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

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

Science.gov (United States)

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

2018-05-01

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

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.

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.

Mapping Russian forest biomass with data from satellites and forest inventories

International Nuclear Information System (INIS)

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

2007-01-01

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

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.

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

Science.gov (United States)

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

2015-04-01

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

Urban forest topographical mapping using UAV LIDAR

Science.gov (United States)

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

2017-12-01

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

Assessment and Mapping of Forest Parcel Sizes

Science.gov (United States)

Brett J. Butler; Susan L. King

2005-01-01

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

Mapping the Distribution of Cloud Forests Using MODIS Imagery

Science.gov (United States)

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

2007-05-01

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

Idaho forest carbon projections from 2017 to 2117 under forest disturbance and climate change scenarios

Science.gov (United States)

Hudak, A. T.; Crookston, N.; Kennedy, R. E.; Domke, G. M.; Fekety, P.; Falkowski, M. J.

2017-12-01

Commercial off-the-shelf lidar collections associated with tree measures in field plots allow aboveground biomass (AGB) estimation with high confidence. Predictive models developed from such datasets are used operationally to map AGB across lidar project areas. We use a random selection of these pixel-level AGB predictions as training for predicting AGB annually across Idaho and western Montana, primarily from Landsat time series imagery processed through LandTrendr. At both the landscape and regional scales, Random Forests is used for predictive AGB modeling. To project future carbon dynamics, we use Climate-FVS (Forest Vegetation Simulator), the tree growth engine used by foresters to inform forest planning decisions, under either constant or changing climate scenarios. Disturbance data compiled from LandTrendr (Kennedy et al. 2010) using TimeSync (Cohen et al. 2010) in forested lands of Idaho (n=509) and western Montana (n=288) are used to generate probabilities of disturbance (harvest, fire, or insect) by land ownership class (public, private) as well as the magnitude of disturbance. Our verification approach is to aggregate the regional, annual AGB predictions at the county level and compare them to annual county-level AGB summarized independently from systematic, field-based, annual inventories conducted by the US Forest Inventory and Analysis (FIA) Program nationally. This analysis shows that when federal lands are disturbed the magnitude is generally high and when other lands are disturbed the magnitudes are more moderate. The probability of disturbance in corporate lands is higher than in other lands but the magnitudes are generally lower. This is consistent with the much higher prevalence of fire and insects occurring on federal lands, and greater harvest activity on private lands. We found large forest carbon losses in drier southern Idaho, only partially offset by carbon gains in wetter northern Idaho, due to anticipated climate change. Public and

Tropical forest carbon assessment: integrating satellite and airborne mapping approaches

International Nuclear Information System (INIS)

Asner, Gregory P

2009-01-01

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

Mapping of forest disturbance magnitudes across the US National Forest System

Science.gov (United States)

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

2013-12-01

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

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...

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.

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

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-12-31

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

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

Projective mapping

DEFF Research Database (Denmark)

Dehlholm, Christian; Brockhoff, Per B.; Bredie, Wender Laurentius Petrus

2012-01-01

by the practical testing environment. As a result of the changes, a reasonable assumption would be to question the consequences caused by the variations in method procedures. Here, the aim is to highlight the proven or hypothetic consequences of variations of Projective Mapping. Presented variations will include...... instructions and influence heavily the product placements and the descriptive vocabulary (Dehlholm et.al., 2012b). The type of assessors performing the method influences results with an extra aspect in Projective Mapping compared to more analytical tests, as the given spontaneous perceptions are much dependent......Projective Mapping (Risvik et.al., 1994) and its Napping (Pagès, 2003) variations have become increasingly popular in the sensory field for rapid collection of spontaneous product perceptions. It has been applied in variations which sometimes are caused by the purpose of the analysis and sometimes...

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.

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.

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.

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...

VT Green Mountain National Forest Map - Southern Section

Data.gov (United States)

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

Uncertainties in mapping forest carbon in urban ecosystems.

