting (SGB) approach. This contribution summarizes previous experiences using ALS data for estimating forest variables useful for fire management in general and for fuel type mapping, in particular. It summarizes characteristics of classification and regression trees, presents the pre-processing operation, the classification algorithms, and the achieved results. The results demonstrated superiority of the SGB method with overall accuracy of 84%. The most relevant ALS metric was canopy cover, defined as the percent of non-ground returns. Other relevant metrics included the spectral information from IRS and several other ALS metrics such as percentiles of the height distribution, the mean height of all returns, and the number of returns.

  8. Mapping tree health using airborne laser scans and hyperspectral imagery: a case study for a floodplain eucalypt forest

    Science.gov (United States)

    Shendryk, Iurii; Tulbure, Mirela; Broich, Mark; McGrath, Andrew; Alexandrov, Sergey; Keith, David

    2016-04-01

    Airborne laser scanning (ALS) and hyperspectral imaging (HSI) are two complementary remote sensing technologies that provide comprehensive structural and spectral characteristics of forests over large areas. In this study we developed two algorithms: one for individual tree delineation utilizing ALS and the other utilizing ALS and HSI to characterize health of delineated trees in a structurally complex floodplain eucalypt forest. We conducted experiments in the largest eucalypt, river red gum forest in the world, located in the south-east of Australia that experienced severe dieback over the past six decades. For detection of individual trees from ALS we developed a novel bottom-up approach based on Euclidean distance clustering to detect tree trunks and random walks segmentation to further delineate tree crowns. Overall, our algorithm was able to detect 67% of tree trunks with diameter larger than 13 cm. We assessed the accuracy of tree delineations in terms of crown height and width, with correct delineation of 68% of tree crowns. The increase in ALS point density from ~12 to ~24 points/m2 resulted in tree trunk detection and crown delineation increase of 11% and 13%, respectively. Trees with incorrectly delineated crowns were generally attributed to areas with high tree density along water courses. The accurate delineation of trees allowed us to classify the health of this forest using machine learning and field-measured tree crown dieback and transparency ratios, which were good predictors of tree health in this forest. ALS and HSI derived indices were used as predictor variables to train and test object-oriented random forest classifier. Returned pulse width, intensity and density related ALS indices were the most important predictors in the tree health classifications. At the forest level in terms of tree crown dieback, 77% of trees were classified as healthy, 14% as declining and 9% as dying or dead with 81% mapping accuracy. Similarly, in terms of tree

  9. Mapping Clearances in Tropical Dry Forests Using Breakpoints, Trend, and Seasonal Components from MODIS Time Series: Does Forest Type Matter?

    NARCIS (Netherlands)

    Grogan, Kenneth; Pflugmacher, Dirk; Hostert, Patrick; Verbesselt, Jan; Fensholt, Rasmus

    2016-01-01

    Tropical environments present a unique challenge for optical time series analysis, primarily owing to fragmented data availability, persistent cloud cover and atmospheric aerosols. Additionally, little is known of whether the performance of time series change detection is affected by diverse forest

  10. 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

  11. Mapping the montane cloud forest of Taiwan using 12 year MODIS-derived ground fog frequency data.

    Science.gov (United States)

    Schulz, Hans Martin; Li, Ching-Feng; Thies, Boris; Chang, Shih-Chieh; Bendix, Jörg

    2017-01-01

    Up until now montane cloud forest (MCF) in Taiwan has only been mapped for selected areas of vegetation plots. This paper presents the first comprehensive map of MCF distribution for the entire island. For its creation, a Random Forest model was trained with vegetation plots from the National Vegetation Database of Taiwan that were classified as "MCF" or "non-MCF". This model predicted the distribution of MCF from a raster data set of parameters derived from a digital elevation model (DEM), Landsat channels and texture measures derived from them as well as ground fog frequency data derived from the Moderate Resolution Imaging Spectroradiometer. While the DEM parameters and Landsat data predicted much of the cloud forest's location, local deviations in the altitudinal distribution of MCF linked to the monsoonal influence as well as the Massenerhebung effect (causing MCF in atypically low altitudes) were only captured once fog frequency data was included. Therefore, our study suggests that ground fog data are most useful for accurately mapping MCF.

  12. Gender differences in exposure to SRH information and risky sexual debut among poor Myanmar youths.

    Science.gov (United States)

    Thin Zaw, Phyu Phyu; Liabsuetrakul, Tippawan; McNeil, Edward; Htay, Thien Thien

    2013-12-05

    Globally, the proportion of youths has been steadily increasing, especially in Asia. This vulnerable population has limited exposure to sexual and reproductive health (SRH) information leading to various reproductive health (RH) problems including risky sexual debut, unwanted pregnancy, unsafe abortion as well as STI/HIV infections. Among known social variations which influence youth's RH, gender differences are critical for planning necessary gender appropriate interventions. This study aimed to identify gender differences in exposure to SRH information and risky sexual debut as well as associated factors among Myanmar youths in poor suburban communities of Mandalay City. A total of 444 randomly selected youths (aged 15-24 years) from all poor, suburban communities in Mandalay City took part in our survey. Gender differences in exposure to SRH information and risky sexual debut were assessed by bivariate analysis. Multivariate logistic regression was used to confirm gender differences and identify independent factors associated with main outcomes separately for males and females as well as for both. Of 444 youths interviewed, 215 were males and 229 were females. Gender differences were seen in both exposures to SRH information (p = 0.013) and risky sexual debut (p = 0.003). These gender differences were confirmed by multivariate analysis even after adjusting for other risk factors. For exposure to SRH information, only age group and schooling status were significant factors for females. As well as those two factors, media exposure and parental guardianship were significant factors among males. Only positive norm of premarital sex increased the likelihood of risky sexual debut among males. In contrast, unwillingness at sexual debut was a risk factor and a higher education level was a protective factor for risky sexual debut among females. Limited exposure to SRH information and high risky sexual debut among poor youths were found. There were different influential

  13. 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.

  14. 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.

  15. Quantifying soil and critical zone variability in a forested catchment through digital soil mapping

    Science.gov (United States)

    Holleran, M.; Levi, M.; Rasmussen, C.

    2015-01-01

    Quantifying catchment-scale soil property variation yields insights into critical zone evolution and function. The objective of this study was to quantify and predict the spatial distribution of soil properties within a high-elevation forested catchment in southern Arizona, USA, using a combined set of digital soil mapping (DSM) and sampling design techniques to quantify catchment-scale soil spatial variability that would inform interpretation of soil-forming processes. The study focused on a 6 ha catchment on granitic parent materials under mixed-conifer forest, with a mean elevation of 2400 m a.s.l, mean annual temperature of 10 °C, and mean annual precipitation of ~ 85 cm yr-1. The sample design was developed using a unique combination of iterative principal component analysis (iPCA) of environmental covariates derived from remotely sensed imagery and topography, and a conditioned Latin hypercube sampling (cLHS) scheme. Samples were collected by genetic horizon from 24 soil profiles excavated to the depth of refusal and characterized for soil mineral assemblage, geochemical composition, and general soil physical and chemical properties. Soil properties were extrapolated across the entire catchment using a combination of least-squares linear regression between soil properties and selected environmental covariates, and spatial interpolation or regression residual using inverse distance weighting (IDW). Model results indicated that convergent portions of the landscape contained deeper soils, higher clay and carbon content, and greater Na mass loss relative to adjacent slopes and divergent ridgelines. The results of this study indicated that (i) the coupled application of iPCA and cLHS produced a sampling scheme that captured the greater part of catchment-scale soil variability; (ii) application of relatively simple regression models and IDW interpolation of residuals described well the variance in measured soil properties and predicted spatial correlation of soil

  16. Use of Bedrock and Geomorphic Mapping Compilations in Assessing Geologic Hazards at Recreation Sites on National Forests in NW California

    Science.gov (United States)

    de La Fuente, J. A.; Bell, A.; Elder, D.; Mowery, R.; Mikulovsky, R.; Klingel, H.; Stevens, M.

    2010-12-01

    Geologic hazards on US Forest Service lands have a long history of producing catastrophic events. In 1890 (prior to the establishment of the Forest Service), the China Mine landslide buried a miner’s camp along the Trinity River in NW California, killing a number of miners. An earthquake in southwestern Montana triggered a massive landslide which killed 28 people in a US Forest Service campground in 1959. In 1980, Mount St. Helens erupted in Oregon, killing 57 people. Debris flows from a winter storm in 2003 on the burned hillslopes of the San Bernardino National Forest in California killed 14 people at the St. Sophia youth Camp. A rockfall in the summer of 2009 in Lassen National Park killed a 9 year old boy. The most recent catastrophe occurred on June 11, 2010 when 20 people died in a flash flood at the Albert Pike Campground on the Ouachita National Forest. These and other disasters point out the need for geologic hazard mapping and assessments on the National Forests. The US Forest Service (USFS) is currently assessing geologic hazards in the Northern Province of USFS Region 5 (Pacific Southwest Region), which includes the Klamath, Mendocino, Shasta-Trinity, and Six Rivers National Forests. The most common geologic hazards (relatively short return intervals) in this area include landslides, rock falls, debris flows, flooding, temporary dam failures (landslide or woody debris), naturally occurring hazardous materials, (asbestos radon, etc), and rarely, karst subsidence. Seismic and volcanic hazards are also important at longer return intervals. This assessment will be conducted in three phases, and is patterned after a process developed by Region 8 of the US Forest Service. The first phase is a reconnaissance level assessment based on existing information such as spatial databases, aerial photos, Digital Elevation Models, State of California Alquist-Priolo Earthquake Fault Zone maps, previous investigations and anecdotal accounts of past events. The bedrock

  17. FS National Forest Dataset (US Forest Service Proclaimed Forests)

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting the boundaries encompassing the National Forest System (NFS) lands within the original proclaimed National Forests, along with...

  18. 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.

  19. Mapping post-disturbance stand age distribution in Siberian larch forest based on a novel method

    Science.gov (United States)

    Chen, D.; Loboda, T. V.; Krylov, A.; Potapov, P.

    2014-12-01

    The Siberian larch forest, which accounts for nearly 20% of the global boreal forest biome, is unique, important, yet significantly understudied. These deciduous needleleaf forests with a single species dominance over a large continuous area are not found anywhere except the extreme continental zones of Siberia and the Russian Far East. Most of these forests are located in remote and sparsely populated areas and, therefore, little is known about spatial variability of their structure and dynamics. Wall-to-wall repeated observations of this area are available only since the 2000s. Previously, we developed methods for reconstruction of stand-age distribution from a sample of 1980-2000 disturbances in Landsat TM and ETM+ imagery. However, availability of those images in Siberian larch forests is particularly limited. Built upon the hypothesis that the spectral characteristics of the disturbed forest in the region change with time consistently, this paper proposes a novel method utilizing the newly released Global Forest Change (GFC) 2000-2012 dataset. We exploit the data-rich era of annual forest disturbance samples identified between 2000 and 2012 in the Siberian larch forest by the GFC dataset to build a robust training set of spectral signatures from regrowing larch forests as they appear in Landsat imagery in 2012. The extracted statistics are ingested into a random forest, which predicts the approximate stand age for every forested pixel in the circa 2000 composite. After merging the estimated stand age distribution for 1989-2000 with the observed disturbance records for 2001-2012, a gap-free 30 m resolution 24-year long record of stand age distribution is obtained. A preliminary accuracy assessment against the Advanced Very High Resolution Radiometer (AVHRR) burned area product suggested satisfactory performance of the proposed method.

  20. 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

  1. Mapping tropical dry forest succession using multiple criteria spectral mixture analysis

    Science.gov (United States)

    Cao, Sen; Yu, Qiuyan; Sanchez-Azofeifa, Arturo; Feng, Jilu; Rivard, Benoit; Gu, Zhujun

    2015-11-01

    Tropical dry forests (TDFs) in the Americas are considered the first frontier of economic development with less than 1% of their total original coverage under protection. Accordingly, accurate estimates of their spatial extent, fragmentation, and degree of regeneration are critical in evaluating the success of current conservation policies. This study focused on a well-protected secondary TDF in Santa Rosa National Park (SRNP) Environmental Monitoring Super Site, Guanacaste, Costa Rica. We used spectral signature analysis of TDF ecosystem succession (early, intermediate, and late successional stages), and its intrinsic variability, to propose a new multiple criteria spectral mixture analysis (MCSMA) method on the shortwave infrared (SWIR) of HyMap image. Unlike most existing iterative mixture analysis (IMA) techniques, MCSMA tries to extract and make use of representative endmembers with spectral and spatial information. MCSMA then considers three criteria that influence the comparative importance of different endmember combinations (endmember models): root mean square error (RMSE); spatial distance (SD); and fraction consistency (FC), to create an evaluation framework to select a best-fit model. The spectral analysis demonstrated that TDFs have a high spectral variability as a result of biomass variability. By adopting two search strategies, the unmixing results showed that our new MCSMA approach had a better performance in root mean square error (early: 0.160/0.159; intermediate: 0.322/0.321; and late: 0.239/0.235); mean absolute error (early: 0.132/0.128; intermediate: 0.254/0.251; and late: 0.191/0.188); and systematic error (early: 0.045/0.055; intermediate: -0.211/-0.214; and late: 0.161/0.160), compared to the multiple endmember spectral mixture analysis (MESMA). This study highlights the importance of SWIR in differentiating successional stages in TDFs. The proposed MCSMA provides a more flexible and generalized means for the best-fit model determination

  2. Decision forests for learning prostate cancer probability maps from multiparametric MRI

    Science.gov (United States)

    Ehrenberg, Henry R.; Cornfeld, Daniel; Nawaf, Cayce B.; Sprenkle, Preston C.; Duncan, James S.

    2016-03-01

    Objectives: Advances in multiparametric magnetic resonance imaging (mpMRI) and ultrasound/MRI fusion imaging offer a powerful alternative to the typical undirected approach to diagnosing prostate cancer. However, these methods require the time and expertise needed to interpret mpMRI image scenes. In this paper, a machine learning framework for automatically detecting and localizing cancerous lesions within the prostate is developed and evaluated. Methods: Two studies were performed to gather MRI and pathology data. The 12 patients in the first study underwent an MRI session to obtain structural, diffusion-weighted, and dynamic contrast enhanced image vol- umes of the prostate, and regions suspected of being cancerous from the MRI data were manually contoured by radiologists. Whole-mount slices of the prostate were obtained for the patients in the second study, in addition to structural and diffusion-weighted MRI data, for pathology verification. A 3-D feature set for voxel-wise appear- ance description combining intensity data, textural operators, and zonal approximations was generated. Voxels in a test set were classified as normal or cancer using a decision forest-based model initialized using Gaussian discriminant analysis. A leave-one-patient-out cross-validation scheme was used to assess the predictions against the expert manual segmentations confirmed as cancer by biopsy. Results: We achieved an area under the average receiver-operator characteristic curve of 0.923 for the first study, and visual assessment of the probability maps showed 21 out of 22 tumors were identified while a high level of specificity was maintained. In addition to evaluating the model against related approaches, the effects of the individual MRI parameter types were explored, and pathological verification using whole-mount slices from the second study was performed. Conclusions: The results of this paper show that the combination of mpMRI and machine learning is a powerful tool for

  3. 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

  4. Mapping physical properties of Swiss forest soils by robust external-drift kriging from legacy soil data

    Science.gov (United States)

    Papritz, Andreas; Ramirez Lopez, Leo; Baltensweiler, Andri; Walthert, Lorenz

    2015-04-01

    Climate change scenario predict for Switzerland increasing summer temperature and decreasing precipitation. In coming decades forests will therefore likely experience more often drought. However, it is not clear to what extent these changes will occur and where in Switzerland they will be most pronounced. Soil-Vegetation-Atmosphere-Transfer (SVAT) models allow to explore likely changes in the water regime of forest under changing climate. Such process models require information of soil physical properties that largely control water storage in forest soils. Spatial information on physical properties of forest soils is currently lacking in Switzerland. Therefore one objective of the project "Soils and water regime of Swiss forests and forest sites under present and future climate BOWA-CH" (http://www.wsl.ch/fe/boden/projekte/bowa_ch/index_EN) was to predict basic physical properties of forest soils at high spatial resolution for the whole Swiss territory. Based on legacy data of about 2000 forest soil profiles, we mapped particle size composition, volumetric content of rock fragments, soil organic carbon (SOC) content and soil density for fixed-depth soil layers (0-10, 10-30, 30-60, ..., 120-150 cm) by robust external drift kriging (Nussbaum et al., 2014). Comprehensive, digitally available information on climate, topography, vegetation and geology were used as covariates for statistical modelling. Preliminary sets of covariates were chosen by LASSO, and the selection was refined by cross-validating the model for the external drift. External validation with 20 % of the data revealed that clay and sand content, soil density and SOC could be predicted with acceptable precision. Predictions of rock fragment content and silt content were less precise, and the developed model failed to spatially predict soil depth. This is unfortunate because soil depth and rock fragment content largely control water storage in soils. Nussbaum, M., Papritz, A., Baltensweiler, A

  5. Social Environment and Problem Behavior: Perceived School Safety, Gender, and Sexual Debut

    Science.gov (United States)

    March, Alice L.; Atav, A. Serdar

    2010-01-01

    In 2007, 48% of U.S. students of grades 9 to 12 had experienced sexual debut, 7% before the age of 13 years. Preventing early intercourse, sexually transmitted diseases, adolescent pregnancy, and the loss of educational opportunity are important concerns for nurses and educators. A secondary data analysis of the Youth Risk Behavior Survey (YRBS)…

  6. The Voice of Design--China young designers make debut in Keqiao

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    From November 26th to 27th, 2012, in Keqiao Town of Shaoxing County in Zhejiang Province, China Young Designers Creative Fashion Show, organized by China Fashion Alliance, made its debut of the original design, unveiling the latest textile and apparel fashion trend significantly.

  7. 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.

  8. US Forest Service National Forest System Roads

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting existing National Forest System Roads (NFSR) that are under the jurisdiction of the U.S. Forest Service. Each feature represents a...

  9. 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...

  10. 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...

  11. Mapping the montane cloud forest of Taiwan using 12 year MODIS-derived ground fog frequency data

    Science.gov (United States)

    Li, Ching-Feng; Thies, Boris; Chang, Shih-Chieh; Bendix, Jörg

    2017-01-01

    Up until now montane cloud forest (MCF) in Taiwan has only been mapped for selected areas of vegetation plots. This paper presents the first comprehensive map of MCF distribution for the entire island. For its creation, a Random Forest model was trained with vegetation plots from the National Vegetation Database of Taiwan that were classified as “MCF” or “non-MCF”. This model predicted the distribution of MCF from a raster data set of parameters derived from a digital elevation model (DEM), Landsat channels and texture measures derived from them as well as ground fog frequency data derived from the Moderate Resolution Imaging Spectroradiometer. While the DEM parameters and Landsat data predicted much of the cloud forest’s location, local deviations in the altitudinal distribution of MCF linked to the monsoonal influence as well as the Massenerhebung effect (causing MCF in atypically low altitudes) were only captured once fog frequency data was included. Therefore, our study suggests that ground fog data are most useful for accurately mapping MCF. PMID:28245279

  12. ­­Estimating Forest Management Units from Road Network Maps in the Southeastern U.S.

    Science.gov (United States)

    Yang, D.; Hall, J.; Fu, C. S.; Binford, M. W.

    2015-12-01

    The most important factor affecting forest structure and function is the type of management undertaken in forest stands. Owners manage forests using appropriately sized areas to meet management objectives, which include economic return, sustainability, recreation, or esthetic enjoyment. Thus, the socio-environmental unit of study for forests should be the management unit. To study the ecological effects of different kinds of management activities, we must identify individual management units. Road networks, which provide access for human activities, are widely used in managing forests in the southeastern U.S. Coastal Plain and Piedmont (SEUS). Our research question in this study is: How can we identify individual forest management units in an entire region? To answer it, we hypothesize that the road network defines management units on the landscape. Road-caused canopy openings are not always captured by satellite sensors, so it is difficult to delineate ecologically relevant patches based only on remote sensing data. We used a reliable, accurate and freely available road network data, OpenStreetMap (OSM), and the National Land Cover Database (NLCD) to delineate management units in a section of the SEUS defined by Landsat Wprldwide Reference System (WRS) II footprint path 17 row 39. The spatial frequency distributions of forest management units indicate that while units Management units ≥ 0.5 Ha ranged from 0.5 to 160,770 Ha (the Okefenokee National Wildlife Refuge). We compared the size-frequency distributions of management units with four independently derived management types: production, ecological, preservation, and passive management. Preservation and production management had the largest units, at 40.5 ± 2196.7 (s.d.) and 41.3 ± 273.5 Ha, respectively. Ecological and passive averaged about half as large at 19.2 ± 91.5 and 22.4 ± 96.0 Ha, respectively. This result supports the hypothesis that the road network defines management units in SEUS. If this way

  13. 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.

  14. Agricultural cropland mapping using black-and-white aerial photography, Object-Based Image Analysis and Random Forests

    Science.gov (United States)

    Vogels, M. F. A.; de Jong, S. M.; Sterk, G.; Addink, E. A.

    2017-02-01

    Land-use and land-cover (LULC) conversions have an important impact on land degradation, erosion and water availability. Information on historical land cover (change) is crucial for studying and modelling land- and ecosystem degradation. During the past decades major LULC conversions occurred in Africa, Southeast Asia and South America as a consequence of a growing population and economy. Most distinct is the conversion of natural vegetation into cropland. Historical LULC information can be derived from satellite imagery, but these only date back until approximately 1972. Before the emergence of satellite imagery, landscapes were monitored by black-and-white (B&W) aerial photography. This photography is often visually interpreted, which is a very time-consuming approach. This study presents an innovative, semi-automated method to map cropland acreage from B&W photography. Cropland acreage was mapped on two study sites in Ethiopia and in The Netherlands. For this purpose we used Geographic Object-Based Image Analysis (GEOBIA) and a Random Forest classification on a set of variables comprising texture, shape, slope, neighbour and spectral information. Overall mapping accuracies attained are 90% and 96% for the two study areas respectively. This mapping method increases the timeline at which historical cropland expansion can be mapped purely from brightness information in B&W photography up to the 1930s, which is beneficial for regions where historical land-use statistics are mostly absent.

  15. Mapping sub-antarctic cushion plants using random forests to combine very high resolution satellite imagery and terrain modelling.

    Directory of Open Access Journals (Sweden)

    Phillippa K Bricher

    Full Text Available 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.

  16. Using a detailed uncertainty analysis to adjust mapped rates of forest disturbance derived from Landsat time series data (Invited)

    Science.gov (United States)

    Cohen, W. B.; Yang, Z.; Stehman, S.; Huang, C.; Healey, S. P.

    2013-12-01

    Forest ecosystem process models require spatially and temporally detailed disturbance data to accurately predict fluxes of carbon or changes in biodiversity over time. A variety of new mapping algorithms using dense Landsat time series show great promise for providing disturbance characterizations at an annual time step. These algorithms provide unprecedented detail with respect to timing, magnitude, and duration of individual disturbance events, and causal agent. But all maps have error and disturbance maps in particular can have significant omission error because many disturbances are relatively subtle. Because disturbance, although ubiquitous, can be a relatively rare event spatially in any given year, omission errors can have a great impact on mapped rates. Using a high quality reference disturbance dataset, it is possible to not only characterize map errors but also to adjust mapped disturbance rates to provide unbiased rate estimates with confidence intervals. We present results from a national-level disturbance mapping project (the North American Forest Dynamics project) based on the Vegetation Change Tracker (VCT) with annual Landsat time series and uncertainty analyses that consist of three basic components: response design, statistical design, and analyses. The response design describes the reference data collection, in terms of the tool used (TimeSync), a formal description of interpretations, and the approach for data collection. The statistical design defines the selection of plot samples to be interpreted, whether stratification is used, and the sample size. Analyses involve derivation of standard agreement matrices between the map and the reference data, and use of inclusion probabilities and post-stratification to adjust mapped disturbance rates. Because for NAFD we use annual time series, both mapped and adjusted rates are provided at an annual time step from ~1985-present. Preliminary evaluations indicate that VCT captures most of the higher

  17. Aerial Orthophotography, Interpretation and Forest Type Mapping on Great Dismal Swamp NWR.

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — Sewall forest typing services for the Northern portion of Great Dismal Swamp NWR in northeastern North Carolina. This includes complete new aerial photography and...

  18. Accuracy Assessment Points for Petrified Forest National Park Vegetation Mapping Project

    Data.gov (United States)

    National Park Service, Department of the Interior — The Petrified Forest National Park Accuracy Assessment Observation Location zip shapefile (pefoaa.zip) was developed as a Geographic Information Systems (GIS)...

  19. Color Infrared Aerial Photographs for Petrified Forest National Park Vegetation Mapping Project

    Data.gov (United States)

    National Park Service, Department of the Interior — Color infrared (CIR) aerial photographs were acquired as baseline imagery data to produce vegetation spatial database coverages of Petrified Forest National Park...