Science.gov (United States)

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

2017-02-01

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

The Southern Forest Futures Project: technical report

Science.gov (United States)

David N. Wear; John G. Greis

2013-01-01

Please visit the Southern Forest Futures Project website for more information.The Southern Forest Futures Project provides a science-based “futuring” analysis of the forests of the 13 States of the Southeastern United States. With findings...

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

Directory of Open Access Journals (Sweden)

K. M. Kim

2016-06-01

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

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

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

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

2014-05-07

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

Mapping forest canopy disturbance in the Upper Great Lakes, USA

Science.gov (United States)

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

2015-01-01

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

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

African Journals Online (AJOL)

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

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

Science.gov (United States)

Elizabeth A. Freeman; Gretchen G. Moisen

2007-01-01

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

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.

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.

Historical satellite data used to map Pan-Amazon forest cover

Science.gov (United States)

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

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

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

Directory of Open Access Journals (Sweden)

Warren B. Cohen

2017-03-01

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

Transfer maps and projection formulas

OpenAIRE

Tabuada, Goncalo

2010-01-01

Transfer maps and projection formulas are undoubtedly one of the key tools in the development and computation of (co)homology theories. In this note we develop an unified treatment of transfer maps and projection formulas in the non-commutative setting of dg categories. As an application, we obtain transfer maps and projection formulas in algebraic K-theory, cyclic homology, topological cyclic homology, and other scheme invariants.

78 FR 38287 - Bitterroot National Forest, Darby Ranger District, Como Forest Health Project

Science.gov (United States)

2013-06-26

... DEPARTMENT OF AGRICULTURE Forest Service Bitterroot National Forest, Darby Ranger District, Como Forest Health Project AGENCY: Forest Service. ACTION: Notice; Correction. SUMMARY: The Department of Agriculture (USDA), Forest Service, Bitterroot National Forest, Darby Ranger District published a document in...

The Southern Forest Futures Project: summary report

Science.gov (United States)

David N. Wear; John G. Greis

2012-01-01

The Southern Forest Futures Project provides a science-based “futuring” analysis of the forests of the 13 States of the Southeastern United States. With findings organized in a set of scenarios and using a combination of computer models and science synthesis, the authors of the Southern Forest Futures Project examine a variety of possible futures that could shape...

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

Science.gov (United States)

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

2015-12-01

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

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.

Participatory forest management in Ethiopia: learning from pilot projects.

Science.gov (United States)

Ameha, Aklilu; Larsen, H O; Lemenih, Mulugeta

2014-04-01

Different arrangements of decentralized forest management have been promoted as alternatives to centralized and top down approaches to halt tropical deforestation and forest degradation. Ethiopia is one of the countries piloting one of these approaches. To inform future programs and projects it is essential to learn from existing pilots and experiences. This paper analyses five of the pilot participatory forest management (PFM) programs undertaken in Ethiopia. The study is based on the Forest User Group (FUG) members' analyses of the programs using selected outcome variables: forest income, change in forest conditions, forest ownership feelings and effectiveness of FUGs as forest managing institutions. These variables were assessed at three points in time-before the introduction of PFM, during the project implementation and after the projects ended. Data were collected using group discussions, key informant interviews and transect walks through the PFM forests. The results show that in all of the five cases the state of the forest is perceived to have improved with the introduction of PFM, and in four of the cases the improvement was maintained after projects ended. Regulated access to the forests following introduction of PFM was not perceived to have affected forest income negatively. There are, however, serious concerns about the institutional effectiveness of the FUGs after projects ended, and this may affect the success of the PFM approach in the longer term.

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

Science.gov (United States)

Gu, Huan

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

76 FR 70955 - Helena Nation Forest: Dalton Mountain Forest Restoration & Fuels Reduction Project

Science.gov (United States)

2011-11-16

... DEPARTMENT OF AGRICULTURE Forest Service Helena Nation Forest: Dalton Mountain Forest Restoration & Fuels Reduction Project AGENCY: Forest Service, USDA. ACTION: Notice of intent to prepare an environmental impact statement. SUMMARY: The Helena National Forest (HNF) is proposing on the Lincoln Ranger...