  20. 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

  1. Mapping tropical forest biomass with radar and spaceborne LiDAR: overcoming problems of high biomass and persistent cloud

    Directory of Open Access Journals (Sweden)

    E. T. A. Mitchard

    2011-08-01

    Full Text Available Spatially-explicit maps of aboveground biomass are essential for calculating the losses and gains in forest carbon at a regional to national level. The production of such maps across wide areas will become increasingly necessary as international efforts to protect primary forests, such as the REDD+ (Reducing Emissions from Deforestation and forest Degradation mechanism, come into effect, alongside their use for management and research more generally. However, mapping biomass over high-biomass tropical forest is challenging as (1 direct regressions with optical and radar data saturate, (2 much of the tropics is persistently cloud-covered, reducing the availability of optical data, (3 many regions include steep topography, making the use of radar data complex, (4 while LiDAR data does not suffer from saturation, expensive aircraft-derived data are necessary for complete coverage.

    We present a solution to the problems, using a combination of terrain-corrected L-band radar data (ALOS PALSAR, spaceborne LiDAR data (ICESat GLAS and ground-based data. We map Gabon's Lopé National Park (5000 km2 because it includes a range of vegetation types from savanna to closed-canopy tropical forest, is topographically complex, has no recent cloud-free high-resolution optical data, and the dense forest is above the saturation point for radar. Our 100 m resolution biomass map is derived from fusing spaceborne LiDAR (7142 ICESat GLAS footprints, 96 ground-based plots (average size 0.8 ha and an unsupervised classification of terrain-corrected ALOS PALSAR radar data, from which we derive the aboveground biomass stocks of the park to be 78 Tg C (173 Mg C ha−1. This value is consistent with our field data average of 181 Mg C ha−1, from the field plots measured in 2009 covering a total of 78 ha, and which are independent as they were not used for the GLAS-biomass estimation. We estimate an uncertainty of ± 25 % on our

  2. Generating an optimal DTM from airborne laser scanning data for landslide mapping in a tropical forest environment

    Science.gov (United States)

    Razak, Khamarrul Azahari; Santangelo, Michele; Van Westen, Cees J.; Straatsma, Menno W.; de Jong, Steven M.

    2013-05-01

    Landslide inventory maps are fundamental for assessing landslide susceptibility, hazard, and risk. In tropical mountainous environments, mapping landslides is difficult as rapid and dense vegetation growth obscures landslides soon after their occurrence. Airborne laser scanning (ALS) data have been used to construct the digital terrain model (DTM) under dense vegetation, but its reliability for landslide recognition in the tropics remains surprisingly unknown. This study evaluates the suitability of ALS for generating an optimal DTM for mapping landslides in the Cameron Highlands, Malaysia. For the bare-earth extraction, we used hierarchical robust filtering algorithm and a parameterization with three sequential filtering steps. After each filtering step, four interpolations techniques were applied, namely: (i) the linear prediction derived from the SCOP++ (SCP), (ii) the inverse distance weighting (IDW), (iii) the natural neighbor (NEN) and (iv) the topo-to-raster (T2R). We assessed the quality of 12 DTMs in two ways: (1) with respect to 448 field-measured terrain heights and (2) based on the interpretability of landslides. The lowest root-mean-square error (RMSE) was 0.89 m across the landscape using three filtering steps and linear prediction as interpolation method. However, we found that a less stringent DTM filtering unveiled more diagnostic micro-morphological features, but also retained some of vegetation. Hence, a combination of filtering steps is required for optimal landslide interpretation, especially in forested mountainous areas. IDW was favored as the interpolation technique because it combined computational times more reasonably without adding artifacts to the DTM than T2R and NEN, which performed relatively well in the first and second filtering steps, respectively. The laser point density and the resulting ground point density after filtering are key parameters for producing a DTM applicable to landslide identification. The results showed that the

  3. Mapping Land Cover and Land Use Changes in the Congo Basin Forests with Optical Satellite Remote Sensing: a Pilot Project Exploring Methodologies that Improve Spatial Resolution and Map Accuracy

    Science.gov (United States)

    Molinario, G.; Baraldi, A.; Altstatt, A. L.; Nackoney, J.

    2011-12-01

    The University of Maryland has been a USAID Central Africa Rregional Program for the Environment (CARPE) cross-cutting partner for many years, providing remote sensing derived information on forest cover and forest cover changes in support of CARPE's objectives of diminishing forest degradation, loss and biodiversity loss as a result of poor or inexistent land use planning strategies. Together with South Dakota State University, Congo Basin-wide maps have been provided that map forest cover loss at a maximum of 60m resolution, using Landsat imagery and higher resolution imagery for algorithm training and validation. However, to better meet the needs within the CARPE Landscapes, which call for higher resolution, more accurate land cover change maps, UMD has been exploring the use of the SIAM automatic spectral -rule classifier together with pan-sharpened Landsat data (15m resolution) and Very High Resolution imagery from various sources. The pilot project is being developed in collaboration with the African Wildlife Foundation in the Maringa Lopori Wamba CARPE Landscape. If successful in the future this methodology will make the creation of high resolution change maps faster and easier, making it accessible to other entities in the Congo Basin that need accurate land cover and land use change maps in order, for example, to create sustainable land use plans, conserve biodiversity and resources and prepare Reducing Emissions from forest Degradation and Deforestation (REDD) Measurement, Reporting and Verification (MRV) projects. The paper describes the need for higher resolution land cover change maps that focus on forest change dynamics such as the cycling between primary forests, secondary forest, agriculture and other expanding and intensifying land uses in the Maringa Lopori Wamba CARPE Landscape in the Equateur Province of the Democratic Republic of Congo. The Methodology uses the SIAM remote sensing imagery automatic spectral rule classifier, together with pan

  4. Use of TMS/TM data for mapping of forest decline damage in the northeastern United States. [Thematic Mapper Simulator (TMS) Thematic Mapper (TM)

    Science.gov (United States)

    Rock, B. N.; Vogelmann, J. E.

    1986-01-01

    Remote sensing systems were used to monitor forest decline damage suspected of being due to air pollution. Field activities and aircraft overflights were centered on montane spruce/fir forest sites. Using aircraft data acquired with the Thematic Mapper Simulator (TMS) and LANDSAT Thematic Mapper (TM) during the growing season, extensive areas of forest decline damage were accurately mapped. Seven levels of decline damage are discrininated and mapped and the levels of discriminated damage agree well (rsq-0.94) with visual assessment conducted on the ground. New areas of high damage were discovered. A band ratio (TM5/TM4) is most useful in discriminating and quantifying the various levels of forest decline damage.

  5. 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.

  6. Comparison between WorldView-2 and SPOT-5 images in mapping the bracken fern using the random forest algorithm

    Science.gov (United States)

    Odindi, John; Adam, Elhadi; Ngubane, Zinhle; Mutanga, Onisimo; Slotow, Rob

    2014-01-01

    Plant species invasion is known to be a major threat to socioeconomic and ecological systems. Due to high cost and limited extents of urban green spaces, high mapping accuracy is necessary to optimize the management of such spaces. We compare the performance of the new-generation WorldView-2 (WV-2) and SPOT-5 images in mapping the bracken fern [Pteridium aquilinum (L) kuhn] in a conserved urban landscape. Using the random forest algorithm, grid-search approaches based on out-of-bag estimate error were used to determine the optimal ntree and mtry combinations. The variable importance and backward feature elimination techniques were further used to determine the influence of the image bands on mapping accuracy. Additionally, the value of the commonly used vegetation indices in enhancing the classification accuracy was tested on the better performing image data. Results show that the performance of the new WV-2 bands was better than that of the traditional bands. Overall classification accuracies of 84.72 and 72.22% were achieved for the WV-2 and SPOT images, respectively. Use of selected indices from the WV-2 bands increased the overall classification accuracy to 91.67%. The findings in this study show the suitability of the new generation in mapping the bracken fern within the often vulnerable urban natural vegetation cover types.

  7. 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

  8. Boreal Forest Land Cover Mapping in Iceland and Finland Using Sentinel-1A

    Science.gov (United States)

    Haarpaintner, J.; Davids, C.; Storvold, R.; Johansen, K. S.; Arnason, K.; Rauste, Y.; Mutanen, T.

    2016-08-01

    The complete Sentinel-1A (S1A) data set since autumn 2014 until September 2015 over two test sites of the EU FP7 project NorthState has been collected: Hallormsstaður in the north-east of Iceland of 50x50 km2 and Hyytiälä in southern Finland of 200x200 km2. The dense 20m-resolution dual-polarization S1A time series allow for a new level of forest land cover monitoring capabilities compared to ESA's former Envisat A(dvanced)SAR sensor. Temporal filtered dual- polarized mosaics clearly show different land covers that can be classified into forest land cover (FLC) products. Even single agricultural fields can be distinguished from these mosaics. The S1A data set also allowed the construction of a precise water mask for these sites. Results of S1A-based FLC based on two different approaches are compared to 2010 ALOS PALSAR derived FLC results and very high resolution (VHR) NDVI aerial photos. The forest land cover classes extracted are forest, disturbed forest, peatland, grassland, bare land, and settlements.

  9. US Forest Service Forest Health Protection Insect and Disease Survey

    Data.gov (United States)

    US Forest Service, Department of Agriculture — This data is a compilation of forest insect, disease and abiotic damage mapped by aerial detection surveys on forested areas in the United States. US Forest Service,...

  10. 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.

  11. Moving from Measuring, Reporting, Verification (MRV of Forest Carbon to Community Mapping, Measuring, Monitoring (MMM: Perspectives from Mexico.

    Directory of Open Access Journals (Sweden)

    Michael K McCall

    Full Text Available There have been many calls for community participation in MRV (measuring, reporting, verification for REDD+. This paper examines whether community involvement in MRV is a requirement, why it appears desirable to REDD+ agencies and external actors, and under what conditions communities might be interested in participating. It asks What's in it for communities? What might communities gain from such an involvement? What could they lose? It embraces a broader approach which we call community MMM which involves mapping, measuring and monitoring of forest and other natural resources for issues which are of interest to the community itself. We focus on cases in México because the country has an unusually high proportion of forests under community communal ownership. In particular, we refer to a recent REDD+ initiative-CONAFOR-LAIF, in which local communities select and approve local people to participate in community-based monitoring activities. From these local initiatives we identify the specific and the general drivers for communities to be involved in mapping, measuring and monitoring of their own territories and their natural resources. We present evidence that communities are more interested in this wider approach than in a narrow focus on carbon monitoring. Finally we review what the challenges to reconciling MMM with MRV requirements are likely to be.

  12. Moving from Measuring, Reporting, Verification (MRV) of Forest Carbon to Community Mapping, Measuring, Monitoring (MMM): Perspectives from Mexico.

    Science.gov (United States)

    McCall, Michael K; Chutz, Noah; Skutsch, Margaret

    2016-01-01

    There have been many calls for community participation in MRV (measuring, reporting, verification) for REDD+. This paper examines whether community involvement in MRV is a requirement, why it appears desirable to REDD+ agencies and external actors, and under what conditions communities might be interested in participating. It asks What's in it for communities? What might communities gain from such an involvement? What could they lose? It embraces a broader approach which we call community MMM which involves mapping, measuring and monitoring of forest and other natural resources for issues which are of interest to the community itself. We focus on cases in México because the country has an unusually high proportion of forests under community communal ownership. In particular, we refer to a recent REDD+ initiative-CONAFOR-LAIF, in which local communities select and approve local people to participate in community-based monitoring activities. From these local initiatives we identify the specific and the general drivers for communities to be involved in mapping, measuring and monitoring of their own territories and their natural resources. We present evidence that communities are more interested in this wider approach than in a narrow focus on carbon monitoring. Finally we review what the challenges to reconciling MMM with MRV requirements are likely to be.

  13. Sexual debut before the age of 14 leads to poorer psychosocial health and risky behaviour in later life

    OpenAIRE

    Kastbom, Åsa A; Sydsjö, Gunilla; Bladh, Marie; Priebe,Gisela; Svedin, Carl-Göran

    2014-01-01

    Aim This study investigated the relationship between sexual debut before 14 years of age and socio-demographics, sexual experience, health, experience of child abuse and behaviour at 18 years of age. Methods A sample of 3432 Swedish high school seniors completed a survey about sexuality, health and abuse at the age of 18. Results Early debut was positively correlated with risky behaviours, such as the number of partners, experience of oral and anal sex, health behaviours, such as smoking, dru...

  14. Capacidad predictiva de la erotofilia y variables sociodemográficas sobre el debut sexual

    Directory of Open Access Journals (Sweden)

    Mª Paz Bermúdez

    2014-01-01

    Full Text Available The aim of the present study was to compare the predictive ability of erotophilia and socio-demographic variables (i.e., sex, age, religion, school shift (morning/afternoon, sexual orientation, socio-economic status and family structure with regard to participants’ sexual experience or lack of it and age of sexual debut in an adolescent sample. The sample was composed of 1,503 Colombian adolescents (45% females aged between 12 and 18 years (M = 14.95; SD = 1.46. The Spanish adaptation of the Sexual Opinion Survey to assess participants’ level of erotophilia was applied. Results suggested that, after age, erotophilia is the second best predictor of having sexual intercourse. Yet, erotophilia was not found to predict age of sexual debut, which was influenced by sex, age and sexual orientation instead. We concluded that erotophilia is a construct that differentiates adolescents who have sexual relations from those who have decided not to have them yet.

  15. 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.

  16. 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.

  17. Maps of critical loads and exceedance for sulfur and nitrogen to forest soils in Norway

    Energy Technology Data Exchange (ETDEWEB)

    Frogner, T.; Wright, R.F.; Cosby, B.J.; Esser, J.M.

    1994-12-31

    This report uses the dynamic MAGIC (Model of Acidification of Groundwater in Catchments) model to calculate critical loads of sulfur and nitrogen for forest soils in Norway. Inputs include soil survey data, atmospheric deposition data, forest productivity data, and surface water chemistry. Two scenarios for future sulfur deposition are used with two scenarios of nitrogen retention in catchments. The magnitude and patterns of calculated nitrogen critical loads and exceedance differ substantially depending on the scenario chosen for sulfur deposition and nitrogen retention. In the worst case, critical loads for N are low and exceeded in southernmost Norway. In the best case, critical loads for N are high and not exceeded. More information on the processes controlling N retention in forested ecosystems is of utmost importance for the specification of nitrogen critical loads. 25 refs., 14 figs., 1 table

  18. 基于MapInfo软件绘制湖北省森林分布图%Forest Distribution Mapping of Hubei Province based on MapInfo Software

    Institute of Scientific and Technical Information of China (English)

    肖微

    2006-01-01

    以地理信息系统软件MapInfo为设计平台,介绍了利用湖北省遥感卫星影像(RS)判读数据制作森林分布图的方法和步骤.重点阐述了MapInfo在制图方面的各项功能以及遥感卫星影像判读数据在MapInfo平台中应用的技术手段.

  19. 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

  20. 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.

  1. Rapid land cover map updates using change detection and robust random forest classifiers

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2016-01-01

    Full Text Available 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...

  2. Quantifying soil and critical zone variability in a forested catchment through digital soil mapping

    Science.gov (United States)

    Quantifying catchment scale soil property variation yields insights into critical zone evolution and function. The objective of this study was to quantify and predict the spatial distribution of soil properties within a high elevation forested catchment in southern AZ, USA using a combined set of di...

  3. Mapping forest stand complexity for woodland caribou habitat assessment using multispectral airborne imagery

    Science.gov (United States)

    Zhang, W.; Hu, B.; Woods, M.

    2014-11-01

    The decline of the woodland caribou population is a result of their habitat loss. To conserve the habitat of the woodland caribou and protect it from extinction, it is critical to accurately characterize and monitor its habitat. Conventionally, products derived from low to medium spatial resolution remote sensing data, such as land cover classification and vegetation indices are used for wildlife habitat assessment. These products fail to provide information on the structure complexities of forest canopies which reflect important characteristics of caribou's habitats. Recent studies have employed the LiDAR system (Light Detection And Ranging) to directly retrieve the three dimensional forest attributes. Although promising results have been achieved, the acquisition cost of LiDAR data is very high. In this study, utilizing the very high spatial resolution imagery in characterizing the structural development the of forest canopies was exploited. A stand based image texture analysis was performed to predict forest succession stages. The results were demonstrated to be consistent with those derived from LiDAR data.

  4. 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 improvement in estimating the beech forest structural attributes compared to NDVI using linear regression models. Mean DBH was the best predicted variable among the stand parameters (calibration R2 = 0.62 for an exponential model fit and standard error...

  5. The cross-correlation between 21cm intensity mapping maps and the Lyman-alpha forest in the post-reionization era

    CERN Document Server

    Carucci, Isabella P; Viel, Matteo

    2016-01-01

    We investigate the cross-correlation signal between 21cm intensity mapping maps and the Lyman-alpha forest in the fully non-linear regime using state-of-the-art hydrodynamic simulations. The cross-correlation signal between these fields 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 Lyman-alpha systems, will show up as regions with low (high) transmitted flux. We find that on scales smaller than k = 0.2 h/Mpc 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 determi...

  6. Comparison of UAV and WorldView-2 imagery for mapping leaf area index of mangrove forest

    Science.gov (United States)

    Tian, Jinyan; Wang, Le; Li, Xiaojuan; Gong, Huili; Shi, Chen; Zhong, Ruofei; Liu, Xiaomeng

    2017-09-01

    Unmanned Aerial Vehicle (UAV) remote sensing has opened the door to new sources of data to effectively characterize vegetation metrics at very high spatial resolution and at flexible revisit frequencies. Successful estimation of the leaf area index (LAI) in precision agriculture with a UAV image has been reported in several studies. However, in most forests, the challenges associated with the interference from a complex background and a variety of vegetation species have hindered research using UAV images. To the best of our knowledge, very few studies have mapped the forest LAI with a UAV image. In addition, the drawbacks and advantages of estimating the forest LAI with UAV and satellite images at high spatial resolution remain a knowledge gap in existing literature. Therefore, this paper aims to map LAI in a mangrove forest with a complex background and a variety of vegetation species using a UAV image and compare it with a WorldView-2 image (WV2). In this study, three representative NDVIs, average NDVI (AvNDVI), vegetated specific NDVI (VsNDVI), and scaled NDVI (ScNDVI), were acquired with UAV and WV2 to predict the plot level (10 × 10 m) LAI. The results showed that AvNDVI achieved the highest accuracy for WV2 (R2 = 0.778, RMSE = 0.424), whereas ScNDVI obtained the optimal accuracy for UAV (R2 = 0.817, RMSE = 0.423). In addition, an overall comparison results of the WV2 and UAV derived LAIs indicated that UAV obtained a better accuracy than WV2 in the plots that were covered with homogeneous mangrove species or in the low LAI plots, which was because UAV can effectively eliminate the influence from the background and the vegetation species owing to its high spatial resolution. However, WV2 obtained a slightly higher accuracy than UAV in the plots covered with a variety of mangrove species, which was because the UAV sensor provides a negative spectral response function(SRF) than WV2 in terms of the mangrove LAI estimation.

  7. Predicting a multi-parametric probability map of active tumor extent using random forests.

    Science.gov (United States)

    Prior, Fred W; Fouke, Sarah J; Benzinger, Tammie; Boyd, Alicia; Chicoine, Michael; Cholleti, Sharath; Kelsey, Matthew; Keogh, Bart; Kim, Lauren; Milchenko, Mikhail; Politte, David G; Tyree, Stephen; Weinberger, Kilian; Marcus, Daniel

    2013-01-01

    Glioblastoma Mulitforme is highly infiltrative, making precise delineation of tumor margin difficult. Multimodality or multi-parametric MR imaging sequences promise an advantage over anatomic sequences such as post contrast enhancement as methods for determining the spatial extent of tumor involvement. In considering multi-parametric imaging sequences however, manual image segmentation and classification is time-consuming and prone to error. As a preliminary step toward integration of multi-parametric imaging into clinical assessments of primary brain tumors, we propose a machine-learning based multi-parametric approach that uses radiologist generated labels to train a classifier that is able to classify tissue on a voxel-wise basis and automatically generate a tumor segmentation. A random forests classifier was trained using a leave-one-out experimental paradigm. A simple linear classifier was also trained for comparison. The random forests classifier accurately predicted radiologist generated segmentations and tumor extent.

  8. Predicting a Multi-Parametric Probability Map of Active Tumor Extent Using Random Forests*

    Science.gov (United States)

    Prior, Fred W.; Fouke, Sarah J.; Benzinger, Tammie; Boyd, Alicia; Chicoine, Michael; Cholleti, Sharath; Kelsey, Matthew; Keogh, Bart; Kim, Lauren; Milchenko, Mikhail; Politte, David G.; Tyree, Stephen; Weinberger, Kilian; Marcus, Daniel

    2014-01-01

    Glioblastoma Mulitforme is highly infiltrative, making precise delineation of tumor margin difficult. Multimodality or multi-parametric MR imaging sequences promise an advantage over anatomic sequences such as post contrast enhancement as methods for determining the spatial extent of tumor involvement. In considering multi-parametric imaging sequences however, manual image segmentation and classification is time-consuming and prone to error. As a preliminary step toward integration of multi-parametric imaging into clinical assessments of primary brain tumors, we propose a machine-learning based multi-parametric approach that uses radiologist generated labels to train a classifier that is able to classify tissue on a voxel-wise basis and automatically generate a tumor segmentation. A random forests classifier was trained using a leave-one-out experimental paradigm. A simple linear classifier was also trained for comparison. The random forests classifier accurately predicted radiologist generated segmentations and tumor extent. PMID:24111225

  9. 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.

  10. Mapping Above- and Below-Ground Carbon Pools in Boreal Forests: The Case for Airborne Lidar.

    Science.gov (United States)

    Kristensen, Terje; Næsset, Erik; Ohlson, Mikael; Bolstad, Paul V; Kolka, Randall

    2015-01-01

    A large and growing body of evidence has demonstrated that airborne scanning light detection and ranging (lidar) systems can be an effective tool in measuring and monitoring above-ground forest tree biomass. However, the potential of lidar as an all-round tool for assisting in assessment of carbon (C) stocks in soil and non-tree vegetation components of the forest ecosystem has been given much less attention. Here we combine the use airborne small footprint scanning lidar with fine-scale spatial C data relating to vegetation and the soil surface to describe and contrast the size and spatial distribution of C pools within and among multilayered Norway spruce (Picea abies) stands. Predictor variables from lidar derived metrics delivered precise models of above- and below-ground tree C, which comprised the largest C pool in our study stands. We also found evidence that lidar canopy data correlated well with the variation in field layer C stock, consisting mainly of ericaceous dwarf shrubs and herbaceous plants. However, lidar metrics derived directly from understory echoes did not yield significant models. Furthermore, our results indicate that the variation in both the mosses and soil organic layer C stock plots appears less influenced by differences in stand structure properties than topographical gradients. By using topographical models from lidar ground returns we were able to establish a strong correlation between lidar data and the organic layer C stock at a stand level. Increasing the topographical resolution from plot averages (~2000 m2) towards individual grid cells (1 m2) did not yield consistent models. Our study demonstrates a connection between the size and distribution of different forest C pools and models derived from airborne lidar data, providing a foundation for future research concerning the use of lidar for assessing and monitoring boreal forest C.

  11. Comparative Analysis of EO-1 ALI and Hyperion, and Landsat ETM+ Data for Mapping Forest Crown Closure and Leaf Area Index.

    Science.gov (United States)

    Pu, Ruiliang; Gong, Peng; Yu, Qian

    2008-06-06

    In this study, a comparative analysis of capabilities of three sensors for mapping forest crown closure (CC) and leaf area index (LAI) was conducted. The three sensors are Hyperspectral Imager (Hyperion) and Advanced Land Imager (ALI) onboard EO-1 satellite and Landsat-7 Enhanced Thematic Mapper Plus (ETM+). A total of 38 mixed coniferous forest CC and 38 LAI measurements were collected at Blodgett Forest Research Station, University of California at Berkeley, USA. The analysis method consists of (1) extracting spectral vegetation indices (VIs), spectral texture information and maximum noise fractions (MNFs), (2) establishing multivariate prediction models, (3) predicting and mapping pixel-based CC and LAI values, and (4) validating the mapped CC and LAI results with field validated photo-interpreted CC and LAI values. The experimental results indicate that the Hyperion data are the most effective for mapping forest CC and LAI (CC mapped accuracy (MA) = 76.0%, LAI MA = 74.7%), followed by ALI data (CC MA = 74.5%, LAI MA = 70.7%), with ETM+ data results being least effective (CC MA = 71.1%, LAI MA = 63.4%). This analysis demonstrates that the Hyperion sensor outperforms the other two sensors: ALI and ETM+. This is because of its high spectral resolution with rich subtle spectral information, of its short-wave infrared data for constructing optimal VIs that are slightly affected by the atmosphere, and of its more available MNFs than the other two sensors to be selected for establishing prediction models. Compared to ETM+ data, ALI data are better for mapping forest CC and LAI due to ALI data with more bands and higher signal-to-noise ratios than those of ETM+ data.

  12. Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data

    CSIR Research Space (South Africa)

    Malahlela, OE

    2015-07-01

    Full Text Available Globally, subtropical forests are rich in biodiversity. However, the native biodiversity in these forests is threatened by the presence of invasive species such as Chromolaena odorata (L.) King and Robinson, which thrives in forest canopy gaps. Our...

  13. Forests and Forest Cover, Parcel Map/Taxroll Data, Published in 1997, 1:24000 (1in=2000ft) scale, Lafayette County Land Records.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Forests and Forest Cover dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Published Reports/Deeds information as of 1997. It...

  14. Polarimetric ALOS PALSAR Time Series in Mapping Biomass of Boreal Forests

    Directory of Open Access Journals (Sweden)

    Oleg Antropov

    2017-09-01

    Full Text Available Here, we examined multitemporal behavior of fully polarimetric SAR (PolSAR parameters at L-band in relation to the stem volume of boreal forests. The PolSAR parameters were evaluated in terms of their temporal consistency, inter-dependence and suitability for forest stem volume estimation across several seasonal conditions (frozen, thaw and unfrozen. The satellite SAR data were represented by a time series of PolSAR images acquired during several seasons in the years 2006 to 2009 by the ALOS PALSAR sensor. The study area was in central Finland, and represented a managed area in typical boreal mixed forest land. Utility of different PolSAR parameters, their temporal stability and cross-correlations were studied along with reference stand-level stem volume data from forest inventory. Further, two polarimetric parameters, cross-polarization backscatter and co-polarization coherence, were chosen for further investigation and stem volume retrieval. A relationship between forest stem volume and PolSAR parameters was established using the kNN regression approach. Ways of optimally combining PolSAR images were evaluated as well. For a single scene, best results were observed with polarimetric coherence (RMSE ≈ 38.8 m3/ha for scene acquired in frozen conditions. An RMSE of 40.8 m3/ha (42.9%, R2 = 0.66 was achieved for cross-polarization backscatter in the best case. Cross-polarization backscatter was a better predictor than polarimetric coherence for few summer scenes. Multitemporal aggregation of selected PolSAR scenes improved estimates for both studied PolSAR parameters. Stronger improvement was observed for coherence with RMSE down to 34 m3/ha (35.8%, R2 = 0.77 compared to 38.8–51.6 m3/ha (40.8–54.3% from separate scenes. Finally, the accuracy statistics reached RMSE of 32.2 m3/ha (34%, R2 = 0.79 when multitemporal HHVV coherence was combined with multitemporal HV-backscatter.

  15. 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.

  16. Vegetation map for the Hakalau Forest Unit of the Big Island National Wildlife Refuge Complex on the island of Hawai‘i

    Science.gov (United States)

    Jacobi, James D.

    2017-01-01

    This vegetation map was produced to serve as an updated habitat base for management of natural resources of the Hakalau Forest Unit (HFU) of the Big Island National Wildlife Refuge Complex (Refuge) on the island of Hawai‘i. The map is based on a vegetation map originally produced as part of the U.S. Fish and Wildlife Service’s Hawai‘i Forest Bird Survey to depict the distribution, structure, and composition of plant communities on the island of Hawai‘i as they existed in 1977. The current map has been updated to represent current conditions of plant communities in the HFU, based on WorldView 2 imagery taken in 2012 and very-high-resolution imagery collected by Pictometry International from 2010 to 2014. Thirty-one detailed plant communities are identified on this map, and fourteen of these units are found within the boundaries of HFU. Additionally, the mapped units can be displayed as five tree canopy cover units, three moisture zones units, eight dominant tree species units, and four habitat status units by choosing the various fields to group the units from the map attribute table. This updated map will provide a foundation for the refinement and tracking of management actions on the Refuge for the near future, particularly as the habitats in this area are subject to projected climate change.

  17. Optical and SAR sensor synergies for forest and land cover mapping in a tropical site in West Africa

    Science.gov (United States)

    Vaglio Laurin, Gaia; Liesenberg, Veraldo; Chen, Qi; Guerriero, Leila; Del Frate, Fabio; Bartolini, Antonio; Coomes, David; Wilebore, Beccy; Lindsell, Jeremy; Valentini, Riccardo

    2013-04-01

    The classification of tropical fragmented landscapes and moist forested areas is a challenge due to the presence of a continuum of vegetation successional stages, persistent cloud cover and the presence of small patches of different land cover types. To classify one such study area in West Africa we integrated the optical sensors Landsat Thematic Mapper (TM) and the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) with the Phased Arrayed L-band SAR (PALSAR) sensor, the latter two on-board the Advanced Land Observation Satellite (ALOS), using traditional Maximum Likelihood (MLC) and Neural Networks (NN) classifiers. The impact of texture variables and the use of SAR to cope with optical data unavailability were also investigated. SAR and optical integrated data produced the best classification overall accuracies using both MLC and NN, respectively equal to 91.1% and 92.7% for TM and 95.6% and 97.5% for AVNIR-2. Texture information derived from optical images was critical, improving results between 10.1% and 13.2%. In our study area, PALSAR alone was able to provide valuable information over the entire area: when the three forest classes were aggregated, it achieved 75.7% (with MCL) and 78.1% (with NN) overall classification accuracies. The selected classification and processing methods resulted in fine and accurate vegetation mapping in a previously untested region, exploiting all available sensors synergies and highlighting the advantages of each dataset.

  18. Mapping Shorea natural distribution in the last remaining forests in Riau as a baseline information for conservation strategy

    Science.gov (United States)

    Subiakto, Atok; Hendalastuti Rachmat, Henti; Wijaya, Kesuma

    2017-01-01

    Shorea divided into four groups: Shorea Red Meranti, White Meranti, Yellow Meranti and Balau. In the past, conservation was not an important issue as this groups were common and abundant. However, Sumatran rain forest were cleared and converted at annual rate of 500.000 Ha with the most extensive in the Province of Riau where had lost 63% between 1985 and 2009. This study conducted to determine the potency and availability of most valuable tropical Shorea dipterocarps in Riau Province. Lines transect and point count methods used to determine the presence any of the Shorea species in the designated remnants area. Leaves samples for morphological identification collected for further taxonomic identification. Data analysis for mapping conducted by overlying the secondary and primary data source. The result showed that the patchy remnants forests in Riau still conserve at least of around 22 Shorea species, included 14 species those of Shorea Red Meranti, 1species Shorea White Meranti, 4 species Shorea Yellow Meranti, and 3 species of Shorea Balau. However, in average the numbers of individual found for each of the species was low with uncomplete occurrence of the life stage in several spots, showing the fragility of local species loss and extinction.

  19. Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object-based classification approaches.

    Science.gov (United States)

    Meneguzzo, Dacia M; Liknes, Greg C; Nelson, Mark D

    2013-08-01

    Discrete trees and small groups of trees in nonforest settings are considered an essential resource around the world and are collectively referred to as trees outside forests (ToF). ToF provide important functions across the landscape, such as protecting soil and water resources, providing wildlife habitat, and improving farmstead energy efficiency and aesthetics. Despite the significance of ToF, forest and other natural resource inventory programs and geospatial land cover datasets that are available at a national scale do not include comprehensive information regarding ToF in the United States. Additional ground-based data collection and acquisition of specialized imagery to inventory these resources are expensive alternatives. As a potential solution, we identified two remote sensing-based approaches that use free high-resolution aerial imagery from the National Agriculture Imagery Program (NAIP) to map all tree cover in an agriculturally dominant landscape. We compared the results obtained using an unsupervised per-pixel classifier (independent component analysis-[ICA]) and an object-based image analysis (OBIA) procedure in Steele County, Minnesota, USA. Three types of accuracy assessments were used to evaluate how each method performed in terms of: (1) producing a county-level estimate of total tree-covered area, (2) correctly locating tree cover on the ground, and (3) how tree cover patch metrics computed from the classified outputs compared to those delineated by a human photo interpreter. Both approaches were found to be viable for mapping tree cover over a broad spatial extent and could serve to supplement ground-based inventory data. The ICA approach produced an estimate of total tree cover more similar to the photo-interpreted result, but the output from the OBIA method was more realistic in terms of describing the actual observed spatial pattern of tree cover.

  20. EU-wide maps of growing stock and above-ground biomass in forests based on remote sensing and field measurements

    NARCIS (Netherlands)

    Gallaun, H.; Zanchi, G.; Nabuurs, G.J.; Hengeveld, G.M.; Schardt, M.; Verkerk, P.J.

    2010-01-01

    The overall objective of this study was to combine national forest inventory data and remotely sensed data to produce pan-European maps on growing stock and above-ground woody biomass for the two species groups " broadleaves" and " conifers" An automatic up-scaling approach making use of satellite

  1. Validating a novel lidar distributional approach for forest floor fuel load mapping: Eastern hardwoods vs. western spruce-fir environments

    Science.gov (United States)

    van Aardt, J. A.; Arthur, M.; Swetnam, T.; Mitchell, B.

    2013-12-01

    Light detection and ranging (lidar) remote sensing has been used extensively for a variety of forest structural assessment applications, ranging from forest volume and biomass assessment, to ecological applications, such as leaf area and fuel load modelling. However, most of these applications have focused on assessment of parameters that rely on upper-canopy lidar returns, e.g., tree height, crown delineation (stems/hectare), and even tree-to-stand-level volume or biomass quantification. It is evident that detection and subsequent quantification of near-ground woody structure remains a challenge, especially when considering coarse woody debris (CWD). This is true due to a number of factors: (i) the lidar signal attenuates through the canopy; (ii) lidar systems can be set to record the last of many returns, i.e., often the ground itself; (iii) system-specific vertical resolution specifications impact detection of structure in-between lidar returns; and (iv) we often attribute 'noisy' near-ground signal to just that, noise. We argue that there is coherent signal that can be exploited for near ground returns, if this is approached with the necessary system and scientific knowledge. We have shown in a previous study that a lidar return distributional approach to CWD modelling, that included both above-ground and theoretical 'below-ground' returns, can be successfully used to map CWD for various fuel loads. This approach hinged on the assumption that so-called below-ground returns can be attributed to multiple scattering events, even at the small beam divergence angle and instantaneous field-of-view (IFOV) found in most modern lidar sensors. Results included adjusted R2 values of up to 0.99 and root mean square error values as low as 0.111 Mg/ha (4.7% of the mean) for an oak dominant forests in central Appalachia, Kentucky, USA, when modelling medium-fast burning (10h) and medium-slow burning (100h) CWD fuel loads. Independent variables included parameters from both

  2. Mapping the optimal forest road network based on the multicriteria evaluation technique: the case study of Mediterranean Island of Thassos in Greece.

    Science.gov (United States)

    Tampekis, Stergios; Sakellariou, Stavros; Samara, Fani; Sfougaris, Athanassios; Jaeger, Dirk; Christopoulou, Olga

    2015-11-01

    The sustainable management of forest resources can only be achieved through a well-organized road network designed with the optimal spatial planning and the minimum environmental impacts. This paper describes the spatial layout mapping for the optimal forest road network and the environmental impacts evaluation that are caused to the natural environment based on the multicriteria evaluation (MCE) technique at the Mediterranean island of Thassos in Greece. Data analysis and its presentation are achieved through a spatial decision support system using the MCE method with the contribution of geographic information systems (GIS). With the use of the MCE technique, we evaluated the human impact intensity to the forest ecosystem as well as the ecosystem's absorption from the impacts that are caused from the forest roads' construction. For the human impact intensity evaluation, the criteria that were used are as follows: the forest's protection percentage, the forest road density, the applied skidding means (with either the use of tractors or the cable logging systems in timber skidding), the timber skidding direction, the visitors' number and truck load, the distance between forest roads and streams, the distance between forest roads and the forest boundaries, and the probability that the forest roads are located on sights with unstable soils. In addition, for the ecosystem's absorption evaluation, we used forestry, topographical, and social criteria. The recommended MCE technique which is described in this study provides a powerful, useful, and easy-to-use implement in order to combine the sustainable utilization of natural resources and the environmental protection in Mediterranean ecosystems.

  3. Adolescent Sexual Debut and Initiation into New-Type Drug Use among a Sample of Young Adults.

    Science.gov (United States)

    Ding, Yingying; He, Na; Detels, Roger

    2015-01-01

    We examined the association between adolescent sexual debut and age at new-type drug initiation among a sample of young adult new-type drug users. A total of 276 participants were recruited using respondent-driven sampling (RDS) in Shanghai, China. The analyses were restricted to a total of 201 participants aged between 18 and 30 years. The average age at sexual debut and age at first new-type drug use were 18.8 and 20.9 years, respectively. About 94% of participants reported having sexual experience (n=188); of those, 137 (72.9%) had sexual debut before they first used new-type drugs, while 32 (17.0%) initiated both events at the same age. After adjustment for age, income, education, and sexual orientation, adolescent sexual debut was independently associated with younger age at new-type drug initiation. Adolescent sexual debut is associated with early onset of new-type drug use. Our findings underscore the importance of implementing sex-education programs for adolescents in schools in China.

  4. Spot-mapping underestimates song-territory size and use of mature forest by breeding golden-winged warblers in Minnesota, USA

    Science.gov (United States)

    Streby, Henry M.; Loegering, John P.; Andersen, David E.

    2012-01-01

    Studies of songbird breeding habitat often compare habitat characteristics of used and unused areas. Although there is usually meticulous effort to precisely and consistently measure habitat characteristics, accuracy of methods for estimating which areas are used versus which are unused by birds remains generally untested. To examine accuracy of spot-mapping to identify singing territories of golden-winged warblers (Vermivora chrysoptera), which are considered an early successional forest specialists, we used spot-mapping and radiotelemetry to record song perches and delineate song territories for breeding male golden-winged warblers in northwestern Minnesota, USA. We also used radiotelemetry to record locations (song and nonsong perches) of a subsample (n = 12) of males throughout the day to delineate home ranges. We found that telemetry-based estimates of song territories were 3 times larger and included more mature forest than those estimated from spot-mapping. In addition, home ranges estimated using radiotelemetry included more mature forest than spot-mapping- and telemetry-based song territories, with 75% of afternoon perches located in mature forest. Our results suggest that mature forest comprises a larger component of golden-winged warbler song territories and home ranges than is indicated based on spot-mapping in Minnesota. Because it appears that standard observational methods can underestimate territory size and misidentify cover-type associations for golden-winged warblers, we caution that management and conservation plans may be misinformed, and that similar studies are needed for golden-winged warblers across their range and for other songbird species.

  5. 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.

  6. Mapping forest plantations in Mainland China: combining remotely sensed land cover and census land use data in a land transition model

    Science.gov (United States)

    Ying, Q.; Hurtt, G. C.; Chini, L. P.; Fisk, J.; Liang, S.; Hansen, M.; Dolan, K. A.

    2013-12-01

    Forest plantations have played an important role in shaping the coverage and compositions of China's forests. Maps characterizing the spatial and temporal patterns of forest plantations in china are essential to both identifying and quantifying how forest plantations are driving changes to the countries ecosystem structure and terrestrial carbon cycle. At this time there are no detailed spatial maps of plantations in China accessible to public. Land transition model that employs Metropolis simulated annealing optimization has been demonstrated effective in land use mapping when land cover observations and land use census data are available. This study aims to map forest plantations in Mainland China by linking remote sensing observations of land cover and census statistics on land use in land transition model. Two models, a national model and a regional model were developed in the study. National model depicted a universal relationship between land cover and land use across the whole country. One of the land use data sources came from the 7th National Forest Inventory (NFI) that depicted forest plantation area in the period of 2004-2008 in each provincial jurisdictions of China (Data from Taiwan, Hongkong and Macau is not available). In accordance with land use data, MODIS yearly IGBP land cover product that contains sixteen-land cover types has been averaged upon the same time period and summarized for each province. The pairwise correlation coefficient between modeled value and reported value is 0.9996. In addition, the 95% confidence interval of true population correlation of these two variables is [0.9994, 0.9998]. Because the targeted forest plantations cover much less area compared to the other land use type of non-plantation, model precision on forest plantations was isolated to eliminate the dominance in area of non-plantation and the correlation coefficient is 0.8058. National model tends to underestimate plantation area. Due to distinct geographic and

  7. Chinese Autos' Debut in Cambodia--Let more Cambodians know high-quality Chinese products

    Institute of Scientific and Technical Information of China (English)

    Jing; Xiong; Phnom; Penh

    2005-01-01

      The 3rd Mudan Cup China International Auto Exhibition (Vietnam & Cambodia) was held in January 28, 2005 in Phnom Penh Hotel. This is the first debut of Chinese autos in Cambodia. 11 buses, 12 seats tourism vans, cargo vans and trucks and 9 motorcycles of different brands showed Cambodians the real Chinese famous brands and high-quality automobiles. The 3rd "Mudan Cup"China International Auto Exhibition Tour was organized by the Society of Automotive Engineers of China, Department of Media and Press of CCPIT, Cambodia Tang Ren International Co., Ltd.,Cambodia Kaide Trade Co., Ltd. andChina Grand River Group.……

  8. Chinese Autos' Debut in Cambodia--Let more Cambodians know high-quality Chinese products

    Institute of Scientific and Technical Information of China (English)

    Jing Xiong; Phnom Penh

    2005-01-01

    @@ The 3rd Mudan Cup China International Auto Exhibition (Vietnam & Cambodia) was held in January 28, 2005 in Phnom Penh Hotel. This is the first debut of Chinese autos in Cambodia. 11 buses, 12 seats tourism vans, cargo vans and trucks and 9 motorcycles of different brands showed Cambodians the real Chinese famous brands and high-quality automobiles. The 3rd "Mudan Cup"China International Auto Exhibition Tour was organized by the Society of Automotive Engineers of China, Department of Media and Press of CCPIT, Cambodia Tang Ren International Co., Ltd.,Cambodia Kaide Trade Co., Ltd. andChina Grand River Group.

  9. A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions

    Science.gov (United States)

    Selkowitz, David J.; Green, Gordon; Peterson, Birgit E.; Wylie, Bruce

    2012-01-01

    Spatially explicit representations of vegetation canopy height over large regions are necessary for a wide variety of inventory, monitoring, and modeling activities. Although airborne lidar data has been successfully used to develop vegetation canopy height maps in many regions, for vast, sparsely populated regions such as the boreal forest biome, airborne lidar is not widely available. An alternative approach to canopy height mapping in areas where airborne lidar data is limited is to use spaceborne lidar measurements in combination with multi-angular and multi-spectral remote sensing data to produce comprehensive canopy height maps for the entire region. This study uses spaceborne lidar data from the Geosciences Laser Altimeter System (GLAS) as training data for regression tree models that incorporate multi-angular and multi-spectral data from the Multi-Angle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging SpectroRadiometer (MODIS) to map vegetation canopy height across a 1,300,000 km2 swath of boreal forest in Interior Alaska. Results are compared to in situ height measurements as well as airborne lidar data. Although many of the GLAS-derived canopy height estimates are inaccurate, applying a series of filters incorporating both data associated with the GLAS shots as well as ancillary data such as land cover can identify the majority of height estimates with significant errors, resulting in a filtered dataset with much higher accuracy. Results from the regression tree models indicate that late winter MISR imagery acquired under snow-covered conditions is effective for mapping canopy heights ranging from 5 to 15 m, which includes the vast majority of forests in the region. It appears that neither MISR nor MODIS imagery acquired during the growing season is effective for canopy height mapping, although including summer multi-spectral MODIS data along with winter MISR imagery does appear to provide a slight increase in the accuracy of

  10. Mapping forest canopy fuels in Yellowstone National Park using lidar and hyperspectral data

    Science.gov (United States)

    Halligan, Kerry Quinn

    The severity and size of wildland fires in the forested western U.S have increased in recent years despite improvements in fire suppression efficiency. This, along with increased density of homes in the wildland-urban interface, has resulted in high costs for fire management and increased risks to human health, safety and property. Crown fires, in comparison to surface fires, pose an especially high risk due to their intensity and high rate of spread. Crown fire models require a range of quantitative fuel parameters which can be difficult and costly to obtain, but advances in lidar and hyperspectral sensor technologies hold promise for delivering these inputs. Further research is needed, however, to assess the strengths and limitations of these technologies and the most appropriate analysis methodologies for estimating crown fuel parameters from these data. This dissertation focuses on retrieving critical crown fuel parameters, including canopy height, canopy bulk density and proportion of dead canopy fuel, from airborne lidar and hyperspectral data. Remote sensing data were used in conjunction with detailed field data on forest parameters and surface reflectance measurements. A new method was developed for retrieving Digital Surface Model (DSM) and Digital Canopy Models (DCM) from first return lidar data. Validation data on individual tree heights demonstrated the high accuracy (r2 0.95) of the DCMs developed via this new algorithm. Lidar-derived DCMs were used to estimate critical crown fire parameters including available canopy fuel, canopy height and canopy bulk density with linear regression model r2 values ranging from 0.75 to 0.85. Hyperspectral data were used in conjunction with Spectral Mixture Analysis (SMA) to assess fuel quality in the form of live versus dead canopy proportions. Severity and stage of insect-caused forest mortality were estimated using the fractional abundance of green vegetation, non-photosynthetic vegetation and shade obtained from

  11. 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

  12. 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...

  13. US Forest Service Healthy Forest Restoration Act

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting areas designated within National Forest System Lands, in 37 States, that are eligible for insect and disease treatments under...

  14. US Forest Service National Forest System Trails

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the world wide web that depicts National Forest Service trails that have been approved for publication. This service is used internally and...

  15. US Forest Service Administrative Forest Boundaries

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting all the National Forest System lands administered by an unit. These areas encompasse private lands, other governmental agency...

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

    Energy Technology Data Exchange (ETDEWEB)

    Tamminen, P.; Aro, A.; Salemaa, M. (Finnish Forest Research Institute, Helsinki (Finland))

    2007-09-15

    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.)

  17. Mapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imagery

    Science.gov (United States)

    Fagan, Matthew E.; Defries, Ruth S.; Sesnie, Steven E.; Arroyo-Mora, J. Pablo; Soto, Carlomagno; Singh, Aditya; Townsend, Philip A.; Chazdon, Robin L.

    2015-01-01

    An efficient means to map tree plantations is needed to detect tropical land use change and evaluate reforestation projects. To analyze recent tree plantation expansion in northeastern Costa Rica, we examined the potential of combining moderate-resolution hyperspectral imagery (2005 HyMap mosaic) with multitemporal, multispectral data (Landsat) to accurately classify (1) general forest types and (2) tree plantations by species composition. Following a linear discriminant analysis to reduce data dimensionality, we compared four Random Forest classification models: hyperspectral data (HD) alone; HD plus interannual spectral metrics; HD plus a multitemporal forest regrowth classification; and all three models combined. The fourth, combined model achieved overall accuracy of 88.5%. Adding multitemporal data significantly improved classification accuracy (p less than 0.0001) of all forest types, although the effect on tree plantation accuracy was modest. The hyperspectral data alone classified six species of tree plantations with 75% to 93% producer's accuracy; adding multitemporal spectral data increased accuracy only for two species with dense canopies. Non-native tree species had higher classification accuracy overall and made up the majority of tree plantations in this landscape. Our results indicate that combining occasionally acquired hyperspectral data with widely available multitemporal satellite imagery enhances mapping and monitoring of reforestation in tropical landscapes.

  18. Mapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imagery

    Directory of Open Access Journals (Sweden)

    Matthew E. Fagan

    2015-05-01

    Full Text Available An efficient means to map tree plantations is needed to detect tropical land use change and evaluate reforestation projects. To analyze recent tree plantation expansion in northeastern Costa Rica, we examined the potential of combining moderate-resolution hyperspectral imagery (2005 HyMap mosaic with multitemporal, multispectral data (Landsat to accurately classify (1 general forest types and (2 tree plantations by species composition. Following a linear discriminant analysis to reduce data dimensionality, we compared four Random Forest classification models: hyperspectral data (HD alone; HD plus interannual spectral metrics; HD plus a multitemporal forest regrowth classification; and all three models combined. The fourth, combined model achieved overall accuracy of 88.5%. Adding multitemporal data significantly improved classification accuracy (p < 0.0001 of all forest types, although the effect on tree plantation accuracy was modest. The hyperspectral data alone classified six species of tree plantations with 75% to 93% producer’s accuracy; adding multitemporal spectral data increased accuracy only for two species with dense canopies. Non-native tree species had higher classification accuracy overall and made up the majority of tree plantations in this landscape. Our results indicate that combining occasionally acquired hyperspectral data with widely available multitemporal satellite imagery enhances mapping and monitoring of reforestation in tropical landscapes.