Map projections cartographic information systems

CERN Document Server

Grafarend, Erik W; Syffus, Rainer

2014-01-01

This book offers a timely review of map projections including sphere, ellipsoid, rotational surfaces, and geodetic datum transformations. Coverage includes computer vision, and remote sensing space projective mappings in photogrammetry.

Mapping of forest types confined to the lay of land

Directory of Open Access Journals (Sweden)

S. K. Farber

2018-04-01

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

A large-scale forest fragmentation experiment: the Stability of Altered Forest Ecosystems Project

Science.gov (United States)

Ewers, Robert M.; Didham, Raphael K.; Fahrig, Lenore; Ferraz, Gonçalo; Hector, Andy; Holt, Robert D.; Kapos, Valerie; Reynolds, Glen; Sinun, Waidi; Snaddon, Jake L.; Turner, Edgar C.

2011-01-01

Opportunities to conduct large-scale field experiments are rare, but provide a unique opportunity to reveal the complex processes that operate within natural ecosystems. Here, we review the design of existing, large-scale forest fragmentation experiments. Based on this review, we develop a design for the Stability of Altered Forest Ecosystems (SAFE) Project, a new forest fragmentation experiment to be located in the lowland tropical forests of Borneo (Sabah, Malaysia). The SAFE Project represents an advance on existing experiments in that it: (i) allows discrimination of the effects of landscape-level forest cover from patch-level processes; (ii) is designed to facilitate the unification of a wide range of data types on ecological patterns and processes that operate over a wide range of spatial scales; (iii) has greater replication than existing experiments; (iv) incorporates an experimental manipulation of riparian corridors; and (v) embeds the experimentally fragmented landscape within a wider gradient of land-use intensity than do existing projects. The SAFE Project represents an opportunity for ecologists across disciplines to participate in a large initiative designed to generate a broad understanding of the ecological impacts of tropical forest modification. PMID:22006969

A large-scale forest fragmentation experiment: the Stability of Altered Forest Ecosystems Project.

Science.gov (United States)

Ewers, Robert M; Didham, Raphael K; Fahrig, Lenore; Ferraz, Gonçalo; Hector, Andy; Holt, Robert D; Kapos, Valerie; Reynolds, Glen; Sinun, Waidi; Snaddon, Jake L; Turner, Edgar C

2011-11-27

Opportunities to conduct large-scale field experiments are rare, but provide a unique opportunity to reveal the complex processes that operate within natural ecosystems. Here, we review the design of existing, large-scale forest fragmentation experiments. Based on this review, we develop a design for the Stability of Altered Forest Ecosystems (SAFE) Project, a new forest fragmentation experiment to be located in the lowland tropical forests of Borneo (Sabah, Malaysia). The SAFE Project represents an advance on existing experiments in that it: (i) allows discrimination of the effects of landscape-level forest cover from patch-level processes; (ii) is designed to facilitate the unification of a wide range of data types on ecological patterns and processes that operate over a wide range of spatial scales; (iii) has greater replication than existing experiments; (iv) incorporates an experimental manipulation of riparian corridors; and (v) embeds the experimentally fragmented landscape within a wider gradient of land-use intensity than do existing projects. The SAFE Project represents an opportunity for ecologists across disciplines to participate in a large initiative designed to generate a broad understanding of the ecological impacts of tropical forest modification.

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.

Coordinate systems and map projections

CERN Document Server

Maling, DH

1992-01-01

A revised and expanded new edition of the definitive English work on map projections. The revisions take into account the huge advances in geometrical geodesy which have occurred since the early years of satellite geodesy. The detailed configuration of the geoid resulting from the GEOS and SEASAT altimetry measurements are now taken into consideration. Additionally, the chapter on computation of map projections is updated bearing in mind the availability of pocket calculators and microcomputers. Analytical derivation of some map projections including examples of pseudocylindrical and polyconic

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.