  19. The Penetration Depth Derived from the Synthesis of ALOS/PALSAR InSAR Data and ASTER GDEM for the Mapping of Forest Biomass

    Directory of Open Access Journals (Sweden)

    Wenjian Ni

    2014-08-01

    Full Text Available The Global Digital Elevation Model produced from stereo images of Advanced Spaceborne Thermal Emission and Reflection Radiometer data (ASTER GDEM covers land surfaces between latitudes of 83°N and 83°S. The Phased Array type L-band Synthetic Aperture Radar (PALSAR onboard Advanced Land Observing Satellite (ALOS collected many SAR images since it was launched on 24 January 2006. The combination of ALOS/PALSAR interferometric data and ASTER GDEM should provide the penetration depth of SAR data assuming ASTER GDEM was the elevation of vegetation canopy top. It would be correlated with forest biomass because penetration depth could be affected by forest density and forest canopy height. Their combination held great promises for the forest biomass mapping over large area. The feasibility of forest biomass mapping through the data synthesis of ALOS/PALSAR InSAR data and ASTER GDEM was investigated in this study. A procedure for the extraction of penetration depth was firstly proposed. Then three models were built for biomass estimation: (I model only using backscattering coefficients of ALOS/PALSAR data; (II model only using penetration depth; (III model using both of them. The biomass estimated from Lidar data was taken as reference data to evaluate the three different models. The results showed that the combination of backscattering coefficients and penetration depth gave the best accuracy. The forest disturbance has to be considered in forest biomass estimation because of the long time span of ASTER data for generating ASTER GDEM. The spatial homogeneity could be used to improve estimation accuracy.

  20. Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome.

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    Stéphane Guitet

    Full Text Available Precise mapping of above-ground biomass (AGB is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate "wall-to-wall" remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5% may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution.

  1. 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

  2. Sexual debut in young adults in Cali as transition: keys for care

    Directory of Open Access Journals (Sweden)

    Claudia Patricia Valencia Molina

    2015-08-01

    Full Text Available Objectives. This work sought to understand sexual debut as a transitional process in the lives of a group of young adults and to interpret the meaning of this transition for them. Methodology. This was a qualitative research with 18 life stories of students from different socio-economic backgrounds and with diverse sexual orientations. Results. According to the middle-range theory of transitions, sexual debut can be considered a developmental transition. The initiative can be their own, motivated by desire, or coerced by pressure from a partner or peers in which case underlay power relations either by age or hierarchy. Its features are shaped by the individual´s abilities, knowledge, and uncertainties, as much as by the circumstances surrounding the event and the socio-cultural precepts towards the topic. It is valued as a healthy transitional process when it is agreed upon by both members of the couple, planned and flows into symmetrical relations. Conclusion. The theory of transitions and analysis of the context are useful in understanding the phenomenon because the subjective experience is framed within normative, appreciative, and socio-cultural constructions. Nursing, as discipline, requires elements like those provided by this research to interpret the dynamics, meanings, as well as subjective and social processes in the sexual evolution of people in different contexts and historical moments.

  3. Sexual debut in young adults in Cali as transition: keys for care.

    Science.gov (United States)

    Valencia Molina, Claudia Patricia; Canaval Erazo, Gladys Eugenia; Sevilla Peñuela, Teresita María; Orcasita Pineda, Linda Teresa

    2015-01-01

    This work sought to understand sexual debut as a transitional process in the lives of a group of young adults and to interpret the meaning of this transition for them. This was a qualitative research with 18 life stories of students from different socio-economic backgrounds and with diverse sexual orientations. According to the middle-range theory of transitions, sexual debut can be considered a developmental transition. The initiative can be their own, motivated by desire, or coerced by pressure from a partner or peers in which case underlay power relations either by age or hierarchy. Its features are shaped by the individual's abilities, knowledge, and uncertainties, as much as by the circumstances surrounding the event and the socio-cultural precepts towards the topic. It is valued as a healthy transitional process when it is agreed upon by both members of the couple, planned and flows into symmetrical relations. The theory of transitions and analysis of the context are useful in understanding the phenomenon because the subjective experience is framed within normative, appreciative, and socio-cultural constructions. Nursing, as discipline, requires elements like those provided by this research to interpret the dynamics, meanings, as well as subjective and social processes in the sexual evolution of people in different contexts and historical moments.

  4. Application of remote sensing and GIS in land use/land cover mapping and change detection in Shasha forest reserve, Nigeria

    Science.gov (United States)

    Olokeogun, O. S.; Iyiola, K.; Iyiola, O. F.

    2014-11-01

    Mapping of LULC and change detection using remote sensing and GIS techniques is a cost effective method of obtaining a clear understanding of the land cover alteration processes due to land use change and their consequences. This research focused on assessing landscape transformation in Shasha Forest Reserve, over an 18 year period. LANDSAT Satellite imageries (of 30 m resolution) covering the area at two epochs were characterized into five classes (Water Body, Forest Reserve, Built up Area, Vegetation, and Farmland) and classification performs with maximum likelihood algorithm, which resulted in the classes of each land use. The result of the comparison of the two classified images showed that vegetation (degraded forest) has increased by 30.96 %, farmland cover increased by 22.82 % and built up area by 3.09 %. Forest reserve however, has decreased significantly by 46.12 % during the period. This research highlights the increasing rate of modification of forest ecosystem by anthropogebic activities and the need to apprehend the situation to ensure sustainable forest management.

  5. Testing the use of a land cover map for habitat ranking in boreal forests.

    Science.gov (United States)

    Hilli, Milla; Kuitunen, Markku T

    2005-04-01

    Habitat loss and modification is one of the major threats to biodiversity and the preservation of conservation values. We use the term ''conservation value'' to mean the benefit of nature or habitats for species. The importance of identifying and preserving conservation values has increased with the decline in biodiversity and the adoption of more stringent environmental legislation. In this study, conservation values were considered in the context of land-use planning and the rapidly increasing demand for more accurate methods of predicting and identifying these values. We used a k-nearest neighbor interpreted satellite (Landsat TM) image classified in 61 classes to assess sites with potential conservation values at the regional and landscape planning scale. Classification was made at the National Land Survey of Finland for main tree species, timber volume, land-use type, and soil on the basis of spectral reflectance in satellite image together with broad numerical reference data. We used the number and rarity of vascular plant species observed in the field as indicators for potential conservation values. We assumed that significant differences in the species richness, rarity, or composition of flora among the classes interpreted in the satellite image would also mean a difference in conservation values among these classes. We found significant differences in species richness among the original satellite image classes. Many of the classes examined could be distinguished by the number of plant species. Species composition also differed correspondingly. Rare species were most abundant in old spruce forests (>200 m3/ha), raising the position of such forests in the ranking of categories according to conservation values. The original satellite image classification was correct for 70% of the sites studied. We concluded that interpreted satellite data can serve as a useful source for evaluating habitat categories on the basis of plant species richness and rarity

  6. 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 (Fpred including temperature, precipitation, acid deposition, soil data and relative site insolation) and forest biomass receptors (Frec 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 Fpred-Frec. Unfavourable Fpred within unfavourable Frec indicated chronic damage, favourable Fpred within unfavourable Frec indicated acute damage, and unfavourable Fpred within favourable Frec 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, Corg>1%, MgO>6g/kg, and nitrogen deposition<1200mol(H(+))/ha·year. Vulnerable forests had BShumus 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 Corg 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

  7. Segmentation and classification of high resolution imagery for mapping individual species in a closed canopy, deciduous forest

    Institute of Scientific and Technical Information of China (English)

    Timothy; A.; Warner; James; B.; McGraw; Rick; Landenberger

    2006-01-01

    In this paper we investigate the use of a shadow-based delineation program for identifying segments in imagery of a closed canopy, deciduous forest, in West Virginia, USA, as a way to reduce the noise associated with per-pixel classification in forested environments. Shadows typically cluster along the boundaries of trees and therefore can be used to provide a network of nodes for the delineation of segments. A minimum cost path algorithm, where cost is defined as the cumulative sum of brightness values traversed along the connecting route, was used to connect shadow clumps. To test this approach, a series of classifications was undertaken using a multispectral digital aerial image of a six hectare test site and a minimum cost path segmentation. Three species were mapped: oaks, red maple and yellow poplar. The accuracy of an aspatial maximum likelihood classification (termed PERPIXEL classification) was 68.5%, compared to 74.0% for classification using the mean vector of the segments identified with the minimum cost path algorithm (MEAN_SEG), and 78% when the most common class present in the segment is assigned to the entire segment (POSTCLASS_SEG). By comparison, multispectral classification of the multispectral data using the field-mapped polygons of individual trees as segments, produced an accuracy of 82.3% when the mean vector of the polygon was used for classification (MEAN_TREE), and 85.7% when the most common class was assigned to the entire polygon (POSTCLASS_TREE). A moving window-based post-classification majority filter (POSTCLASS_MAJ5BY5) produced an intermediate accuracy value, 73.8%. The minimum cost path segmentation algorithm was found to correctly delineate approximately 28% of the trees. The remaining trees were either segmented, aggregated, or a combination of both segmented and aggregated. Varying the threshold that was used to discriminate shadows appeared to have little effect on the number of correctly delineated trees, or on the overall

  8. Mapping shrublands and forests with multispectral satellite images based on spectral unmixing of scene components

    Science.gov (United States)

    Caetano, Mario R.; Oliveira, Tiago; Paul, Jose U.; Vasconcelos, Maria J.; Cardoso Pereira, Jose M.

    1997-12-01

    Linear spectral mixture models (SMM) with image endmembers (IEM) and with reference endmembers (REM) were tested for discriminating maritime pine stands and shrublands in a Landsat-TM image of Central Portugal. For both types of EM, IEM and REM, two types of SMM were tried: SMM with three EM (SMM-3), i.e., green vegetation, soil and shade, and SMM with five EM (SMM-5), where the EM were the components of the landscapes that we were interested on, i.e., pine canopy, shrub, soil, forest litter and shade. Results showed that in the SMM-5, REM need to be used, since IEM were not pure enough. We verified that in the SMM-5, there was not a single set of EM that could be applied to the whole study area, because the shrubs that exist underneath the pine canopy and in the shrublands could not be modeled just by using a shrub EM. Therefore, SMM-5 require a multi-endmember approach, where the set of EM may change from pixel to pixel. In the SMM-3, an accurate discrimination of shrublands and pine stands (90% accuracy) was achieved by thresholding the shade fraction. In these simpler SMM, IEM and REM produced similar results.

  9. US Forest Service National Forest System Land Units

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting National Forest Service land units. An NFS Land Unit is nationally significant classification of Federally owned forest, range,...

  10. US Forest Service Original Proclaimed National Forests and National Grasslands

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting the boundaries encompassing the National Forest System (NFS) lands within the original proclaimed National Forests, along with...

  11. Mapping tropical forest biomass with radar and spaceborne LiDAR in Lopé National Park, Gabon: overcoming problems of high biomass and persistent cloud

    Science.gov (United States)

    Mitchard, E. T. A.; Saatchi, S. S.; White, L. J. T.; Abernethy, K. A.; Jeffery, K. J.; Lewis, S. L.; Collins, M.; Lefsky, M. A.; Leal, M. E.; Woodhouse, I. H.; Meir, P.

    2012-01-01

    Spatially-explicit maps of aboveground biomass are essential for calculating the losses and gains in forest carbon at a regional to national level. The production of such maps across wide areas will become increasingly necessary as international efforts to protect primary forests, such as the REDD+ (Reducing Emissions from Deforestation and forest Degradation) mechanism, come into effect, alongside their use for management and research more generally. However, mapping biomass over high-biomass tropical forest is challenging as (1) direct regressions with optical and radar data saturate, (2) much of the tropics is persistently cloud-covered, reducing the availability of optical data, (3) many regions include steep topography, making the use of radar data complex, (5) while LiDAR data does not suffer from saturation, expensive aircraft-derived data are necessary for complete coverage. We present a solution to the problems, using a combination of terrain-corrected L-band radar data (ALOS PALSAR), spaceborne LiDAR data (ICESat GLAS) and ground-based data. We map Gabon's Lopé National Park (5000 km2) because it includes a range of vegetation types from savanna to closed-canopy tropical forest, is topographically complex, has no recent contiguous cloud-free high-resolution optical data, and the dense forest is above the saturation point for radar. Our 100 m resolution biomass map is derived from fusing spaceborne LiDAR (7142 ICESat GLAS footprints), 96 ground-based plots (average size 0.8 ha) and an unsupervised classification of terrain-corrected ALOS PALSAR radar data, from which we derive the aboveground biomass stocks of the park to be 78 Tg C (173 Mg C ha-1). This value is consistent with our field data average of 181 Mg C ha-1, from the field plots measured in 2009 covering a total of 78 ha, and which are independent as they were not used for the GLAS-biomass estimation. We estimate an uncertainty of ±25% on our carbon stock value for the park. This error term

  12. Implementation of random forest algorithm for crop mapping across an aridic to ustic area of Indian states

    Science.gov (United States)

    Shukla, Gaurav; Garg, Rahul Dev; Srivastava, Hari Shanker; Garg, Pradeep Kumar

    2017-04-01

    The purpose of this study is to effectively implement random forest algorithm for crop classification of large areas and to check the classification capability of different variables. To incorporate dependency of crops in different variables namely, texture, phenological, parent material and soil, soil moisture, topographic, vegetation, and climate, 35 digital layers are prepared using different satellite data (ALOS DEM, Landsat-8, MODIS NDVI, RISAT-1, and Sentinel-1A) and climatic data (precipitation and temperature). The importance of variables is also calculated based on mean decrease in accuracy and mean decrease in Gini score. Importance and capabilities of variables for crop mapping have been discussed. Variables associated with spectral responses have shown greater importance in comparison to topographic and climate variables. The spectral range (0.85 to 0.88 μm) of the near-infrared band is the most useful variable with the highest scores. The topographic variable and elevation have secured the second place rank in the both scores. This indicates the importance of spectral responses as well as of topography in model development. Climate variables have not shown as much importance as others, but in association with others, they cause a decrease in the out of bag (OOB) error rate. In addition to the OOB data, a 20% independent dataset of training samples is used to evaluate RF model. Results show that RF has good capability for crop classification.

  13. Interpreting participatory Fuzzy Cognitive Maps as complex networks in the social-ecological systems of the Amazonian forests

    Science.gov (United States)

    Varela, Consuelo; Tarquis, Ana M.; Blanco-Gutiérrez, Irene; Estebe, Paloma; Toledo, Marisol; Martorano, Lucieta

    2015-04-01

    Social-ecological systems are linked complex systems that represent interconnected human and biophysical processes evolving and adapting across temporal and spatial scales. In the real world, social-ecological systems pose substantial challenges for modeling. In this regard, Fuzzy Cognitive Maps (FCMs) have proven to be a useful method for capturing the functioning of this type of systems. FCMs are a semi-quantitative type of cognitive map that represent a system composed of relevant factors and weighted links showing the strength and direction of cause-effects relationships among factors. Therefore, FCMs can be interpreted as complex system structures or complex networks. In this sense, recent research has applied complex network concepts for the analysis of FCMs that represent social-ecological systems. Key to FCM the tool is its potential to allow feedback loops and to include stakeholder knowledge in the construction of the tool. Also, previous research has demonstrated their potential to represent system dynamics and simulate the effects of changes in the system, such as policy interventions. For illustrating this analysis, we have developed a series of participatory FCM for the study of the ecological and human systems related to biodiversity conservation in two case studies of the Amazonian region, the Bolivia lowlands of Guarayos and the Brazil Tapajos National forest. The research is carried out in the context of the EU project ROBIN1 and it is based on the development of a series of stakeholder workshops to analyze the current state of the socio-ecological environment in the Amazonian forest, reflecting conflicts and challenges for biodiversity conservation and human development. Stakeholders included all relevant actors in the local case studies, namely farmers, environmental groups, producer organizations, local and provincial authorities and scientists. In both case studies we illustrate the use of complex networks concepts, such as the adjacency

  14. Mapping aboveground biomass by integrating geospatial and forest inventory data through a k-nearest neighbor strategy in North Central Mexico

    Institute of Scientific and Technical Information of China (English)

    Carlos A AGUIRRE-SALADO; Liliana MIRANDA-ARAGÓN; Eduardo J TREVIÑO-GARZA; Oscar A AGUIRRE-CALDERÓN; Javier JIMÉNEZ-PÉREZ; Marco A GONZÁLEZ-TAGLE; José R VALDÉZ-LAZALDE; Guillermo SÁNCHEZ-DÍAZ; Reija HAAPANEN; Alejandro I AGUIRRE-SALADO

    2014-01-01

    As climate change negotiations progress, monitoring biomass and carbon stocks is becoming an im-portant part of the current forest research. Therefore, national governments are interested in developing for-est-monitoring strategies using geospatial technology. Among statistical methods for mapping biomass, there is a nonparametric approach called k-nearest neighbor (kNN). We compared four variations of distance metrics of the kNN for the spatially-explicit estimation of aboveground biomass in a portion of the Mexican north border of the intertropical zone. Satellite derived, climatic, and topographic predictor variables were combined with the Mexican National Forest Inventory (NFI) data to accomplish the purpose. Performance of distance metrics applied into the kNN algorithm was evaluated using a cross validation leave-one-out technique. The results indicate that the Most Similar Neighbor (MSN) approach maximizes the correlation between predictor and response variables (r=0.9). Our results are in agreement with those reported in the literature. These findings confirm the predictive potential of the MSN approach for mapping forest variables at pixel level under the policy of Reducing Emission from Deforestation and Forest Degradation (REDD+).

  15. Surface analysis and mechanical behaviour mapping of vertically aligned CNT forest array through nanoindentation

    Science.gov (United States)

    Koumoulos, Elias P.; Charitidis, C. A.

    2017-02-01

    Carbon nanotube (CNT) based architectures have increased the scientific interest owning to their exceptional performance rendering them promising candidates for advanced industrial applications in the nanotechnology field. Despite individual CNTs being considered as one of the most known strong materials, much less is known about other CNT forms, such as CNT arrays, in terms of their mechanical performance (integrity). In this work, thermal chemical vapor deposition (CVD) method is employed to produce vertically aligned multiwall (VA-MW) CNT carpets. Their structural properties were studied by means of scanning electron microscopy (SEM), X-Ray diffraction (XRD) and Raman spectroscopy, while their hydrophobic behavior was investigated via contact angle measurements. The resistance to indentation deformation of VA-MWCNT carpets was investigated through nanoindentation technique. The synthesized VA-MWCNTs carpets consisted of well-aligned MWCNTs. Static contact angle measurements were performed with water and glycerol, revealing a rather super-hydrophobic behavior. The structural analysis, hydrophobic behavior and indentation response of VA-MWCNTs carpets synthesized via CVD method are clearly demonstrated. Additionally, cycle indentation load-depth curve was applied and hysteresis loops were observed in the indenter loading-unloading cycle due to the local stress distribution. Hardness (as resistance to applied load) and modulus mapping, at 200 nm of displacement for a grid of 70 μm2 is presented. Through trajection, the resistance is clearly divided in 2 regions, namely the MWCNT probing and the in-between area MWCNT - MWCNT interface.

  16. Mapping resource use over a Russian landscape: an integrated look at harvesting of a non-timber forest product in central Kamchatka

    Science.gov (United States)

    Hitztaler, Stephanie K.; Bergen, Kathleen M.

    2013-12-01

    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.

  17. MAPPING AND CHANGE ANALYSIS IN MANGROVE FOREST BY USING LANDSAT IMAGERY

    Directory of Open Access Journals (Sweden)

    T. T. Dan

    2016-06-01

    Full Text Available Mangrove is located in the tropical and subtropical regions and brings good services for native people. Mangrove in the world has been lost with a rapid rate. Therefore, monitoring a spatiotemporal distribution of mangrove is thus critical for natural resource management. This research objectives were: (i to map the current extent of mangrove in the West and Central Africa and in the Sundarbans delta, and (ii to identify change of mangrove using Landsat data. The data were processed through four main steps: (1 data pre-processing including atmospheric correction and image normalization, (2 image classification using supervised classification approach, (3 accuracy assessment for the classification results, and (4 change detection analysis. Validation was made by comparing the classification results with the ground reference data, which yielded satisfactory agreement with overall accuracy 84.1% and Kappa coefficient of 0.74 in the West and Central Africa and 83.0% and 0.73 in the Sundarbans, respectively. The result shows that mangrove areas have changed significantly. In the West and Central Africa, mangrove loss from 1988 to 2014 was approximately 16.9%, and only 2.5% was recovered or newly planted at the same time, while the overall change of mangrove in the Sundarbans increased approximately by 900 km2 of total mangrove area. Mangrove declined due to deforestation, natural catastrophes deforestation and mangrove rehabilitation programs. The overall efforts in this study demonstrated the effectiveness of the proposed method used for investigating spatiotemporal changes of mangrove and the results could provide planners with invaluable quantitative information for sustainable management of mangrove ecosystems in these regions.

  18. Mapping and Change Analysis in Mangrove Forest by Using Landsat Imagery

    Science.gov (United States)

    Dan, T. T.; Chen, C. F.; Chiang, S. H.; Ogawa, S.

    2016-06-01

    Mangrove is located in the tropical and subtropical regions and brings good services for native people. Mangrove in the world has been lost with a rapid rate. Therefore, monitoring a spatiotemporal distribution of mangrove is thus critical for natural resource management. This research objectives were: (i) to map the current extent of mangrove in the West and Central Africa and in the Sundarbans delta, and (ii) to identify change of mangrove using Landsat data. The data were processed through four main steps: (1) data pre-processing including atmospheric correction and image normalization, (2) image classification using supervised classification approach, (3) accuracy assessment for the classification results, and (4) change detection analysis. Validation was made by comparing the classification results with the ground reference data, which yielded satisfactory agreement with overall accuracy 84.1% and Kappa coefficient of 0.74 in the West and Central Africa and 83.0% and 0.73 in the Sundarbans, respectively. The result shows that mangrove areas have changed significantly. In the West and Central Africa, mangrove loss from 1988 to 2014 was approximately 16.9%, and only 2.5% was recovered or newly planted at the same time, while the overall change of mangrove in the Sundarbans increased approximately by 900 km2 of total mangrove area. Mangrove declined due to deforestation, natural catastrophes deforestation and mangrove rehabilitation programs. The overall efforts in this study demonstrated the effectiveness of the proposed method used for investigating spatiotemporal changes of mangrove and the results could provide planners with invaluable quantitative information for sustainable management of mangrove ecosystems in these regions.

  19. Field strategies for the calibration and validation of high-resolution forest carbon maps: Scaling from plots to a three state region MD, DE, & PA, USA.

    Science.gov (United States)

    Dolan, K. A.; Huang, W.; Johnson, K. D.; Birdsey, R.; Finley, A. O.; Dubayah, R.; Hurtt, G. C.

    2016-12-01

    In 2010 Congress directed NASA to initiate research towards the development of Carbon Monitoring Systems (CMS). In response, our team has worked to develop a robust, replicable framework to quantify and map aboveground forest biomass at high spatial resolutions. Crucial to this framework has been the collection of field-based estimates of aboveground tree biomass, combined with remotely detected canopy and structural attributes, for calibration and validation. Here we evaluate the field- based calibration and validation strategies within this carbon monitoring framework and discuss the implications on local to national monitoring systems. Through project development, the domain of this research has expanded from two counties in MD (2,181 km2), to the entire state of MD (32,133 km2), and most recently the tri-state region of MD, PA, and DE (157,868 km2) and covers forests in four major USDA ecological providences. While there are approximately 1000 Forest Inventory and Analysis (FIA) plots distributed across the state of MD, 60% fell in areas considered non-forest or had conditions that precluded them from being measured in the last forest inventory. Across the two pilot counties, where population and landuse competition is high, that proportion rose to 70% Thus, during the initial phases of this project 850 independent field plots were established for model calibration following a random stratified design to insure the adequate representation of height and vegetation classes found across the state, while FIA data were used as an independent data source for validation. As the project expanded to cover the larger spatial tri-state domain, the strategy was flipped to base calibration on more than 3,300 measured FIA plots, as they provide a standardized, consistent and available data source across the nation. An additional 350 stratified random plots were deployed in the Northern Mixed forests of PA and the Coastal Plains forests of DE for validation.

  20. The influence of early sexual debut and pubertal timing on psychological distress among Taiwanese adolescents.

    Science.gov (United States)

    Chiao, Chi; Ksobiech, Kate

    2015-01-01

    This study examined the relative influence of early sexual debut (ESD) and pubertal timing on psychological distress from adolescence to young adulthood in Taiwan, a non-Western society with a distinct cultural and family context. Data were from a cohort sample of 15-year-olds (N = 2595) first interviewed in 2000, with four follow-ups during a 7-year period. Psychological distress was assessed by a reduced form of the Symptom Checklist-90 Revised. ESD was defined by first intercourse at age 15 or younger. Multivariate analyses via growth curve modeling found a greater increase in psychological distress over time in adolescents with ESD (β = .28, p influence of both ESD and pubertal timing on distress trajectories, independent of parental and family characteristics.

  1. Revisiting a universal airborne light detection and ranging approach for tropical forest carbon mapping: scaling-up from tree to stand to landscape.

    Science.gov (United States)

    Vincent, Grégoire; Sabatier, Daniel; Rutishauser, Ervan

    2014-06-01

    Airborne laser scanning provides continuous coverage mapping of forest canopy height and thereby is a powerful tool to scale-up above-ground biomass (AGB) estimates from stand to landscape. A critical first step is the selection of the plot variables which can be related to light detection and ranging (LiDAR) statistics. A universal approach was previously proposed which combines local and regional estimates of basal area (BA) and wood density with LiDAR-derived canopy height to map carbon at a regional scale (Asner et al. in Oecologia 168:1147-1160, 2012). Here we explore the contribution of stem diameter distribution, specific wood density and height-diameter (H-D) allometry to forest stand AGB and propose an alternative model. By applying the new model to a large tropical forest data set we show that an appropriate choice of input variables is essential to minimize prediction error of stand AGB which will propagate at larger scale. Stem number (N) and average stem cross-sectional area should be used instead of BA when scaling from tree to plot. Stand quadratic mean diameter above the census threshold diameter size should be preferred over stand mean diameter as it reduces the prediction error of stand AGB by a factor of ten. Wood density should be weighted by stem volume per species instead of BA. LiDAR-derived statistics should prove useful for estimating local H-D allometries as well as mapping N and the mean quadratic diameter above 10 cm at the landscape level. Prior stratification into forest types is likely to improve both estimation procedures significantly and is considered the foremost current challenge.

  2. Using interpreted large scale aerial photo data to enhance satellite-based mapping and explore forest land definitions

    Science.gov (United States)

    Tracey S. Frescino; Gretchen G. Moisen

    2009-01-01

    The Interior-West, Forest Inventory and Analysis (FIA), Nevada Photo-Based Inventory Pilot (NPIP), launched in 2004, involved acquisition, processing, and interpretation of large scale aerial photographs on a subset of FIA plots (both forest and nonforest) throughout the state of Nevada. Two objectives of the pilot were to use the interpreted photo data to enhance...

  3. 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.

  4. Lyman-alpha Forest Tomography from Background Galaxies: The First Megaparsec-Resolution Large-Scale Structure Map at z>2

    CERN Document Server

    Lee, Khee-Gan; Stark, Casey; Prochaska, J Xavier; White, Martin; Schlegel, David J; Eilers, Anna-Christina; Arinyo-i-Prats, Andreu; Suzuki, Nao; Croft, Rupert A C; Caputi, Karina I; Cassata, Paolo; Ilbert, Olivier; Garilli, Bianca; Koekemoer, Anton M; Brun, Vincent Le; Fèvre, Olivier Le; Maccagni, Dario; Nugent, Peter; Taniguchi, Yoshiaki; Tasca, Lidia A M; Tresse, Laurence; Zamorani, Gianni; Zucca, Elena

    2014-01-01

    We present the first observations of foreground Lyman-$\\alpha$ forest absorption from high-redshift galaxies, targeting 24 star-forming galaxies (SFGs) with $z\\sim 2.3-2.8$ within a $5' \\times 15'$ region of the COSMOS field. The transverse sightline separation is $\\sim 2\\,h^{-1}\\mathrm{Mpc}$ comoving, allowing us to create a tomographic reconstruction of the 3D Ly$\\alpha$ forest absorption field over the redshift range $2.20\\leq z\\leq 2.45$. The resulting map covers $6\\,h^{-1}\\mathrm{Mpc} \\times 14\\,h^{-1}\\mathrm{Mpc}$ in the transverse plane and $230\\,h^{-1}\\mathrm{Mpc}$ along the line-of-sight with a spatial resolution of $\\approx 3.5\\,h^{-1}\\mathrm{Mpc}$, and is the first high-fidelity map of large-scale structure on $\\sim\\mathrm{Mpc}$ scales at $z>2$. Our map reveals significant structures with $\\gtrsim 10\\,h^{-1}\\mathrm{Mpc}$ extent, including several spanning the entire transverse breadth, providing qualitative evidence for the filamentary structures predicted to exist in the high-redshift cosmic web. ...

  5. Are female orphans at risk for early marriage, early sexual debut, and teen pregnancy? Evidence from sub-Saharan Africa.

    Science.gov (United States)

    Palermo, Tia; Peterman, Amber

    2009-06-01

    Female orphans are widely cited as being at risk for early marriage, early childbearing, and risky sexual behavior; however, to date no studies have examined these linkages using population-level data across multiple countries. This study draws from recent Demographic and Health Surveys from ten sub-Saharan African countries to examine the relationship between orphanhood status and measures of early marriage, early sexual debut, and teen pregnancy among adolescent girls aged 15 to 17. Results indicate that, overall, little association is found between orphanhood and early marriage or teen pregnancy, whereas evidence from seven countries supports associations between orphanhood and early sexual debut. Findings are sensitive to the use of multivariate models, type of orphan, and country setting. Orphanhood status alone may not be a sufficient targeting mechanism for addressing these outcomes in many countries; a broader, multidimensional targeting scheme including orphan type, schooling, and poverty measures would be more robust in identifying and aiding young women at risk.

  6. 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

  7. 森林资源二类调查中MapInfo应用技巧探讨%The Application Skills of MapInfo in Forest Inventory of Management Plan

    Institute of Scientific and Technical Information of China (English)

    刘建国; 柯善新

    2011-01-01

    MapInfo是一款著名的地理信息管理桌面系统,具有小巧灵活、使用简单、功能强大、价格适中的特点,非常适合森林资源二类调查中使用;通过合理定制工作流程、快捷键定义、快速配准、建立小班图层、MapBasic编程等技巧的应用,更能得心应手、简捷有效地处理小班信息。%MapInfo is a leading desktop system software of geographic information management with many advantages,such as small and flexible,simple and practical,powerful function,appropriate price.MapInfo is a ideal software for forest inventory of management plan,it is favorable and simple to deal effectively subcompartment information by designing reasonable workflows,defining shortcut keys,matching images shortly,establishing image layers of subcompartment,applying MapBasic programming skills.

  8. Generating an optimal DTM from airborne laser scanning data for landslide mapping in a tropical forest environment

    NARCIS (Netherlands)

    Razak, Khamarrul Azahari; Santangelo, Michele; Westen, van Cees J.; Straatsma, Menno W.; Jong, de Steven M.

    2013-01-01

    Landslide inventory maps are fundamental for assessing landslide susceptibility, hazard, and risk. In tropical mountainous environments, mapping landslides is difficult as rapid and dense vegetation growth obscures landslides soon after their occurrence. Airborne laser scanning (ALS) data have been

  9. Mapping canopy gaps in an indigenous subtropical coastal forest using high resolution WorldView-2 data

    CSIR Research Space (South Africa)

    Malahlela, O

    2014-01-01

    Full Text Available Invasive species usually colonize canopy gaps in tropical and sub-tropical forests, which results in loss of native species. Therefore, an understanding of the location and distribution of canopy gaps will assist in predicting the occurrence...

  10. Mapping Webs of Information, Conversation, and Social Connections: Evaluating the Mechanics of Collaborative Adaptive Management in the Sierra Nevada Forests

    OpenAIRE

    2014-01-01

    Managing within social-ecological systems at the landscape scale, such as in the national forests of the Sierra Nevada of California, is challenging to natural resource managers (e.g. the U.S. Forest Service) due to the uncertainties in natural processes and the complexities in social dynamics. Collaborative adaptive management (CAM) has been recently adopted as a viable strategy to diminish uncertainties in natural processes through iterative policy experimentations and adaptations, as well ...

  11. Mapping Robinia Pseudoacacia Forest Health Conditions by Using Combined Spectral, Spatial, and Textural Information Extracted from IKONOS Imagery and Random Forest Classifier

    Directory of Open Access Journals (Sweden)

    Hong Wang

    2015-07-01

    Full Text Available The textural and spatial information extracted from very high resolution (VHR remote sensing imagery provides complementary information for applications in which the spectral information is not sufficient for identification of spectrally similar landscape features. In this study grey-level co-occurrence matrix (GLCM textures and a local statistical analysis Getis statistic (Gi, computed from IKONOS multispectral (MS imagery acquired from the Yellow River Delta in China, along with a random forest (RF classifier, were used to discriminate Robina pseudoacacia tree health levels. Specifically, eight GLCM texture features (mean, variance, homogeneity, dissimilarity, contrast, entropy, angular second moment, and correlation were first calculated from IKONOS NIR band (Band 4 to determine an optimal window size (13 × 13 and an optimal direction (45°. Then, the optimal window size and direction were applied to the three other IKONOS MS bands (blue, green, and red for calculating the eight GLCM textures. Next, an optimal distance value (5 and an optimal neighborhood rule (Queen’s case were determined for calculating the four Gi features from the four IKONOS MS bands. Finally, different RF classification results of the three forest health conditions were created: (1 an overall accuracy (OA of 79.5% produced using the four MS band reflectances only; (2 an OA of 97.1% created with the eight GLCM features calculated from IKONOS Band 4 with the optimal window size of 13 × 13 and direction 45°; (3 an OA of 93.3% created with the all 32 GLCM features calculated from the four IKONOS MS bands with a window size of 13 × 13 and direction of 45°; (4 an OA of 94.0% created using the four Gi features calculated from the four IKONOS MS bands with the optimal distance value of 5 and Queen’s neighborhood rule; and (5 an OA of 96.9% created with the combined 16 spectral (four, spatial (four, and textural (eight features. The most important feature ranked by RF

  12. GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran.

    Science.gov (United States)

    Naghibi, Seyed Amir; Pourghasemi, Hamid Reza; Dixon, Barnali

    2016-01-01

    Groundwater is considered one of the most valuable fresh water resources. The main objective of this study was to produce groundwater spring potential maps in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran, using three machine learning models: boosted regression tree (BRT), classification and regression tree (CART), and random forest (RF). Thirteen hydrological-geological-physiographical (HGP) factors that influence locations of springs were considered in this research. These factors include slope degree, slope aspect, altitude, topographic wetness index (TWI), slope length (LS), plan curvature, profile curvature, distance to rivers, distance to faults, lithology, land use, drainage density, and fault density. Subsequently, groundwater spring potential was modeled and mapped using CART, RF, and BRT algorithms. The predicted results from the three models were validated using the receiver operating characteristics curve (ROC). From 864 springs identified, 605 (≈70 %) locations were used for the spring potential mapping, while the remaining 259 (≈30 %) springs were used for the model validation. The area under the curve (AUC) for the BRT model was calculated as 0.8103 and for CART and RF the AUC were 0.7870 and 0.7119, respectively. Therefore, it was concluded that the BRT model produced the best prediction results while predicting locations of springs followed by CART and RF models, respectively. Geospatially integrated BRT, CART, and RF methods proved to be useful in generating the spring potential map (SPM) with reasonable accuracy.

  13. 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.

  14. 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.

  15. 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, T.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

  16. 基于NewMap Server的森林防火应急指挥系统设计与实现%The Design and Implementation of an Emergency Command Forest Fire Prevention Systems Based on NewMap Server

    Institute of Scientific and Technical Information of China (English)

    朱琳; 禄丰年; 张蓓蓓; 张娜

    2012-01-01

    综合运用3S技术,以NewMap Server为地理信息系统开发平台,建立森林防火应急指挥系统,具体介绍了系统设计思想,系统结构和系统开发.并结合济源市森林防火应急指挥系统实例,介绍了预报监测、辅助决策、、扑救指挥和灾后评估等系统功能.%Comprehensively using 3S technique, this paper established the emergency command forest fire prevention system, with the NewMap server as geographic information system development platform, which includes the system designing thought, system structure and system development. And combined with the emergency command forest fire prevention system of Jiyuan city as an example, this paper introduces the forecast monitoring, decision support, incident command and disaster assessment system function.

  17. Mapping forest habitats in protected areas by integrating LiDAR and SPOT Multispectral Data

    OpenAIRE

    Alvarez, Manuela

    2016-01-01

    KNAS (Continuous Habitat Mapping of Protected Areas) is a Metria AB project that produces vegetation and habitat mapping in protected areas in Sweden. Vegetation and habitat mapping is challenging due to its heterogeneity, spatial variability and complex vertical and horizontal structure. Traditionally, multispectral data is used due to its ability to give information about horizontal structure of vegetation. LiDAR data contains information about vertical structure of vegetation, and therefor...

  18. 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.

  19. 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%.

  20. Towards an improved Land Surface Phenology mapping using a new MODIS product: A case study of Bavarian Forest National Park

    Science.gov (United States)

    Misra, Gourav; Buras, Allan; Asam, Sarah; Menzel, Annette

    2017-04-01

    Past work in remote sensing of land surface phenology have mapped vegetation cycles at multiple scales. Much has been discussed and debated about the uncertainties associated with the selection of data, data processing and the eventual conclusions drawn. Several studies do however provide evidence of strong links between different land surface phenology (LSP) metrics with specific ground phenology (GP) (Fisher and Mustard, 2007; Misra et al., 2016). Most importantly the use of high temporal and spatial resolution remote sensing data and ground truth information is critical for such studies. In this study, we use a higher temporal resolution 4 day MODIS NDVI product developed by EURAC (Asam et al., in prep) for the Bavarian Forest National Park during 2002-2015 period and extract various phenological metrics covering different phenophases of vegetation (start of season / sos and end of season / eos). We found the LSP-sos to be more strongly linked to the elevation of the area than LSP-eos which has been cited to be harder to detect (Stöckli et al., 2008). The LSP metrics were also correlated to GP information at 4 different stations covering elevations ranging from approx. 500 to 1500 metres. Results show that among the five dominant species in the area i.e. European ash, Norway spruce, European beech, Norway maple and orchard grass, only particular GP observations for some species show stronger correlations with LSP than others. Spatial variations in the LSP-GP correlations were also observed, with certain areas of the National Park showing positive correlations and others negative. An analysis of temporal trends of LSP also indicates the possibility to detect those areas in the National Park that were affected by extreme events. Further investigations are planned to explain the heterogeneity in the derived LSP metrics using high resolution ground truth data and multivariate statistical analyses. Acknowledgement: This research received funding from the Bavarian

  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

    2015-08-01

    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.

  2. 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

  3. An Automatic Mosaicking Algorithm for the Generation of a Large-Scale Forest Height Map Using Spaceborne Repeat-Pass InSAR Correlation Magnitude

    Directory of Open Access Journals (Sweden)

    Yang Lei

    2015-05-01

    Full Text Available This paper describes an automatic mosaicking algorithm for creating large-scale mosaic maps of forest height. In contrast to existing mosaicking approaches through using SAR backscatter power and/or InSAR phase, this paper utilizes the forest height estimates that are inverted from spaceborne repeat-pass cross-pol InSAR correlation magnitude. By using repeat-pass InSAR correlation measurements that are dominated by temporal decorrelation, it has been shown that a simplified inversion approach can be utilized to create a height-sensitive measure over the whole interferometric scene, where two scene-wide fitting parameters are able to characterize the mean behavior of the random motion and dielectric changes of the volume scatterers within the scene. In order to combine these single-scene results into a mosaic, a matrix formulation is used with nonlinear least squares and observations in adjacent-scene overlap areas to create a self-consistent estimate of forest height over the larger region. This automated mosaicking method has the benefit of suppressing the global fitting error and, thus, mitigating the “wallpapering” problem in the manual mosaicking process. The algorithm is validated over the U.S. state of Maine by using InSAR correlation magnitude data from ALOS/PALSAR and comparing the inverted forest height with Laser Vegetation Imaging Sensor (LVIS height and National Biomass and Carbon Dataset (NBCD basal area weighted (BAW height. This paper serves as a companion work to previously demonstrated results, the combination of which is meant to be an observational prototype for NASA’s DESDynI-R (now called NISAR and JAXA’s ALOS-2 satellite missions.

  4. 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

  5. US Forest Service Special Interest Management Areas

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www that depicts National Forest System land parcels that have management or use limits placed on them by the Forest Service. Examples include:...

  6. 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

    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...... experiments, the disaggregation provided a good prediction of the soil types, despite the coarse scale of the input maps....

  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. Variables psicosociales que median en el debut sexual de adolescentes en España

    Directory of Open Access Journals (Sweden)

    Ángel Castro

    2011-01-01

    Full Text Available El objetivo de esta investigación es analizar las variables sociodemográficas y psicosociales que median en el debut sexual de los adolescentes en España. Participaron 2.153 adolescentes residentes en España, entre 14 y 19 años de edad, y de distinto origen cultural. De ellos, el 67.7% eran autóctonos españoles y el 32.3% inmigrantes latinoamericanos. El 19.2% de los participantes no había tenido contacto sexual, el 47.3% lo había tenido sin penetración y el 33.5% restante manifestó haber tenido relaciones sexuales con penetración. Se llevó a cabo una regresión logística multinomial para comparar a los adolescentes de los tres grupos, a través de la cual se concluye que las relaciones sexuales sin penetración pueden ser predichas por las actitudes positivas hacia el preservativo y que las relaciones sexuales con penetración pueden serlo por la adaptación personal, la adaptación escolar y las actitudes positivas hacia el preservativo. Posteriormente, a través de un análisis de regresión logística binaria, se obtuvo que los adolescentes latinoamericanos, las mujeres, los que están más adaptados en el ámbito personal y los que presentan menos autoeficacia en el uso del preservativo tienen más probabilidades de tener relaciones sexuales con penetración. En la discusión se resalta la importancia de la edad de inicio en las relaciones sexuales como factor clave para la emisión de conductas sexuales de riesgo.

  9. Mapping Robinia Pseudoacacia Forest Health Conditions by Using Combined Spectral, Spatial and Textureal Information Extracted from Ikonos Imagery

    Science.gov (United States)

    Wang, H.; Zhao, Y.; Pu, R.; Zhang, Z.

    2016-10-01

    In this study grey-level co-occurrence matrix (GLCM) textures and a local statistical analysis Getis statistic (Gi), computed from IKONOS multispectral (MS) imagery acquired from the Yellow River Delta in China, along with a random forest (RF) classifier, were used to discriminate Robina pseudoacacia tree health levels. The different RF classification results of the three forest health conditions were created: (1) an overall accuracy (OA) of 79.5% produced using the four MS band reflectances only; (2) an OA of 97.1% created with the eight GLCM features calculated from IKONOS Band 4 with the optimal window size of 13 × 13 and direction 45°; (3) an OA of 94.0% created using the four Gi features calculated from the four IKONOS MS bands with the optimal distance value of 5 and Queen's neighborhood rule; and (4) an OA of 96.9% created with the combined 16 spectral (four), spatial (four), and textural (eight) features. The experimental results demonstrate that (a) both textural and spatial information was more useful than spectral information in determining the Robina pseudoacacia forest health conditions; and (b) IKONOS NIR band was more powerful than visible bands in quantifying varying degree of forest crown dieback.

  10. Insight into the Genetic Components of Community Genetics: QTL Mapping of Insect Association in a Fast-Growing Forest Tree

    NARCIS (Netherlands)

    DeWoody, J.; Viger, M.; Lakatos, F.; Tuba, K.; Taylor, G.; Smulders, M.J.M.

    2013-01-01

    Identifying genetic sequences underlying insect associations on forest trees will improve the understanding of community genetics on a broad scale. We tested for genomic regions associated with insects in hybrid poplar using quantitative trait loci (QTL) analyses conducted on data from a common gard

  11. Tropical forest mapping at regional scale using the GRFM SAR mosaics over the Amazon in South America

    NARCIS (Netherlands)

    Sgrenzaroli, M.

    2004-01-01

    The work described in this thesis concerns the estimation of tropical forest vegetation cover in the Amazon region using as data source a continental scale high resolution (100 m) radar mosaic as data source. The radar mosaic was compiled by the Jet Propulsion Laboratory (NASA JPL) using approximate

  12. Mapping Above-Ground Biomass in a Tropical Forest in Cambodia Using Canopy Textures Derived from Google Earth

    Directory of Open Access Journals (Sweden)

    Minerva Singh

    2015-04-01

    Full Text Available This study develops a modelling framework for utilizing very high-resolution (VHR aerial imagery for monitoring stocks of above-ground biomass (AGB in a tropical forest in Southeast Asia. Three different texture-based methods (grey level co-occurrence metric (GLCM, Gabor wavelets and Fourier-based textural ordination (FOTO were used in conjunction with two different machine learning (ML-based regression techniques (support vector regression (SVR and random forest (RF regression. These methods were implemented on both 50-cm resolution Digital Globe data extracted from Google Earth™ (GE and 8-cm commercially obtained VHR imagery. This study further examines the role of forest biophysical parameters, such as ground-measured canopy cover and vertical canopy height, in explaining AGB distribution. Three models were developed using: (i horizontal canopy variables (i.e., canopy cover and texture variables plus vertical canopy height; (ii horizontal variables only; and (iii texture variables only. AGB was variable across the site, ranging from 51.02 Mg/ha to 356.34 Mg/ha. GE-based AGB estimates were comparable to those derived from commercial aerial imagery. The findings demonstrate that novel use of this array of texture-based techniques with GE imagery can help promote the wider use of freely available imagery for low-cost, fine-resolution monitoring of forests parameters at the landscape scale.

  13. Insight into the Genetic Components of Community Genetics: QTL Mapping of Insect Association in a Fast-Growing Forest Tree

    NARCIS (Netherlands)

    DeWoody, J.; Viger, M.; Lakatos, F.; Tuba, K.; Taylor, G.; Smulders, M.J.M.

    2013-01-01

    Identifying genetic sequences underlying insect associations on forest trees will improve the understanding of community genetics on a broad scale. We tested for genomic regions associated with insects in hybrid poplar using quantitative trait loci (QTL) analyses conducted on data from a common gard

  14. Modelagem numérica em mapa temático: sítios florestais Numerical modelling in thematical map: forestal sites

    Directory of Open Access Journals (Sweden)

    Cláudia Weber Corseuil

    1998-12-01

    Full Text Available O presente trabalho tem por objetivo a utilização de programas de geoprocessamento e de tratamento de imagens, considerados de domínio público e de fácil operacionalidade, para modelagem numérica de um mapa temático. Esta modelagem é feita a partir da alimentação de um banco de dados digitais, para fins de planejamento e cadastro florestal. Mais especificamente, criou-se uma metodologia que utiliza a modelagem numérica para a visualização tridimensional de um plano de informação de sítios florestais georeferenciados, que permite o cruzamento (sobreposição com outros planos de informações, também georeferenciados, de interesse na área florestal. Foram utilizados os seguintes materiais: mapa de sítios naturais da Floresta Nacional de Passo Fundo, microcomputador, impressora, scanner de mesa, os softwares Idrisi 4.1 e Aldus PhotoStyler 2.0. A metodologia empregada baseou-se na digitalização, por varredura ótica, do mapa de sítios naturais existentes, sua edição de cores e georeferenciamento, para posterior modelagem numérica e visualização tridimensional dos diferentes sítios representados no mapa planimétrico da Floresta Nacional de Passo Fundo. Como resultado, obteve-se arquivos, que possibilitaram a identificação, através das diferentes alturas, dos sítios onde podem ser implantadas espécies mais adequadas às suas características naturais, demonstrando a viabilidade da aplicação da presente metodologia no planejamento florestal.The objective of this work was to utilize programs of geoprocessing and treatment of images, considerated to be well-knowm and easily operated, for numerical modelling of a thematical map. This modelling is carried out from feeding a digital base bank, for forest planning and cadaster. More specifically, a methodology that uses the numerical modelling for tridimensional visualization of a layer of geoindicated forest sites has been designed to permit the crossing (superposition

  15. US Forest Service National Wilderness Areas

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting parcels of Forest Service land congressionally designated as wilderness such as National Wilderness Areas. This map service...

  16. US Forest Service Land Status and Encumbrance

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service designed to portray US Forest Service Land Status Record System data. The map service is for querying and displaying Land Status Record System...

  17. US Forest Service Wilderness Areas: Legal Status

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting status of parcels for Forest Service land congressionally designated as wilderness such as National Wilderness Areas. This map...

  18. US Forest Service National Forest System Trails With Data Status

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the world wide web that depicts National Forest Service trails that have been approved for publication. It also depicts the availability of trails...

  19. US Forest Service Forest Carbon Stocks Contiguous United States

    Data.gov (United States)

    US Forest Service, Department of Agriculture — Through application of a nearest-neighbor imputation approach, mapped estimates of forest carbon density were developed for the contiguous United States using the...

  20. US Forest Service Collaborative Forest Landscape Restoration Program

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www that depicts Collaborative Forest Landscape Restoration (CFLR) and High Priority Restoration (HRP) project accomplishments. These are ten...

  1. A systematic review on identifying risk factors associated with early sexual debut and coerced sex among adolescents and young people in communities.