Economics of forest and forest carbon projects. Translating lessons learned into national REDD+ implementation

Energy Technology Data Exchange (ETDEWEB)

Zaballa Romero, M.; Traerup, S.; Wieben, E.; Ravnkilde Moeller, L.; Koch, A.

2013-01-15

The financial implications of implementing a new forest management paradigm have not been well understood and have often been underestimated. Resource needs for e.g., stakeholder consultation, capacity building and addressing the political economy are seldom fully accounted for in the resource needs estimates put forward in connection to REDD+. This report investigates the economics of implementing forest and REDD+ projects through eight case studies from Africa, Latin America and Asia, analyzing real forest and REDD+ investments. The report is part of efforts to share financial experiences and lessons learned with policymakers, project developers and stakeholders, with the objective to inform forest project and strategy development. It presents experiences and advice on the risks, costs and revenues of forest projects, thereby informing not only the development of future REDD+ initiatives but also the testing of advanced market commitments as a finance option for sustainable forest management. The findings in the report underline the fact that only through sound and transparent financial information will forest projects and national forest initiatives become interesting for private financial institutions and comparable with other investment opportunities. It is therefore important to include robust analysis of the operations business case and its financial attractiveness to commercial investors, early in the design process. As for the economics of forest and forest carbon projects, it appears that REDD+ payments alone, especially at current prices, will not deliver the revenues that cover all expenses of transparent and long-term mitigation of forest carbon emissions. Instead the findings underline the importance of building up forest operations which effectively manages risk and delivers several revenue streams. These findings are aligned with the advocacy efforts of UNEP and the UN-REDD Programme on multiple benefits and the combination of various funding and

Map projections cartographic information systems

CERN Document Server

Grafarend, Erik W

2006-01-01

In the context of Geographical Information Systems (GIS) the book offers a timely review of map projections (sphere, ellipsoid, rotational surfaces) and geodetic datum transformations. For the needs of photogrammetry, computer vision, and remote sensing space projective mappings are reviewed.

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

International Nuclear Information System (INIS)

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

1998-01-01

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

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

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

Science.gov (United States)

Lin, T.; Laporte, N. T.

2003-12-01

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

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

Science.gov (United States)

Turlej, K.; Radeloff, V.

2017-12-01

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

Understanding map projections: Chapter 15

Science.gov (United States)

Usery, E. Lynn; Kent, Alexander J.; Vujakovic, Peter

2018-01-01

It has probably never been more important in the history of cartography than now that people understand how maps work. With increasing globalization, for example, world maps provide a key format for the transmission of information, but are often poorly used. Examples of poor understanding and use of projections and the resultant maps are many; for instance, the use of rectangular world maps in the United Kingdom press to show Chinese and Korean missile ranges as circles, something which can only be achieved on equidistant projections and then only from one launch point (Vujakovic, 2014).

The projective heat map

CERN Document Server

Schwartz, Richard Evan

2017-01-01

This book introduces a simple dynamical model for a planar heat map that is invariant under projective transformations. The map is defined by iterating a polygon map, where one starts with a finite planar N-gon and produces a new N-gon by a prescribed geometric construction. One of the appeals of the topic of this book is the simplicity of the construction that yet leads to deep and far reaching mathematics. To construct the projective heat map, the author modifies the classical affine invariant midpoint map, which takes a polygon to a new polygon whose vertices are the midpoints of the original. The author provides useful background which makes this book accessible to a beginning graduate student or advanced undergraduate as well as researchers approaching this subject from other fields of specialty. The book includes many illustrations, and there is also a companion computer program.

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.