    Science.gov (United States)

    Lee, Regina Lai Tong; Yuen Loke, Alice; Hung, Tsz Man Tommy; Sobel, Howard

    2017-06-21

    To review literature on identifying the risk factors associated with early sexual coerced debut with the aim to facilitate the health care workers' planning of relevant health services to improve intervention strategies for delaying of early coerced sexual debut or forced sexual debut (CSD/FSD) in the communities. Identifying the risk factors associated with coercion at first sex is crucial for developing appropriate sexual and reproductive health information and health promotion in response. However, current knowledge about the risk factors associated with coercion, sexual debut (SD), and delayed SD among young people is limited. Health information programs are important during adolescence, when young people are developing their values and beliefs about sexual activity and sexual norms. However, little is known about those risk factors on initiation of early sexual debut in order to plan relevant interventions that can delay SD and prevent coerced sexual debut or forced sexual debut (CSD/FSD) in this population. A systematic review. An extensive literature search using Medline (PubMed), Nursing Journals (PubMed), Web of Science, PsychINFO and CINAHL. The search generated 39 published studies that met our inclusion and exclusion criteria. Thirty-two articles passed the quality appraisal and were selected. This review identified six domains of risk factors, categorized as: (1) the individual domain, (2) the family domain, (3) the partner/peer domain, (4) the school domain, (5) the community domain, and (6) the cultural domain. These factors highlight the influences on sexual decision-making among adolescents and young people and the timing of their first sexual intercourse. It is important to utilize the outcome of this review's categorization of identified risk factors to facilitate the health care workers and plan relevant sexual and reproductive health programs more accessible to adolescents, especially young females and their parents. There is a need to evaluate

  2. 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.

  3. US Forest Service Recreation Opportunities

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting the recreation opportunity information that the Forest Service collects through the Recreation Portal and shares with the public...

  4. US Forest Service Regional Boundaries

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting all the National Forest System lands administered by a Region. The area encompasses private lands, other governmental agency...

  5. The government of Kenya's cash transfer program reduces the risk of sexual debut among young people age 15-25.

    Science.gov (United States)

    Handa, Sudhanshu; Halpern, Carolyn Tucker; Pettifor, Audrey; Thirumurthy, Harsha

    2014-01-01

    The aim of this study is to assess whether the Government of Kenya's Cash Transfer for Orphans and Vulnerable Children (Kenya CT-OVC) can reduce the risk of HIV among young people by postponing sexual debut. The program provides an unconditional transfer of US$20 per month directly to the main caregiver in the household. An evaluation of the program was implemented in 2007-2009 in seven districts. Fourteen Locations were randomly assigned to receive the program and fourteen were assigned to a control arm. A sample of households was enrolled in the evaluation in 2007. We revisited these households in 2011 and collected information on sexual activity among individuals between 15-25 years of age. We used logistic regression, adjusted for the respondent's age, sex and relationship to caregiver, the age, sex and schooling of the caregiver and whether or not the household lived in Nairobi at baseline, to compare rates of sexual debut among young people living in program households with those living in control households who had not yet entered the program. Our results, adjusted for these covariates, show that the program reduced the odds of sexual debut by 31 percent. There were no statistically significant effects on secondary outcomes of behavioral risk such as condom use, number of partners and transactional sex. Since the CT-OVC provides cash to the caregiver and not to the child, and there are no explicit conditions associated with receipt, these impacts are indirect, and may have been achieved by keeping young people in school. Our results suggest that large-scale national social cash transfer programs with poverty alleviation objectives may have potential positive spillover benefits in terms of reducing HIV risk among young people in Eastern and Southern Africa.

  6. The government of Kenya's cash transfer program reduces the risk of sexual debut among young people age 15-25.

    Directory of Open Access Journals (Sweden)

    Sudhanshu Handa

    Full Text Available The aim of this study is to assess whether the Government of Kenya's Cash Transfer for Orphans and Vulnerable Children (Kenya CT-OVC can reduce the risk of HIV among young people by postponing sexual debut. The program provides an unconditional transfer of US$20 per month directly to the main caregiver in the household. An evaluation of the program was implemented in 2007-2009 in seven districts. Fourteen Locations were randomly assigned to receive the program and fourteen were assigned to a control arm. A sample of households was enrolled in the evaluation in 2007. We revisited these households in 2011 and collected information on sexual activity among individuals between 15-25 years of age. We used logistic regression, adjusted for the respondent's age, sex and relationship to caregiver, the age, sex and schooling of the caregiver and whether or not the household lived in Nairobi at baseline, to compare rates of sexual debut among young people living in program households with those living in control households who had not yet entered the program. Our results, adjusted for these covariates, show that the program reduced the odds of sexual debut by 31 percent. There were no statistically significant effects on secondary outcomes of behavioral risk such as condom use, number of partners and transactional sex. Since the CT-OVC provides cash to the caregiver and not to the child, and there are no explicit conditions associated with receipt, these impacts are indirect, and may have been achieved by keeping young people in school. Our results suggest that large-scale national social cash transfer programs with poverty alleviation objectives may have potential positive spillover benefits in terms of reducing HIV risk among young people in Eastern and Southern Africa.

  7. 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.

  8. Forest Disturbance Mapping Using Dense Synthetic Landsat/MODIS Time-Series and Permutation-Based Disturbance Index Detection

    Directory of Open Access Journals (Sweden)

    David Frantz

    2016-03-01

    Full Text Available Spatio-temporal information on process-based forest loss is essential for a wide range of applications. Despite remote sensing being the only feasible means of monitoring forest change at regional or greater scales, there is no retrospectively available remote sensor that meets the demand of monitoring forests with the required spatial detail and guaranteed high temporal frequency. As an alternative, we employed the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM to produce a dense synthetic time series by fusing Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS nadir Bidirectional Reflectance Distribution Function (BRDF adjusted reflectance. Forest loss was detected by applying a multi-temporal disturbance detection approach implementing a Disturbance Index-based detection strategy. The detection thresholds were permutated with random numbers for the normal distribution in order to generate a multi-dimensional threshold confidence area. As a result, a more robust parameterization and a spatially more coherent detection could be achieved. (i The original Landsat time series; (ii synthetic time series; and a (iii combined hybrid approach were used to identify the timing and extent of disturbances. The identified clearings in the Landsat detection were verified using an annual woodland clearing dataset from Queensland’s Statewide Landcover and Trees Study. Disturbances caused by stand-replacing events were successfully identified. The increased temporal resolution of the synthetic time series indicated promising additional information on disturbance timing. The results of the hybrid detection unified the benefits of both approaches, i.e., the spatial quality and general accuracy of the Landsat detection and the increased temporal information of synthetic time series. Results indicated that a temporal improvement in the detection of the disturbance date could be achieved relative to the irregularly spaced Landsat

  9. Spatial Bayesian belief networks as a planning decision tool for mapping ecosystem services trade-offs on forested landscapes.

    Science.gov (United States)

    Gonzalez-Redin, Julen; Luque, Sandra; Poggio, Laura; Smith, Ron; Gimona, Alessandro

    2016-01-01

    An integrated methodology, based on linking Bayesian belief networks (BBN) with GIS, is proposed for combining available evidence to help forest managers evaluate implications and trade-offs between forest production and conservation measures to preserve biodiversity in forested habitats. A Bayesian belief network is a probabilistic graphical model that represents variables and their dependencies through specifying probabilistic relationships. In spatially explicit decision problems where it is difficult to choose appropriate combinations of interventions, the proposed integration of a BBN with GIS helped to facilitate shared understanding of the human-landscape relationships, while fostering collective management that can be incorporated into landscape planning processes. Trades-offs become more and more relevant in these landscape contexts where the participation of many and varied stakeholder groups is indispensable. With these challenges in mind, our integrated approach incorporates GIS-based data with expert knowledge to consider two different land use interests - biodiversity value for conservation and timber production potential - with the focus on a complex mountain landscape in the French Alps. The spatial models produced provided different alternatives of suitable sites that can be used by policy makers in order to support conservation priorities while addressing management options. The approach provided provide a common reasoning language among different experts from different backgrounds while helped to identify spatially explicit conflictive areas.

  10. Mapping CORINE Land Cover from Sentinel-1A SAR and SRTM Digital Elevation Model Data using Random Forests

    Directory of Open Access Journals (Sweden)

    Heiko Balzter

    2015-11-01

    Full Text Available The European CORINE land cover mapping scheme is a standardized classification system with 44 land cover and land use classes. It is used by the European Environment Agency to report large-scale land cover change with a minimum mapping unit of 5 ha every six years and operationally mapped by its member states. The most commonly applied method to map CORINE land cover change is by visual interpretation of optical/near-infrared satellite imagery. The Sentinel-1A satellite carries a C-band Synthetic Aperture Radar (SAR and was launched in 2014 by the European Space Agency as the first operational Copernicus mission. This study is the first investigation of Sentinel-1A for CORINE land cover mapping. Two of the first Sentinel-1A images acquired during its ramp-up phase in May and December 2014 over Thuringia in Germany are analysed. 27 hybrid level 2/3 CORINE classes are defined. 17 of these were present at the study site and classified based on a stratified random sample of training pixels from the polygon-eroded CORINE 2006 map. Sentinel-1A logarithmic radar backscatter at HH and HV polarisation (May acquisition, VV and VH polarisation (December acquisition, and the HH image texture are used as input bands to the classification. In addition, a Digital Terrain Model (DTM, a Canopy Height Model (CHM and slope and aspect maps from the Shuttle Radar Topography Mission (SRTM are used as input bands to account for geomorphological features of the landscape. In future, elevation data will be delivered for areas with sufficiently high coherence from the Sentinel-1A Interferometric Wide-Swath Mode itself. When augmented by elevation data from radar interferometry, Sentinel-1A is able to discriminate several CORINE land cover classes, making it useful for monitoring of cloud-covered regions. A bistatic Sentinel-1 Convoy mission would enable single-pass interferometric acquisitions without temporal decorrelation.

  11. The Application of Satellite Map on Drawing in the Forestry Division and Liquidation and Returning to Forest%卫星地图在林业区划绘图、清收还林工作上的应用

    Institute of Scientific and Technical Information of China (English)

    毕靖吉; 刘素娟

    2015-01-01

    With the emergence of intelligent GPS,electronic map and other large data can be installed with the operating system. Through a large number of computer software the format can be changed. GPS,forest map,AutoCAD,Google Earth and satellite photos can be perfectly combined,and work efficiency can be more efficient. Forest maps and other for-estry drawings can be produced into GPS available map by different software. So work outside can be as easy as walking in the forest map.%随着智能 GPS 的出现,其操作系统可以安装电子地图等大数据,再通过大量计算机软件的格式转换,可以把 GPS 和林相图、AutoCAD、Google 地球卫星照片完美结合使用,达到更高工作效率。还可以把林相图等林业图纸,通过不同的软件制作成 GPS 可用的地图,安装到 GPS当中,外业工作时就如在林相图中行走一样方便。

  12. Assessing the Potential to Operationalize Shoreline Sensitivity Mapping: Classifying Multiple Wide Fine Quadrature Polarized RADARSAT-2 and Landsat 5 Scenes with a Single Random Forest Model

    Directory of Open Access Journals (Sweden)

    Sarah Banks

    2015-10-01

    Full Text Available The Random Forest algorithm was used to classify 86 Wide Fine Quadrature Polarized RADARSAT-2 scenes, five Landsat 5 scenes, and a Digital Elevation Model covering an area approximately 81,000 km2 in size, and representing the entirety of Dease Strait, Coronation Gulf and Bathurst Inlet, Nunavut. The focus of this research was to assess the potential to operationalize shoreline sensitivity mapping to inform oil spill response and contingency planning. The impact of varying the training sample size and reducing model data load were evaluated. Results showed that acceptable accuracies could be achieved with relatively few training samples, but that higher accuracies and greater probabilities of correct class assignment were observed with larger sample sizes. Additionally, the number of inputs to the model could be greatly reduced without impacting overall performance. Optimized models reached independent accuracies of 91% for seven land cover types, and classification probabilities between 0.77 and 0.98 (values for latter represent per-class averages generated from independent validation sites. Mixed results were observed when assessing the potential for remote predictive mapping by simulating transferability of the model to scenes without training data.

  13. Shadow of a Colossus: A z=2.45 Galaxy Protocluster Detected in 3D Ly-a Forest Tomographic Mapping of the COSMOS Field

    CERN Document Server

    Lee, Khee-Gan; White, Martin; Prochaska, J Xavier; Font-Ribera, Andreu; Schlegel, David J; Rich, R Michael; Suzuki, Nao; Stark, Casey W; Fevre, Olivier Le; Nugent, Peter E; Salvato, Mara; Zamorani, Gianni

    2015-01-01

    Using moderate-resolution optical spectra from 58 background Lyman-break galaxies and quasars at $z\\sim 2.3-3$ within a $11.5'\\times13.5'$ area of the COSMOS field ($\\sim 1200\\,\\mathrm{deg}^2$ projected area density or $\\sim 2.4\\,h^{-1}\\,\\mathrm{Mpc}$ mean transverse separation), we reconstruct a 3D tomographic map of the foreground Ly$\\alpha$ forest absorption at $2.2map. We find an extended IGM overdensity with deep absorption troughs at $z=2.45$ associated with a recently-discovered galaxy protocluster at the same redshift. Based on simulations matched to our data, we estimate the enclosed dark matter mass within this IGM overdensity to be $M_{\\rm dm} (z=2.45) = (9\\pm4)\\times 10^{13}\\,h^{-1}\\,\\mathrm{M_\\o...

  14. Mapping the distributions of C3 and C4 grasses in the mixed-grass prairies of southwest Oklahoma using the Random Forest classification algorithm

    Science.gov (United States)

    Yan, Dong; de Beurs, Kirsten M.

    2016-05-01

    The objective of this paper is to demonstrate a new method to map the distributions of C3 and C4 grasses at 30 m resolution and over a 25-year period of time (1988-2013) by combining the Random Forest (RF) classification algorithm and patch stable areas identified using the spatial pattern analysis software FRAGSTATS. Predictor variables for RF classifications consisted of ten spectral variables, four soil edaphic variables and three topographic variables. We provided a confidence score in terms of obtaining pure land cover at each pixel location by retrieving the classification tree votes. Classification accuracy assessments and predictor variable importance evaluations were conducted based on a repeated stratified sampling approach. Results show that patch stable areas obtained from larger patches are more appropriate to be used as sample data pools to train and validate RF classifiers for historical land cover mapping purposes and it is more reasonable to use patch stable areas as sample pools to map land cover in a year closer to the present rather than years further back in time. The percentage of obtained high confidence prediction pixels across the study area ranges from 71.18% in 1988 to 73.48% in 2013. The repeated stratified sampling approach is necessary in terms of reducing the positive bias in the estimated classification accuracy caused by the possible selections of training and validation pixels from the same patch stable areas. The RF classification algorithm was able to identify the important environmental factors affecting the distributions of C3 and C4 grasses in our study area such as elevation, soil pH, soil organic matter and soil texture.

  15. US Forest Service Ecological Sections

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting ecological section boundaries within the conterminous United States. The map service contains regional geographic delineations for...

  16. Insight into the genetic components of community genetics: QTL mapping of insect association in a fast-growing forest tree.

    Directory of Open Access Journals (Sweden)

    Jennifer DeWoody

    Full Text Available Identifying genetic sequences underlying insect associations on forest trees will improve the understanding of community genetics on a broad scale. We tested for genomic regions associated with insects in hybrid poplar using quantitative trait loci (QTL analyses conducted on data from a common garden experiment. The F2 offspring of a hybrid poplar (Populus trichocarpa x P. deltoides cross were assessed for seven categories of insect leaf damage at two time points, June and August. Positive and negative correlations were detected among damage categories and between sampling times. For example, sap suckers on leaves in June were positively correlated with sap suckers on leaves (P<0.001 but negatively correlated with skeletonizer damage (P<0.01 in August. The seven forms of leaf damage were used as a proxy for seven functional groups of insect species. Significant variation in insect association occurred among the hybrid offspring, including transgressive segregation of susceptibility to damage. NMDS analyses revealed significant variation and modest broad-sense heritability in insect community structure among genets. QTL analyses identified 14 genomic regions across 9 linkage groups that correlated with insect association. We used three genomics tools to test for putative mechanisms underlying the QTL. First, shikimate-phenylpropanoid pathway genes co-located to 9 of the 13 QTL tested, consistent with the role of phenolic glycosides as defensive compounds. Second, two insect association QTL corresponded to genomic hotspots for leaf trait QTL as identified in previous studies, indicating that, in addition to biochemical attributes, leaf morphology may influence insect preference. Third, network analyses identified categories of gene models over-represented in QTL for certain damage types, providing direction for future functional studies. These results provide insight into the genetic components involved in insect community structure in a fast

  17. [Successful treatment of a persistent rhino-cerebral mucormycosis in a pediatric patient with a debut of acute lymphoblastic leukemia].

    Science.gov (United States)

    Cofré, Fernanda; Villarroel, Milena; Castellón, Loreto; Santolaya, María E

    2015-08-01

    The fungi of the order Mucorales cause mucormycosis, which usually presents as an invasive fungal disease with rapid angioinvasion in immunocompromised patients. Rhinocerebral is the most common presentation. The lipid formulations of amphotericin B are used as primary treatment in invasive mucormycosis; the combined use of posaconazole could allow a reduction in the dose of amphotericin B improving tolerance and adherence to treatment. Caspofungin and amphotericin B association has been shown to be synergistic in vitro and effective in murine models. We present the case of a preschool patient that during the debut of acute lymphoblastic leukemia developed a rhinocerebral mucormycosis successfully responding to antifungal treatment with the combination of liposomal amphotericin and caspofungin.

  18. 使用GIS区划白河林业局森林经营类型%A Geographic Information Systems approach for classifying and mapping forest management category in Baihe Forestry Bureau, Northeast China

    Institute of Scientific and Technical Information of China (English)

    王顺忠; 邵国凡; 谷会岩; 王庆礼; 代力民

    2006-01-01

    This paper demonstrates a Geographic Information Systems (GIS) procedure of classifying and mapping forest management category in Baihe Forestry Burea, Jilin Province, China. Within the study area, Baihe Forestry Bureau land was classified into a two-hierarchy system. The top-level class included the non-forest and forest. Over 96% of land area is forest in the study area, which was further divided into key ecological service forest (KES), general ecological service forest (GES), and commodity forest (COM).COM covered 45.0% of the total land area and was the major forest management type in Baihe Forest Bureau. KES and GES accounted for 21.2% and 29.9% of the total land area, respectively. The forest management zones designed with GIS in this study were then compared with the forest management zones established using the hand draw by the local agency. There were obvious differences between the two products. It suggested that the differences had some to do with the data sources, basic unit and mapping procedures. It also suggested that the GIS method was a useful tool in integrating forest inventory data and other data for classifying and mapping forest zones to meet the needs of the classified forest management system.%使用GIS区划了白河林业局森林经营类型,并和原有的森林经营类型进行了比较.在数字化区划的森林经营类型中,二级系统被采纳.首先,白河林业局被区划为林地和非林地,其中,总面积的96%为林地,然后,林地区划为重点公益林,一般公益林和商品林.在重新区划的森林经营类型中,商品林达到总面积的45.0%,是最主要的森林经营类型:重点公益林和一般公益林分别为总面积的21.2%和29.9%.两个区划结果有很大的不同,在数字化区划的森林经营类型中,各类型斑块数量较多,面积较小,这些不同主要由使用数据,区划单位和区划方法的不同引起的.研究表明,GIS在区划森林经营类型时是一种有效的方

  19. The first film presentation of REM sleep behavior disorder precedes its scientific debut by 35 years

    Directory of Open Access Journals (Sweden)

    Janković Slavko M.

    2006-01-01

    Full Text Available The perplexing and tantalizing disease of rapid eye movement (REM sleep behavior disorder (RBD is characterized by peculiar, potentially dangerous behavior during REM sleep. It was described both in animals and humans. RBD in mammals was first described by Jouvet and Delorme in 1965, based on an experimental model induced by lesion in pontine region of cats [1]. In 1972, Passouant et al. described sleep with eye movements and persistent tonic muscle activity induced by tricyclic antidepressant medication [2], and Tachibana et al., in 1975, the preservation of muscle tone during REM sleep in the acute psychosis induced by alcohol and meprobamate abuse [3]. However, the first formal description of RBD in humans as new parasomnia was made by Schenck et al in 1986 [4-7]. Subsequently, in 1990, the International Classification of Sleep Disorders definitely recognized RBD as new parasomnia [8]. To our knowledge, arts and literature do not mention RBD. Except for the quotation, made by Schenck et al [6] in 2002, of Don Quixote de la Mancha whose behavior in sleep strongly suggested that Miguel de Servantes actually described RBD, no other artistic work has portrayed this disorder. Only recently we become aware of the cinematic presentation of RBD which by decades precedes the first scientific description. The first presentation of RBD on film was made prior to the era of advanced electroencephalography and polysomnography, and even before the discovery of REM sleep by Aserinsky and Kleitman in 1953. [9]. The artistic and intuitive presentation of RBD was produced in Technicolor in a famous film "Cinderella" created by Walt Disney in 1950, some 35 years prior to its original publication in the journal "Sleep" [2]. Since there is an earlier version of the film initially produced in 1920, presumably containing this similar scene, we can only speculate that the first cinematic presentation of RBD might precede its scientific debut by 65 years. In a scene

  20. [The first film presentation of REM sleep behavior disorder precedes its scientific debut by 35 years].

    Science.gov (United States)

    Janković, Slavko M; Sokić, Dragoslav V; Vojvodić, Nikola M; Ristić, Aleksandar J

    2006-01-01

    The perplexing and tantalizing disease of rapid eye movement (REM) sleep behavior disorder (RBD) is characterized by peculiar, potentially dangerous behavior during REM sleep. It was described both in animals and humans. RBD in mammals was first described by Jouvet and Delorme in 1965, based on an experimental model induced by lesion in pontine region of cats. In 1972, Passouant et al. described sleep with eye movements and persistent tonic muscle activity induced by tricyclic antidepressant medication, and Tachibana et al., in 1975, the preservation of muscle tone during REM sleep in the acute psychosis induced by alcohol and meprobamate abuse. wever, the first formal description of RBD in humans as new parasomnia was made by Schenck et al in 1986. Subsequently, in 1990, the International Classification of Sleep Disorders definitely recognized RBD as new parasomnia. To our knowledge, arts and literature do not mention RBD. Except for the quotation, made by Schenck et al [n 2002, of Don Quixote de la Mancha whose behavior in sleep strongly suggested that Miguel de Servantes actually described RBD, no other artistic work has portrayed this disorder. Only recently we become aware of the cinematic presentation of RBD which by decades precedes the first scientific description. The first presentation of RBD on film was made prior to the era of advanced electroencephalography and polysomnography, and even before the discovery of REM sleep by Aserinsky and Kleitman in 1953. The artistic and intuitive presentation of RBD was produced in Technicolor in a famous film "Cinderella" created by Walt Disney in 1950, some 35 years prior to its original publication in the journal "Sleep". Since there is an earlier version of the film initially produced in 1920, presumably containing this similar scene, we can only speculate that the first cinematic presentation of RBD might precede its scientific debut by 65 years. In a scene in a barn, clumsy and goofy dog Bruno is, as dogs

  1. 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...

  2. US Forest Service National Wilderness Areas 2 - Green Polygon Fill

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting parcels of Forest Service land congressionally designated as wilderness such as National Wilderness Areas. This map service...

  3. An intercomparison of Satellite Burned Area Maps derived from MODIS, MERIS, SPOT-VEGETATION, and ATSR images. An application to the August 2006 Galicia (Spain forest fires

    Directory of Open Access Journals (Sweden)

    M. Huesca

    2013-07-01

    Full Text Available Aim of study: The following paper presents an inter-comparison of three global products: MCD45A1 (MODIS - MODerate resolution Imaging Spectrometer - Burned Area Product, L3JRC (Terrestrial Ecosystem Monitoring Global Burnt Area Product, and GLOBCARBON Burnt Area Estimate (BAE Product; and three local products, two of them based on MODIS data and the other one based on MERIS (MEdium Resolution Imaging Spectrometer data.Area of study: The study was applied to the Galician forest fires occurred in 2006.Materials and Methods: Materials used involved the three already mentioned global products together with two MODIS and one MERIS reflectance images, and MODIS thermal anomalies. The algorithm we used, which is based on the determination of thresholds values on infrared bands, allowed the identification of burned pixels. The determination of such threshold values was based on the maximum spatial correlation between MODIS thermal anomalies, and infrared reflectance values. This methodology was applied to MODIS and MERIS reflectance bands, and to the NBR (Normalized Burn Ratio. Burned area validation was evaluated using burned area polygons as derived from an AWiFS (Advanced Wide Field Sensor image of 60m pixel size.Main results: Best results were reached when using the MERIS infrared bands, followed by the MODIS infrared bands. Worst results were reached when using the MCD45A1 product, which clearly overestimated; and when using the L3JRC product, which clearly underestimated.Research highlights: Since the efficiency of the performance of the available burned area products is highly variable, much work is needed in terms of comparison among the available sensors, the burned area mapping algorithms and the resulting products.Keywords: forest fires; MODIS; MERIS; MCD45A1; L3JRC; GLOBCARBON-BAE; SPOT-VEGETATION; ATSR.Abbreviations used: ATSR: Along Scanning Radiometer; AVHRR: Advanced Very High Resolution Radiometer; AWiFS: Advanced Wide Field Sensor; EOS

  4. US Forest Service Western Bark Beetle Strategy

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting Western Bark Beetle Strategy (WBBS) activities reported through the U.S. Forest Service FACTS database. Activities include...