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

Directory of Open Access Journals (Sweden)

Liang Xu

2016-08-01

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

Mapping of Shorea robusta Forest Using Time Series MODIS Data

NARCIS (Netherlands)

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

2017-01-01

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

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.

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.

Small forest cuttings mapped with Landsat digital data

Science.gov (United States)

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

1979-01-01

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

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

International Nuclear Information System (INIS)

Policnik, Helena; Simoncic, Primoz; Batic, Franc

2008-01-01

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

Forest energy project in Central Finland; Keski-Suomen metsaeenergia -projekti

Energy Technology Data Exchange (ETDEWEB)

Ahokas, M [Association of Central Finland, Jyvaeskylae (Finland); Kuitto, P J [VTT Energy, Jyvaeskylae (Finland)

1997-12-31

The Forest Energy Project of Central Finland is one of the topleading regional demonstration project in Finland for testing and studying of the complete energy wood delivery chains and energy wood utilization. It is a large development and technology transfer venture concentrated primarily on practical needs. Total delivery chains are formed of the best machine and method alternatives, and they are also demonstrated. The project offers hence a wide test field for regional and national techno/economical wood fuel development. The target of this provincial project is to collect and demonstrate the most promising energy wood procurement technologies and methods for utilization of energy producers, forest industry and small and medium sized industries co-operating with forest owners, contractors and forest organizations. An essential target of the project is to direct the know-how, concentrated in the project, to development of the energy field. The project is directed to international information delivery, to concrete widening of cooperation, on transfer of testing and training activities and utilization experiences in the field of wood energy. The Forest Energy Project of Central Finland is a demonstration project supervised by the Regional Council of Central Finland. The project is a part of the national Bioenergy Research Programme. A large number of provincial partners interested in wood fuels, e.g. energy wood suppliers, energy producers, communes, forest industry, forestry boards, forestry associations, wood delivery contractors, and equipment producers, take part in the project

Forest energy project in Central Finland; Keski-Suomen metsaeenergia -projekti

Energy Technology Data Exchange (ETDEWEB)

Ahokas, M. [Association of Central Finland, Jyvaeskylae (Finland); Kuitto, P.J. [VTT Energy, Jyvaeskylae (Finland)

1996-12-31

The Forest Energy Project of Central Finland is one of the topleading regional demonstration project in Finland for testing and studying of the complete energy wood delivery chains and energy wood utilization. It is a large development and technology transfer venture concentrated primarily on practical needs. Total delivery chains are formed of the best machine and method alternatives, and they are also demonstrated. The project offers hence a wide test field for regional and national techno/economical wood fuel development. The target of this provincial project is to collect and demonstrate the most promising energy wood procurement technologies and methods for utilization of energy producers, forest industry and small and medium sized industries co-operating with forest owners, contractors and forest organizations. An essential target of the project is to direct the know-how, concentrated in the project, to development of the energy field. The project is directed to international information delivery, to concrete widening of cooperation, on transfer of testing and training activities and utilization experiences in the field of wood energy. The Forest Energy Project of Central Finland is a demonstration project supervised by the Regional Council of Central Finland. The project is a part of the national Bioenergy Research Programme. A large number of provincial partners interested in wood fuels, e.g. energy wood suppliers, energy producers, communes, forest industry, forestry boards, forestry associations, wood delivery contractors, and equipment producers, take part in the project

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

Science.gov (United States)

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

2007-01-01

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

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.

77 FR 18997 - Rim Lakes Forest Restoration Project; Apache-Sitgreavese National Forest, Black Mesa Ranger...

Science.gov (United States)

2012-03-29

... DEPARTMENT OF AGRICULTURE Forest Service Rim Lakes Forest Restoration Project; Apache-Sitgreavese National Forest, Black Mesa Ranger District, Coconino County, AZ AGENCY: Forest Service, USDA. ACTION: Notice of intent to prepare an environmental impact statement. SUMMARY: The U.S. Forest Service (FS) will...