  5. US Forest Service Special Status Areas

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting land areas that have distinct management/use authorities or agreements for Forest Service action. Includes: Cost Share Agreement...

  6. US Forest Service Recreation Area Activities

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting the recreation area activity information that the Forest Service collects through the Recreation Portal and shares with the public...

  7. US Forest Service Integrated Resource Restoration (IRR)

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting activities funded through the Integrated Resource Restoration (IRR) NFRR Budget Line Item and reported through the U.S. Forest...

  8. Assessing the utility WorldView-2 imagery for tree species mapping in a South African subtropical forest patch and the conservation implications: Dukuduku forest patch as case study

    CSIR Research Space (South Africa)

    Cho, Moses A

    2015-06-01

    Full Text Available Indigenous forest biome in South Africa is highly fragmented into patches of various sizes (most patches < 1 km (sup20). The utilization of timber and non-timber resources by poor rural communities living around protected forest patches produce...

  9. A Combined Random Forest and OBIA Classification Scheme for Mapping Smallholder Agriculture at Different Nomenclature Levels Using Multisource Data (Simulated Sentinel-2 Time Series, VHRS and DEM

    Directory of Open Access Journals (Sweden)

    Valentine Lebourgeois

    2017-03-01

    Full Text Available Sentinel-2 images are expected to improve global crop monitoring even in challenging tropical small agricultural systems that are characterized by high intra- and inter-field spatial variability and where satellite observations are disturbed by the presence of clouds. To overcome these constraints, we analyzed and optimized the performance of a combined Random Forest (RF classifier/object-based approach and applied it to multisource satellite data to produce land use maps of a smallholder agricultural zone in Madagascar at five different nomenclature levels. The RF classifier was first optimized by reducing the number of input variables. Experiments were then carried out to (i test cropland masking prior to the classification of more detailed nomenclature levels, (ii analyze the importance of each data source (a high spatial resolution (HSR time series, a very high spatial resolution (VHSR coverage and a digital elevation model (DEM and data type (spectral, textural or other, and (iii quantify their contributions to classification accuracy levels. The results show that RF classifier optimization allowed for a reduction in the number of variables by 1.5- to 6-fold (depending on the classification level and thus a reduction in the data processing time. Classification results were improved via the hierarchical approach at all classification levels, achieving an overall accuracy of 91.7% and 64.4% for the cropland and crop subclass levels, respectively. Spectral variables derived from an HSR time series were shown to be the most discriminating, with a better score for spectral indices over the reflectances. VHSR data were only found to be essential when implementing the segmentation of the area into objects and not for the spectral or textural features they can provide during classification.

  10. Mian is...?——,Mian is..“Yearly Campaign Officially Debuts and Trailer of Mian Series of Videos Premieres

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    Beijing, April 25, 2012 - Brand new yearly campaign “Mian is...” officially debuted with a fresh concept and the one and only Mian series of videos unveiled. Three principals of Mian series of videos, Greeny Wu, lead singer of famous Taiwanese band Sodagreen, Tong Liya, Chinese uprising beautiful actress, Sam Lee, Chinese fashion and lifestyle media mavon, attended the ceremony and shared their answers to “Mian is..” and their own Mian fashion and lifestyle.

  11. Study on the Boundary Survey in the Tenure Collective Forest the Technique of Overlaying the Digital Orthophoto Maps and the Topographic Maps%航空遥感技术在林改宗地勘界中的研究与应用

    Institute of Scientific and Technical Information of China (English)

    邹杰

    2011-01-01

    In the reform of the collective forest right system, delineating parcel forestland is the core content. Using high resolution and large scale aerial orthoimage and electronic vector topographic map overlay for forest land surveying technology, the study shows that the work efficiency and sketch precision are higherthan the traditional topographic map drew parcel method.%指出了在集体林权制度改革中,林地宗地勾绘是核心内容,分析了采用高分辨率大比例尺航空正射影像图与电子矢量化地形图叠加进行林改宗地勘界,研究表明:其技术比传统地形图上勾绘宗地方法更能提高工作效率及勾绘精度。

  12. US Forest Service LANDFIRE Potential Vegetation

    Data.gov (United States)

    US Forest Service, Department of Agriculture — LANDFIRE Potential Vegetation is mapped using predictive landscape models based on extensive field-referenced data and biophysical gradient layers using...

  13. Hyperspectral Remote Sensing for Tropical Rain Forest

    Directory of Open Access Journals (Sweden)

    Kamaruzaman Jusoff

    2009-01-01

    Full Text Available Problem statement: Sensing, mapping and monitoring the rain forest in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions and are now included in climate change negotiations. Approach: We reviewed the potential for air and spaceborne hyperspectral sensing to identify and map individual tree species measure carbon stocks, specifically Aboveground Biomass (AGB and provide an overview of a range of approaches that have been developed and used to map tropical rain forest across a diverse set of conditions and geographic areas. We provided a summary of air and spaceborne hyperspectral remote sensing measurements relevant to mapping the tropical forest and assess the relative merits and limitations of each. We then provided an overview of modern techniques of mapping the tropical forest based on species discrimination, leaf chlorophyll content, estimating aboveground forest productivity and monitoring forest health. Results: The challenges in hyperspectral Imaging of tropical forests is thrown out to researchers in such field as to come with the latest techniques of image processing and improved mapping resolution leading towards higher precision mapping accuracy. Some research results from an airborne hyperspectral imaging over Bukit Nanas forest reserve was shared implicating high potential of such very high resolution imaging techniques for tropical mixed dipterocarp forest inventory and mapping for species discrimination, aboveground forest productivity, leaf chlorophyll content and carbon mapping. Conclusion/Recommendations: We concluded that while spaceborne hyperspectral remote sensing has often been discounted as inadequate for the task, attempts to map with airborne sensors are still insufficient in tropical developing countries like Malaysia. However, we demonstrated this with a case

  14. 基于GIS与RS三维虚拟林相图可视化技术研究%3 D virtual visualization technology research of forest form map based on GIS and RS

    Institute of Scientific and Technical Information of China (English)

    陈利; 王福生; 管远保; 陶冀; 林辉

    2014-01-01

    Three-D visualization technology can make the abstract conceptions and the space phenomena that difficult to directly perceive reality and visualization. Therefore, the technology can be used to simulate woodland vegetation, to demonstrate forest land distribution with virtual method and can abstract various kinds of experiences and concepts of spatial perception beyond the reality that is hard to direct perception of reality and visualization space phenomenon. This study takes Wuchuanhu village of Changsha county in Hunan province as the experimental area, based on the 1︰10 000 topographic maps, the aerial photo with resolution of 0.5 meter and the second class forest resource survey data taken in 2013 as the data sources, and takes full use the advantage of a variety of data, then integrates a variety of data, breaks the traditional two-dimensional forest map, ifnally explores the making method of 3-D forest map based on GIS platform. Through the 3-D forest map making, we can not only taste the changes of forest landscape in three-dimensional space, understand the forest composition with three-dimensional and multi-angle and more intuitively understand the forest spatial structure and distribution law;but also can complete the inquiry and positioning function, thus it is convenient for the forestry sector’s production and business operation and management.%三维可视化能够使抽象概念且难以直接感知的空间现象现实化以及直观化,利用此技术可以对林地植被进行模拟,虚拟演示林地分布情况,能够获得各种超越现实的空间感知的经验。本研究以湖南省长沙县乌川湖村作为实验区,以1∶10000的地形图、分辨率为0.5 m的航片以及2013年二类森林资源调查数据等为数据源,充分利用各种数据的优势,把各种数据融为一体,突破了传统的二维林相图,探索出了基于GIS平台的三维林相图的制作,通过三维林相图的制作,不仅

  15. US Forest Service National Forest Lands with Nationally Designated Management or Use Limitations 

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting an area depicting National Forest System land parcels that have management or use limits placed on them by legal authority....

  16. US Forest Service National Forest Lands with Nationally Designated Management or Use Limitations: Legal Status

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting the status of areas showing National Forest System land parcels that have management or use limits placed on them by legal...

  17. US Forest Service Ranger District Boundaries

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting the boundary that encompasses a Ranger District. This map service provides display, identification, and analysis tools for...

  18. US Forest Service Surface Ownership Parcels

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting areas as surface ownership parcels dissolved on the same ownership classification. This map service was prepared to describe...

  19. US Forest Service Surface Ownership Parcels (Generalized)

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting areas as surface ownership parcels dissolved on the same ownership classification. This map service was prepared to describe...

  20. Translating Forest Change to Carbon Emissions and Removals By Linking Disturbance Products, Biomass Maps, and Carbon Cycle Modeling in a Comprehensive Carbon Monitoring Framework for the Conterminous US Forests

    Science.gov (United States)

    Williams, C. A.; Gu, H.

    2016-12-01

    Protecting forest carbon stores and uptake is central to national and international policies aimed at mitigating climate change. The success of such polices relies on high quality, accurate reporting (Tier 3) that earns the greatest financial value of carbon credits and hence incentivizes forest conservation and protection. Methods for Tier 3 Measuring, Reporting, and Verification (MRV) are still in development, generally involving some combination of direct remote sensing, ground based inventorying, and computer modeling, but have tended to emphasize assessments of live aboveground carbon stocks with a less clear connection to the real target of MRV which is carbon emissions and removals. Most existing methods are also ambiguous as to the mechanisms that underlie carbon accumulation, and any have limited capacity for forecasting carbon dynamics over time. This paper reports on the design and implementation of a new method for Tier 3 MRV, decision support, and forecasting that is being applied to assess forest carbon dynamics across the conterminous US. The method involves parameterization of a carbon cycle model (CASA) to match yield data from the US forest inventory (FIA). A range of disturbance types and severities are imposed in the model to estimate resulting carbon emissions, carbon uptake, and carbon stock changes post-disturbance. Resulting trajectories are then applied to landscapes at the 30-m pixel level based on two remote-sensing based data products. One documents the year, type, and severity of disturbance in recent decades. The second documents aboveground biomass which is used to estimate time since disturbance and associated carbon fluxes and stocks. Results will highlight high-resolution (30 m) annual carbon stocks and fluxes from 1990 to 2010 for select regions of interest across the US. Spatial analyses reveal regional patterns in US forest carbon stocks and fluxes as they respond to forest types, climate, and disturbances. Temporal analyses

  1. US Forest Service Geopolitical Units adjusted within Administrative Forest Boundaries

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting geopolitical data for the entire area of the United States and territories. This includes States, Counties or Boroughs,...

  2. [Sexual intercourse debut and associated factors in Mexican students aged 14-19 years in public schools].

    Science.gov (United States)

    Rivera-Rivera, Leonor; Leyva-López, Ahidée; García-Guerra, Armando; de Castro, Filipa; González-Hernández, Dolores; de Los Santos, Lilia Margarita

    2016-01-01

    To estimate the mean age of sexual intercourse debut (SID) and associated family and individual factors in 14-19-year-olds of both sexes in the 32 states of Mexico in 2007. A cross-sectional study was conducted of a representative sample of 9,893 students aged between 14 and 19 years old. The data were collected through a self-administered, anonymous and voluntary questionnaire. Logistic regression models were used to estimate odds ratios (OR) with 95% confidence intervals (95%CI) by category: no SID, SID at 10-15 years and SID at 16-19 years. The national mean age of SID was 16 years, being 15 years for boys (95%CI: 15.88-16.11) and 16 years for girls (95%CI: 15.26-15.42). Factors associated with SID in boys were disadvantaged socioeconomic level (OR=0.66; 95%CI: 0.46-0.94), living with parents (OR=0.65; 95%CI: 0.56-0.75), less offensive communication between parents and boys/girls (OR=0.66; 95%CI: 0.57-0.77), and high social self-esteem (OR=1.68; 95%CI: 1.35-1.77). Factors associated with SID in girls were traditional gender beliefs (OR=0.49; 95%CI: 0.32-0.74), high depressive symptoms (OR=1.88; 95%CI: 1.19-2.99), and high family self-esteem (OR= 0.50; 95%CI: 0.38-0.65). In Mexico, SID occurred early in boys. In addition, the findings of this study show that in Mexico, the age of SID and associated factors differ in boys and girls. The age of SID is strongly influenced by gender and cultural beliefs. Copyright © 2015 SESPAS. Published by Elsevier Espana. All rights reserved.

  3. US Forest Service Timber Harvests

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www that depicts the area planned and accomplished acres treated as a part of the timber harvest program of work, funded through the budget...

  4. US Forest Service Land Utilization

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting units designated by the Secretary of Agriculture for conservation and utilization under Title III of the Bankhead-Jones Farm...

  5. Forest Cover Types - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This map layer portrays general forest cover types for the United States. Data were derived from Advanced Very High Resolution Radiometer (AVHRR) composite images...

  6. US Forest Service Stewardship Contracting

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting the locations of activities within the Stewardship Contracting Project Boundary. Activities are implemented through stewardship...

  7. Evaluation and Zone Mapping of Forest Fire Risk Grade in Dapingzhang,Dongguan%东莞大屏嶂森林火险等级评价与区划

    Institute of Scientific and Technical Information of China (English)

    严朝东; 林育述; 陈轩阳; 胡科; 林观土

    2014-01-01

    针对广东省东莞大屏嶂森林公园的森林资源环境特点,选取植被类型、坡度、坡向、海拔、居民区距离、道路距离6个火险影响因子,利用GI S空间分析功能对大屏嶂森林公园进行森林火险等级的评价与区划。区划方案表明,该区可以划分为无、低、中、高和极高5个等级火险区,其面积分别占研究区的1.67%、2.19%、33.16%、55.3%和7.68%。森林火险等级的空间分异较明显,极高火险主要出现在西北部,中部和北部火险等级较高,东部与南部火险稍低。森林火险较高等级主要受植被类型、坡向及海拔这3个因素影响。%According to the traits of forest resource environment in Dapingzhang forest park,spatial analysis function of GIS was applied to forest fire risk grade evaluation and zone mapping in this paper.Six factors including stand,slope,aspect,altitude,distance to settlement and to road,were chosen as forest fire risk factors.The re-sults indicated that Dapingzhang forest park could be divided into five fire risk zones.The area of no,low,moder-ate,high and extremely high fire risk zone accounted for 1.67%,2.19%,33.16%,55.3%and 7.68%,respec-tively.The spatial distribution differences of forest fire risk zones were obvious.The extremely high fire risk mainly appeared in the northwestern part,while moderate and high fire risk spread through the central and northern part, and the low fire risk mainly located on the eastern and southern part.Stand,aspect and altitude were principal fac-tors that affected forest fire risk.

  8. Mapping the distribution of the main host for plague in a complex landscape in Kazakhstan: An object-based approach using SPOT-5 XS, Landsat 7 ETM+, SRTM and multiple Random Forests.

    Science.gov (United States)

    Wilschut, L I; Addink, E A; Heesterbeek, J A P; Dubyanskiy, V M; Davis, S A; Laudisoit, A; M Begon; Burdelov, L A; Atshabar, B B; de Jong, S M

    2013-08-01

    Plague is a zoonotic infectious disease present in great gerbil populations in Kazakhstan. Infectious disease dynamics are influenced by the spatial distribution of the carriers (hosts) of the disease. The great gerbil, the main host in our study area, lives in burrows, which can be recognized on high resolution satellite imagery. In this study, using earth observation data at various spatial scales, we map the spatial distribution of burrows in a semi-desert landscape. The study area consists of various landscape types. To evaluate whether identification of burrows by classification is possible in these landscape types, the study area was subdivided into eight landscape units, on the basis of Landsat 7 ETM+ derived Tasselled Cap Greenness and Brightness, and SRTM derived standard deviation in elevation. In the field, 904 burrows were mapped. Using two segmented 2.5 m resolution SPOT-5 XS satellite scenes, reference object sets were created. Random Forests were built for both SPOT scenes and used to classify the images. Additionally, a stratified classification was carried out, by building separate Random Forests per landscape unit. Burrows were successfully classified in all landscape units. In the 'steppe on floodplain' areas, classification worked best: producer's and user's accuracy in those areas reached 88% and 100%, respectively. In the 'floodplain' areas with a more heterogeneous vegetation cover, classification worked least well; there, accuracies were 86 and 58% respectively. Stratified classification improved the results in all landscape units where comparison was possible (four), increasing kappa coefficients by 13, 10, 9 and 1%, respectively. In this study, an innovative stratification method using high- and medium resolution imagery was applied in order to map host distribution on a large spatial scale. The burrow maps we developed will help to detect changes in the distribution of great gerbil populations and, moreover, serve as a unique empirical

  9. Classification of Forest Fragmentation in North America - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This map layer is a grid map of North America including the Caribbean and most of Mexico. The map layer is an excerpt from a global assessment of forest...

  10. Forest cover from landsat thematic mapper data for use in the Catahoula Ranger District geographic information system. Forest Service general technical report

    Energy Technology Data Exchange (ETDEWEB)

    Evans, D.L.

    1994-04-01

    A forest cover classification of the Kisatchie National Forest, Catahoula Ranger District, was performed with Landsat Thematic Mapper data. Data base retrievals and map products from this analysis demonstrated used of Landsat for forest management decisions.

  11. Asymmetric Information,Noise Trading and Proceeds from IPOs on their Debut%信息不对称、噪声交易与IPO首日收益

    Institute of Scientific and Technical Information of China (English)

    武龙

    2011-01-01

    IPO首日收益异象的形成一直有争议,而发行价偏低的抑价观点也受到某些实证研究的挑战。本文在一级市场中引入噪声申购者影响,并综合信息不对称和噪声交易两类因素,对IPO首日收益的形成进行研究并实证。研究发现,IPO首日收益与新股的一、二级市场错误定价均有关,前者由信息不对称和噪声申购者共同决定,后者由上市首日的噪声交易者(狂热投资者和正向反馈交易者)决定,其中后者的影响更强。%There have been disagreements on the formation of anomalous proceeds from IPOs on their debut and the view of IPO being underpriced is doubted by some empirical researches with the discovery of IPOs' overpricing.By introducing the impact of noise traders into the primary market and considering the two types of factors of asymmetric information and noise trading together,this paper systematically explains the abnormal proceeds from IPOs on their debut.The findings suggest that the proceeds on debut are mainly related to the mispricing of new shares in both the primary and the secondary markets.The former is reflected by the asymmetric information and the noise traders in the primary market,while the latter is reflected by the noise traders(including sentiment investors and positive feedback traders) in the secondary market,and the effect of the latter is more remarkable.

  12. Object-based random forest classification for mapping floodplain vegetation structure from nation-wide CIR and LiDAR datasets

    NARCIS (Netherlands)

    Kooistra, L.; Kuilder, E.T.; Mücher, C.A.

    2014-01-01

    Very high resolution aerial images and LiDAR (AHN2) datasets with a national coverage provide opportunities to produce vegetation maps automatically. As such the entire area of the river floodplains in the Netherlands may be mapped with high accuracy and regular updates, capturing the dynamic state

  13. Object-based random forest classification for mapping floodplain vegetation structure from nation-wide CIR and LiDAR datasets

    NARCIS (Netherlands)

    Kooistra, L.; Kuilder, E.T.; Mücher, C.A.

    2014-01-01

    Very high resolution aerial images and LiDAR (AHN2) datasets with a national coverage provide opportunities to produce vegetation maps automatically. As such the entire area of the river floodplains in the Netherlands may be mapped with high accuracy and regular updates, capturing the dynamic state

  14. Lyα Forest Tomography from Background Galaxies: The First Megaparsec-resolution Large-scale Structure Map at z > 2

    NARCIS (Netherlands)

    Lee, Khee-Gan; Hennawi, Joseph F.; Stark, Casey; Prochaska, J. Xavier; White, Martin; Schlegel, David J.; Eilers, Anna-Christina; Arinyo-i-Prats, Andreu; Suzuki, Nao; Croft, Rupert A. C.; Caputi, Karina I.; Cassata, Paolo; Ilbert, Olivier; Garilli, Bianca; Koekemoer, Anton M.; Le Brun, Vincent; Le Fèvre, Olivier; Maccagni, Dario; Nugent, Peter; Taniguchi, Yoshiaki; Tasca, Lidia A. M.; Tresse, Laurence; Zamorani, Gianni; Zucca, Elena

    2014-01-01

    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 -1 Mpc comoving, allowing us to create a tomographic

  15. Forest hydrology

    Science.gov (United States)

    Ge Sun; Devendra Amatya; Steve McNulty

    2016-01-01

    Forest hydrology studies the distribution, storage, movement, and quality of water and the hydrological processes in forest-dominated ecosystems. Forest hydrological science is regarded as the foundation of modern integrated water¬shed management. This chapter provides an overview of the history of forest hydrology and basic principles of this unique branch of...

  16. Forest Management

    Science.gov (United States)

    S. Hummel; K. L. O' Hara

    2008-01-01

    Global variation in forests and in human cultures means that a single method for managing forests is not possible. However, forest management everywhere shares some common principles because it is rooted in physical and biological sciences like chemistry and genetics. Ecological forest management is an approach that combines an understanding of universal processes with...

  17. 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...

  18. DEBUT OF NEW LEADERSHIP

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    COVER STORY For a week the world watched and listened as the 17th National Congress of the Communist Party of China(CPC)deliberated on the country’s future in Beijing.Decisions taken at the Congress will most likely affect not only China,but also the world.Media had more access to proceedings while new younger faces were introduced to replace some of the old guard in the all-powerful politburo. But perhaps the highlight of the Congress was the presentation of a report by Hu Jintao,General Secretary of the Central Committee of the CPC,in which he clearly defined the blueprint for China’s impressive goals in areas of economic,political, cultural and social development.Tempered by reduced consumption of resources and bigger efforts in environmental protection,the country’s growth is taking on a more holistic approach,which bodes well for domestic and global outlook in the years ahead.

  19. Popularity and Debut

    DEFF Research Database (Denmark)

    Winther, Christian Dahl

    This paper focuses on two firms' optimal entry strategies in an emerging market characterized by word-of-mouth effects. Consumers can be of two types depending on which firm's brand they prefer. Firms are asymmetric in their popularity as given by the probability of meeting a fan of its brand. Word......-of-mouth communication influences popularity in the two periods of competition by increasing the likelihood of the late consumer having an affinity towards the brand adopted at the first stage. In this environment firms strategically choose their timing of product introduction knowing that fast introduction is costly. I....... In addition, the paper illustrates that the more popular firm in many cases prefers to mimic its smaller rival, which, on the other hand, would like for the firms to play opposite strategies. The model is extended to study how firms may want to lower the degree of product differentiation to reduce first...

  20. Popularity and Debut

    DEFF Research Database (Denmark)

    Winther, Christian Dahl

    -of-mouth communication influences popularity in the two periods of competition by increasing the likelihood of the late consumer having an affinity towards the brand adopted at the first stage. In this environment firms strategically choose their timing of product introduction knowing that fast introduction is costly. I......This paper focuses on two firms' optimal entry strategies in an emerging market characterized by word-of-mouth effects. Consumers can be of two types depending on which firm's brand they prefer. Firms are asymmetric in their popularity as given by the probability of meeting a fan of its brand. Word...

  1. New Leadership Debut

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The curtain has come down on the annual sessions of the National People’s Congress (NPC) and the National Committee of the Chinese People’s Political Consultative Conference (CPPCC) in Beijing.The meetings deliberated and ap- proved the Report on the Work of the Government and other important reports, summarized significant achievements and lessons learned in the past five years, identified key tasks and charted the directions for the next five years. In his report on the work of the government,Premier Wen Jiabao pointed out that in the past five years,China saw remarkable progress in carrying out reform and opening up and in building a moderately prosperous society in all respects.

  2. US Forest Service Wilderness Areas: Legal Status 2 - Grid Polygon Fill

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting status of parcels for Forest Service land congressionally designated as wilderness such as National Wilderness Areas. This map...

  3. Forest rights

    DEFF Research Database (Denmark)

    Balooni, Kulbhushan; Lund, Jens Friis

    2014-01-01

    One of the proposed strategies for implementation of reducing emissions from deforestation and forest degradation plus (REDD+) is to incentivize conservation of forests managed by communities under decentralized forest management. Yet, we argue that this is a challenging road to REDD+ because......+ transactions costs. Third, beyond the “conservation islands” represented by forests under decentralized management, processes of deforestation and forest degradation continue. Given these challenges, we argue that REDD+ efforts through decentralized forestry should be redirected from incentivizing further...

  4. Forest rights

    DEFF Research Database (Denmark)

    Balooni, Kulbhushan; Lund, Jens Friis

    2014-01-01

    One of the proposed strategies for implementation of reducing emissions from deforestation and forest degradation plus (REDD+) is to incentivize conservation of forests managed by communities under decentralized forest management. Yet, we argue that this is a challenging road to REDD+ because......+ transactions costs. Third, beyond the “conservation islands” represented by forests under decentralized management, processes of deforestation and forest degradation continue. Given these challenges, we argue that REDD+ efforts through decentralized forestry should be redirected from incentivizing further...

  5. Digital forestry maps representation using web mapping services

    Directory of Open Access Journals (Sweden)

    Martin Klimánek

    2008-01-01

    Full Text Available The Web Mapping Services (WMS are very useful means for presentation of digital geospatial data in the Internet environment. Typical Open Source example of these services is development environment MapServer, which was originally developed by the University of Minnesota ForNet project in cooperation with NASA and the Minnesota Department of Natural Resources. MapServer is not a full-featured Geographical Information System (GIS, but provides the core functionality to support a wide variety of web applications. Complex and open information system about forest (and cultural land is presented in real example of MapServer application with data from the Mendel University Training Forest. MapServer is used in effective representing of data for the University Forest staff, students and general public from October 2002. MapServer is usually applied in education process of GIS and Remote Sensing and for sharing of the Faculty of Forestry and Wood Technology Departments geospatial data.

  6. A new 500-m resolution map of canopy height for Amazon forest using spaceborne LiDAR and cloud-free MODIS imagery

    Science.gov (United States)

    Sawada, Yoshito; Suwa, Rempei; Jindo, Keiji; Endo, Takahiro; Oki, Kazuo; Sawada, Haruo; Arai, Egidio; Shimabukuro, Yosio Edemir; Celes, Carlos Henrique Souza; Campos, Moacir Alberto Assis; Higuchi, Francisco Gasparetto; Lima, Adriano José Nogueira; Higuchi, Niro; Kajimoto, Takuya; Ishizuka, Moriyoshi

    2015-12-01

    In the present study, we aimed to map canopy heights in the Brazilian Amazon mainly on the basis of spaceborne LiDAR and cloud-free MODIS imagery with a new method (the Self-Organizing Relationships method) for spatial modeling of the LiDAR footprint. To evaluate the general versatility, we compared the created canopy height map with two different canopy height estimates on the basis of our original field study plots (799 plots located in eight study sites) and a previously developed canopy height map. The compared canopy height estimates were obtained by: (1) a stem diameter at breast height (D) - tree height (H) relationship specific to each site on the basis of our original field study, (2) a previously developed D-H model involving environmental and structural factors as explanatory variables (Feldpausch et al., 2011), and (3) a previously developed canopy height map derived from the spaceborne LiDAR data with different spatial modeling method and explanatory variables (Simard et al., 2011). As a result, our canopy height map successfully detected a spatial distribution pattern in canopy height estimates based on our original field study data (r = 0.845, p = 8.31 × 10-3) though our canopy height map showed a poor correlation (r = 0.563, p = 0.146) with the canopy height estimate based on a previously developed model by Feldpausch et al. (2011). We also confirmed that the created canopy height map showed a similar pattern with the previously developed canopy height map by Simard et al. (2011). It was concluded that the use of the spaceborne LiDAR data provides a sufficient accuracy in estimating the canopy height at regional scale.

  7. 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,…

  8. 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...

  9. 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,…

  10. US Forest Service Public Land Survey System Sections

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting areas defined by the Public Lands Survey System Grid. Normally, 36 sections make up a township. Sections cover US Forest Service...

  11. US Forest Service Purchase Units under the Weeks Law

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting units designated by the Secretary of Agriculture or previously approved by the National Forest Reservation Commission for purposes...

  12. US Forest Service Roadless Areas: Colorado Roadless Rule

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service, available on the www that depicts the boundaries of Roadless Areas designated by the Colorado Roadless Rule of 2012 and managed by the US Forest...

  13. US Forest Service Land and Water Conservation Fund Projects

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www that displays LWCF projects for the Bureau of Land Management (BLM), U.S. Forest Service (USFS), National Park Service (NPS), and U.S. Fish...

  14. Survey Boundaries maintained by the US Forest Service

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting surface management agency lines which are the surveyed boundary lines for which the Forest Service is responsible for making and...

  15. US Forest Service Aerial Fire Retardant Avoidance Areas: Terrestrial

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service depicting aerial fire retardant avoidance areas delivered as part of the 2011 Nationwide Aerial Application of Fire Retardant on National Forest System...

  16. 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

  17. Forest Resource Information System (FRIS)

    Science.gov (United States)

    1983-01-01

    The technological and economical feasibility of using multispectral digital image data as acquired from the LANDSAT satellites in an ongoing operational forest information system was evaluated. Computer compatible multispectral scanner data secured from the LANDSAT satellites were demonstrated to be a significant contributor to ongoing information systems by providing the added dimensions of synoptic and repeat coverage of the Earth's surface. Major forest cover types of conifer, deciduous, mixed conifer-deciduous and non-forest, were classified well within the bounds of the statistical accuracy of the ground sample. Further, when overlayed with existing maps, the acreage of cover type retains a high level of positional integrity. Maps were digitized by a graphics design system, overlayed and registered onto LANDSAT imagery such that the map data with associated attributes were displayed on the image. Once classified, the analysis results were converted back to map form as a cover type of information. Existing tabular information as represented by inventory is registered geographically to the map base through a vendor provided data management system. The notion of a geographical reference base (map) providing the framework to which imagery and tabular data bases are registered and where each of the three functions of imagery, maps and inventory can be accessed singly or in combination is the very essence of the forest resource information system design.

  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 great importance for the d

  19. 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.

  20. Spatial pattern and compositive structure of forests in Guizhou

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Remote-sensing and field data of Guizhou forest resources in 2000 are processed usingArcGIS, with the production of forest resource distribution map, forest age class structure map, andforest canopy distribution map. Analysis of these data shows that: (1) though there are multiple typesof forest resources, forest coverage is low (only 25.27%, excluding sparse woodland, shrub andunderage-forest); (2) the geographical distribution of forests is quite uneven, mainly in the southeastof the province and in Zunyi prefecture; (3) the zonal evergreen broad-leaved forests have beenseriously destroyed, with striking secondary features, i.e., coniferous forest and shrubbery account forthe greatest proportion of Guizhou forests; (4) the timber-forest is much larger in area thanshelter-forest and economic forest; (5) young-and-middle aged forests are more widely distributed thannear-and-over matured forest; and (6) the forest of Guizhou is not enough to effectively protect theenvironment of karst mountain areas of the province.

  1. Evaluating differences in forest fragmentation and restoration between western natural forests and southeastern plantation forests in the United States.

    Science.gov (United States)

    Ren, Xinyu; Lv, Yingying; Li, Mingshi

    2017-03-01

    Changes in forest ecosystem structure and functions are considered some of the research issues in landscape ecology. In this study, advancing Forman's theory, we considered five spatially explicit processes associated with fragmentation, including perforation, dissection, subdivision, shrinkage, and attrition, and two processes associated with restoration, i.e., increment and expansion processes. Following this theory, a forest fragmentation and restoration process model that can detect the spatially explicit processes and ecological consequences of forest landscape change was developed and tested in the current analysis. Using the National Land Cover Databases (2001, 2006 and 2011), the forest fragmentation and restoration process model was applied to US western natural forests and southeastern plantation forests to quantify and classify forest patch losses into one of the four fragmentation processes (the dissection process was merged into the subdivision process) and to classify the newly gained forest patches based on the two restoration processes. At the same time, the spatio-temporal differences in fragmentation and restoration patterns and trends between natural forests and plantations were further compared. Then, through overlaying the forest fragmentation/restoration processes maps with targeting year land cover data and land ownership vectors, the results from forest fragmentation and the contributors to forest restoration in federal and nonfederal lands were identified. Results showed that, in natural forests, the forest change patches concentrated around the urban/forest, cultivated/forest, and shrubland/forest interfaces, while the patterns of plantation change patches were scattered sparsely and irregularly. The shrinkage process was the most common type in forest fragmentation, and the average size was the smallest. Expansion, the most common restoration process, was observed in both natural forests and plantations and often occurred around the

  2. Forest Histories & Forest Futures

    OpenAIRE

    Whitlock, Cathy

    2009-01-01

    The climate changes projected for the future will have significant consequences for forest ecosystems and our ability to manage them. It is reasonable to ask: Are there historical precedents that help us understand what might happen in the future or are historical perspectives becoming irrelevant? What synergisms and feedbacks might be expected between rapidly changing climate and land–use in different settings, especially at the wildland–urban interface? What lessons from the past might help...

  3. Softwood distribution maps for the South

    Science.gov (United States)

    Paul L. Janssen; Melvin R. Weiland

    1960-01-01

    The maps in this report describe the relative concentration as well as the approximate range of 11 softwoods in 12 southern states--extending from the Atlantic Coast westward to about the 96th meridian in Oklahoma and Texas. The data upon which the maps are based were gathered during 1947-57 by the Forest Surveys of the Southern and Southeastern Forest Experiment...

  4. Forest Resources

    Energy Technology Data Exchange (ETDEWEB)

    None

    2016-06-01

    Forest biomass is an abundant biomass feedstock that complements the conventional forest use of wood for paper and wood materials. It may be utilized for bioenergy production, such as heat and electricity, as well as for biofuels and a variety of bioproducts, such as industrial chemicals, textiles, and other renewable materials. The resources within the 2016 Billion-Ton Report include primary forest resources, which are taken directly from timberland-only forests, removed from the land, and taken to the roadside.

  5. Mapping the Distribution of Woodlands in Shangri -LaBased on Forest Management Inventory%基于二类调查数据的香格里拉林地分布制图

    Institute of Scientific and Technical Information of China (English)

    芦珊; 舒清态; 栗业

    2014-01-01

    Taking Shangri -La as an example ,this article uses ArcGIS to accomplish forestry distribution drawing which is based on the data of forest management inventory .And it also introduces the mapping process and all the details which should be paid attention to .The practices show that ArcGIS is a powerful cartographic software which is easy to operate ,and it has incomparable advantages in forestry mapping .%以香格里拉县为例,利用A rcGIS软件并以林业“二类”调查数据为基础进行了林地分布制图,最终形成了香格里拉县林地分布图,详细探讨了制图过程及应注意的细节问题,实践证明了 ArcGIS软件制图功能强大,且操作方便易学,在林业制图中有无可比拟的强大优势。

  6. Northern Forest Ecosystem Dynamics Using Coupled Models and Remote Sensing

    Science.gov (United States)

    Ranson, K. J.; Sun, G.; Knox, R. G.; Levine, E. R.; Weishampel, J. F.; Fifer, S. T.

    1999-01-01

    Forest ecosystem dynamics modeling, remote sensing data analysis, and a geographical information system (GIS) were used together to determine the possible growth and development of a northern forest in Maine, USA. Field measurements and airborne synthetic aperture radar (SAR) data were used to produce maps of forest cover type and above ground biomass. These forest attribute maps, along with a conventional soils map, were used to identify the initial conditions for forest ecosystem model simulations. Using this information along with ecosystem model results enabled the development of predictive maps of forest development. The results obtained were consistent with observed forest conditions and expected successional trajectories. The study demonstrated that ecosystem models might be used in a spatial context when parameterized and used with georeferenced data sets.

  7. Methodology to assess and map the potential development of forest ecosystems exposed to climate change and atmospheric nitrogen deposition: A pilot study in Germany.

    Science.gov (United States)

    Schröder, Winfried; Nickel, Stefan; Jenssen, Martin; Riediger, Jan

    2015-07-15

    A methodology for mapping ecosystems and their potential development under climate change and atmospheric nitrogen deposition was developed using examples from Germany. The methodology integrated data on vegetation, soil, climate change and atmospheric nitrogen deposition. These data were used to classify ecosystem types regarding six ecological functions and interrelated structures. Respective data covering 1961-1990 were used for reference. The assessment of functional and structural integrity relies on comparing a current or future state with an ecosystem type-specific reference. While current functions and structures of ecosystems were quantified by measurements, potential future developments were projected by geochemical soil modelling and data from a regional climate change model. The ecosystem types referenced the potential natural vegetation and were mapped using data on current tree species coverage and land use. In this manner, current ecosystem types were derived, which were related to data on elevation, soil texture, and climate for the years 1961-1990. These relations were quantified by Classification and Regression Trees, which were used to map the spatial patterns of ecosystem type clusters for 1961-1990. The climate data for these years were subsequently replaced by the results of a regional climate model for 1991-2010, 2011-2040, and 2041-2070. For each of these periods, one map of ecosystem type clusters was produced and evaluated with regard to the development of areal coverage of ecosystem type clusters over time. This evaluation of the structural aspects of ecological integrity at the national level was added by projecting potential future values of indicators for ecological functions at the site level by using the Very Simple Dynamic soil modelling technique based on climate data and two scenarios of nitrogen deposition as input. The results were compared to the reference and enabled an evaluation of site-specific ecosystem changes over time

  8. 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)

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

    2017-01-01

    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...

  9. Evaluation and Comparison of QuickBird and ADS40-SH52 Multispectral Imagery for Mapping Iberian Wild Pear Trees (Pyrus bourgaeana, Decne in a Mediterranean Mixed Forest

    Directory of Open Access Journals (Sweden)

    Salvador Arenas-Castro

    2014-06-01

    Full Text Available The availability of images with very high spatial and spectral resolution from airborne sensors or those aboard satellites is opening new possibilities for the analysis of fine-scale vegetation, such as the identification and classification of individual tree species. To evaluate the potential of these images, a study was carried out to compare the spatial, spectral and temporal resolution between QuickBird and ADS40-SH52 imagery, in order to discriminate and identify, within the mixed Mediterranean forest, individuals of the Iberian wild pear (Pyrus bourgaeana. This is a typical species of the Mediterranean forest, but its biology and ecology are still poorly known. The images were subjected to different correction processes and data were homogenized. Vegetation classes and individual trees were identified on the images, which were classified from two types of supervised classification (Maximum Likelihood and Support Vector Machines on a pixel-by-pixel basis. The classification values were satisfactory. The classifiers were compared, and Support Vector Machines was the algorithm that provided the best results in terms of overall accuracy. The QuickBird image showed higher overall accuracy (86.16% when the Support Vector Machines algorithm was applied. In addition, individuals of Iberian wild pear were discriminated with probability of over 55%, when the Maximum Likelihood algorithm was applied. From the perspective of improving the sampling effort, these results are a starting point for facilitating research on the abundance, distribution and spatial structure of P. bourgaeana at different scales, in order to quantify the conservation status of this species.

  10. US Forest Service National Wild and Scenic Rivers

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting areas designated as Wild and Scenic Rivers. This map service provides display, identification, and analysis tools for determining...

  11. US Forest Service Tribal Lands Ceded to the United States

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www that depicts sixty-seven maps from Royce’s 1897 report that have been scanned, georeferenced in JPEG2000 format, and digitized to create...

  12. US Forest Service Ranger District Boundaries (With Regions Table)

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting the boundary that encompasses a Ranger District. This map service provides display, identification, and analysis tools for...

  13. US Forest Service Wild and Scenic Rivers: Legal Status

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting the status of areas designated as Wild and Scenic Rivers. This map service provides display, identification, and analysis tools...

  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. 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; Borys M. Tkacz

    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...

  16. US Forest Service LANDFIRE Existing Vegetation

    Data.gov (United States)

    US Forest Service, Department of Agriculture — LANDFIRE Existing Vegetation is mapped using predictive landscape models based on extensive field-referenced data, satellite imagery and biophysical gradient layers...

  17. US Forest Service Brush Disposal Funded Activities

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www that depicts the area of activities funded through BDBD and PPPP budget line item and reported through the FACTS database. The objective of...

  18. US Forest Service Current Invasive Plants Inventory

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting the most recent measurement of Invasive Plant Infestation polygons collected by the National Invasive Plant Inventory Protocol....

  19. US Forest Service LANDFIRE Historical Fire Regimes

    Data.gov (United States)

    US Forest Service, Department of Agriculture — Historical fire regimes, intervals, and vegetation conditions are mapped using the Vegetation Dynamics Development Tool (VDDT). These data support fire and landscape...

  20. US Forest Service Other Surface Right

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting areas with a right to a surface resource, excluding rights of way. The purpose of the data is to provide display, identification,...

  1. US Forest Service Right of Way

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting areas with a privilege to pass over the land of another in some particular path; usually an easement over the land of another; a...

  2. US Forest Service Surface Drinking Water Importance

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting watershed indexes to help identify areas of interest for protecting surface drinking water quality. The dataset depicted in this...

  3. US Forest Service Periodical Cicada Broods

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting periodical cicada distribution and expected year of emergence by cicada brood and county. The periodical cicada emerges in massive...

  4. US Forest Service Hazardous Fuel Treatment Reduction

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting select activities that help reduce hazardous fuels on the landscape. This includes features representing Rx Fire, Wildfire,...

  5. US Forest Service Surface Ownership Parcels, detailed

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting ownership parcels of the surface estate. Each surface ownership parcel is tied to a particular legal transaction. The same...

  6. US Forest Service National Grassland Units

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting National Grassland units designated by the Secretary of Agriculture and permanently held by the Department of Agriculture under...

  7. US Forest Service Corners and Monuments

    Data.gov (United States)

    US Forest Service, Department of Agriculture — A map service on the www depicting land survey points from a GCDB LX file, survey plat, or captured from a CFF land net coverage. Includes points generated by...

  8. Arkansas, 2009 forest inventory and analysis factsheet

    Science.gov (United States)

    James F. Rosson

    2011-01-01

    The summary includes estimates of forest land area (table 1), ownership (table 2), forest-type groups (table 3), volume (tables 4 and 5), biomass (tables 6 and 7), and pine plantation area (table 8) along with maps of Arkansas’ survey units (fig. 1), percent forest by county (fig. 2), and distribution of pine plantations (fig. 3). The estimates are presented by survey...

  9. Burned Area Mapping in the North American Boreal Forest Using Terra-MODIS LTDR (2001–2011: A Comparison with the MCD45A1, MCD64A1 and BA GEOLAND-2 Products

    Directory of Open Access Journals (Sweden)

    José Andrés Moreno Ruiz

    2014-01-01

    Full Text Available An algorithm based on a Bayesian network classifier was adapted to produce 10-day burned area (BA maps from the Long Term Data Record Version 3 (LTDR at a spatial resolution of 0.05° (~5 km for the North American boreal region from 2001 to 2011. The modified algorithm used the Brightness Temperature channel from the Moderate Resolution Imaging Spectroradiometer (MODIS band 31 T31 (11.03 μm instead of the Advanced Very High Resolution Radiometer (AVHRR band T3 (3.75 μm. The accuracy of the BA-LTDR, the Collection 5.1 MODIS Burned Area (MCD45A1, the MODIS Collection 5.1 Direct Broadcast Monthly Burned Area (MCD64A1 and the Burned Area GEOLAND-2 (BA GEOLAND-2 products was assessed using reference data from the Alaska Fire Service (AFS and the Canadian Forest Service National Fire Database (CFSNFD. The linear regression analysis of the burned area percentages of the MCD64A1 product using 40 km × 40 km grids versus the reference data for the years from 2001 to 2011 showed an agreement of R2 = 0.84 and a slope = 0.76, while the BA-LTDR showed an agreement of R2 = 0.75 and a slope = 0.69. These results represent an improvement over the MCD45A1 product, which showed an agreement of R2 = 0.67 and a slope = 0.42. The MCD64A1, BA-LTDR and MCD45A1 products underestimated the total burned area in the study region, whereas the BA GEOLAND-2 product overestimated it by approximately five-fold, with an agreement of R2 = 0.05. Despite MCD64A1 showing the best overall results, the BA-LTDR product proved to be an alternative for mapping burned areas in the North American boreal forest region compared with the other global BA products, even those with higher spatial/spectral resolution.

  10. Mangrove Blue Carbon stocks and change estimation from PolInSAR, Lidar and High Resolution Stereo Imagery combined with Forest Cover change mapping

    Science.gov (United States)

    Zalles, V.; Fatoyinbo, T. E.; Simard, M.; Lagomasino, D.; Lee, S. K.; Trettin, C.; Feliciano, E. A.; Hansen, M.; John, P.

    2015-12-01

    Mangroves and tidal wetlands have the highest carbon density among terrestrial ecosystems. Although they only represent 3 % of the total forest area (or 0.01 % of land area), C emissions from mangrove destruction alone at current rates could be equivalent to 10 % of carbon emissions from deforestation. One of the main challenges to implementing carbon mitigation projects is measuring carbon, efficiently, effectively, and safely. In mangroves especially, the extreme difficulty of the terrain has hindered the establishment of sufficient field plots needed to accurately measure carbon on the scale necessary to relate remotely sensed measurements with field measurements at accuracies required for REDD and other C trading mechanisms. In this presentation we will showcase the methodologies for, and the remote sensing products necessary to implement MRV (monitoring, reporting and verification) systems in Coastal Blue Carbon ecosystems. Specifically, we will present new methods to estimate aboveground biomass stocks and change in mangrove ecosystems using remotely sensed data from Interferometric SAR from the TanDEM-X mission, commercial airborne Lidar, High Resolution Stereo-imagery, and timeseries analysis of Landsat imagery in combination with intensive field measurements of above and belowground carbon stocks. Our research is based on the hypothesis that by combining field measurements, commercial airborne Lidar, optical and Pol-InSAR data, we are able to estimate Mangrove blue carbon storage with an error under 20% at the project level and permit the evaluation of UNFCCC mechanisms for the mitigation of carbon emissions from coastal ecosystems.

  11. 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...

  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. Spatially explicit forest characteristics of Europe through integrating Forest Inventory and Remotely sensed data

    Science.gov (United States)

    Moreno, Adam; Neumann, Mathias; Hasenauer, Hubert

    2015-04-01

    Carbon stock estimates are critical for any carbon trading scheme or climate change mitigation strategy. Understanding the carbon allocation and the structure of its ecosystem further help scientists and policy makers develop realistic plans for utilizing these systems. Forests play an important role in global carbon storage. Therefore it is imperative to include forests in any climate change mitigation and/or carbon trading scheme. Currently there is no estimate of forest carbon stocks and allocation nor forest structure maps throughout Europe. We compiled National Forest Inventory (NFI) data from 12 European countries. We integrated the NFI data with Net Primary Production data (NPP) from Moderate Resolution Imaging Spectroradiometer (MODIS), tree height data from Light Detection and Ranging (LIDAR) data from the Geosciences Laser Altimeter System (GLAS) instrument, and various other spatially explicit data sets. Through this process of integration of terrestrial and space based data we produced wall-to-wall forest characteristics maps of Europe. These maps include forest age, basal area, average diameter at breast height, total carbon, carbon allocation (stem, branches, leaves, roots), and other characteristics derived from forest inventory data. These maps cover Europe - including countries without terrestrial data - and give one coherent harmonized data set of current forest structure and carbon storage on a 16x16km resolution. The methodology presented here has the potential to be used world-wide in regions with data limitations or with limited access to data.

  14. A comparison of Gridded Quantile Mapping vs. Station Based Downscaling Approaches on Potential Hydrochemical Responses of Forested Watersheds to Climate Change Using a Dynamic Biogeochemical Model (PnET-BGC)

    Science.gov (United States)

    Pourmokhtarian, A.; Driscoll, C. T.; Campbell, J. L.; Hayhoe, K.

    2012-12-01

    Dynamic hydrochemical models are useful tools to understand and predict the interactive effects of climate change, atmospheric CO2, and atmospheric deposition on the hydrology and water quality of forested watersheds. Although application of these models for climate projections necessitates the use of climatic variables simulated by atmosphere-ocean general circulation models (AOGCMs) to determine inputs to drive model projections. Due to the coarse resolution of AOGCMs, outputs need to be downscaled to bridge the gap between coarse spatial resolution and higher resolution required for hydrochemical models. This research compares two different statistical downscaling approaches; Gridded Quantile Mapping (BCSD) and Station-based Daily Asynchronous Regression, and their effects on potential biogeochemical responses of forested watershed. In this study, we used the biogeochemical model, PnET-BGC, to assess, compare and contrast the effects of these two downscaling approaches on potential future changes in temperature, precipitation, solar radiation and atmospheric CO2 and their effects in projections of pools, concentrations, and fluxes of major elements at Hubbard Brook Experimental Forest in New Hampshire, U.S. Future emissions scenarios were developed from monthly output from three AOGCMs (HadCM3, GFDL, PCM) in conjunction with potential lower and upper bounds of projected atmospheric CO2 (550 and 970 ppm by 2099, respectively). The climate projections from both downscaling approaches indicate that over the 21st century, average air temperature will increase with simultaneous increases in annual average precipitation. The modeling results from both downscaling approaches suggest that climate change is projected to cause substantial temporal shifts in hydrologic and hydrochemistry patterns. The choice of downscaling approach had a major impact on the streamflow simulations, which was directly related to the ability of the downscaling approach to mimic observed

  15. 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.

  16. 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.

  17. Texas' forests, 2008

    Science.gov (United States)

    James W. Bentley; Consuelo Brandeis; Jason A. Cooper; Christopher M. Oswalt; Sonja N. Oswalt; KaDonna Randolph

    2014-01-01

    This bulletin describes forest resources of the State of Texas at the time of the 2008 forest inventory. This bulletin addresses forest area, volume, growth, removals, mortality, forest health, timber product output, and the economy of the forest sector.