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

Science.gov (United States)

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

2014-01-01

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

Economics of forests and REDD+ projects

DEFF Research Database (Denmark)

Zaballa Romero, Mauricio Ernesto; Trærup, Sara Lærke Meltofte; Wieben, Emilie

The financial implications of implementing a new forest management paradigm have not been well understood and have often been underestimated. Resource needs for e.g., stakeholder consultation, capacity building and addressing the political economy are seldom fully accounted for in the resource...... needs estimates put forward in connection to REDD+. This report investigates the economics of implementing forest and REDD+ projects through eight case studies from Africa, Latin America and Asia, analyzing real forest and REDD+ investments....

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.

Economics of forest and forest carbon projects. Translating lessons learned into national REDD+ implementation

DEFF Research Database (Denmark)

Zaballa Romero, Mauricio Ernesto; Trærup, Sara Lærke Meltofte; Wieben, Emilie

The financial implications of implementing a new forest management paradigm have not been well understood and have often been underestimated. Resource needs for e.g., stakeholder consultation, capacity building and addressing the political economy are seldom fully accounted for in the resource...... but also the testing of advanced market commitments as a finance option for sustainable forest management. The findings in the report underline the fact that only through sound and transparent financial information will forest projects and national forest initiatives become interesting for private...... needs estimates put forward in connection to REDD+. This report investigates the economics of implementing forest and REDD+ projects through eight case studies from Africa, Latin America and Asia, analyzing real forest and REDD+ investments. The report is part of efforts to share financial experiences...

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

Brain-mapping projects using the common marmoset.

Science.gov (United States)

Okano, Hideyuki; Mitra, Partha

2015-04-01

Globally, there is an increasing interest in brain-mapping projects, including the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative project in the USA, the Human Brain Project (HBP) in Europe, and the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) project in Japan. These projects aim to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain. Brain/MINDS is focused on structural and functional mapping of the common marmoset (Callithrix jacchus) brain. This non-human primate has numerous advantages for brain mapping, including a well-developed frontal cortex and a compact brain size, as well as the availability of transgenic technologies. In the present review article, we discuss strategies for structural and functional mapping of the marmoset brain and the relation of the common marmoset to other animals models. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Forest Energy Project of Central Finland; Keski-Suomen metsaeenergiaprojekti

Energy Technology Data Exchange (ETDEWEB)

Ahokas, M [Regional Council of Central Finland, Jyvaeskylae (Finland); Kuitto, P J [VTT Energy, Jyvaeskylae (Finland). Fuel Production

1997-12-01

The Forest Energy Project of Central Finland (1994 - 1996) was one of the leading regional demonstration projects in Finland for testing and studying of the complete energy wood delivery chains and energy wood utilisation. The target of this provincial project was to collect and demonstrate the most promising energy wood procurement technologies and methods for utilisation of energy producers, forest industry and small and medium sized industries co- operating with forest owners, contractors and forest organisations. The project was a large development and technology transfer venture concentrated primarily on practical needs. Total delivery chains were formed of the best machine and method alternatives, and they were also demonstrated. The project offered hence a wide test field for regional and national techno / economical wood fuel development. The Forest Energy Project of Central Finland was a demonstration project supervised by the Regional Council of Central Finland. The project was a part of the national Bioenergy Research Programme. VTT Energy and the Forestry Board of Central Finland were responsible for the practical development work. A large number of provincial partners interested in wood fuels took part in the project. The project were carried out during the years 1994 - 1996. The total costs were 4.4 million FIM. The aim is to create a practical model for the entire system, by which enables the economically profitable increment of the utilisation of chip fuels in Central Finland by 100 GWh/1996 and 500 GWh/a (about 250 000 m{sup 3}) to the end of the decade. (orig.)

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...

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

CSIR Research Space (South Africa)

Cho, Moses A

2009-06-01

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

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

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.

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

Science.gov (United States)

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

2013-10-26

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

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

Science.gov (United States)

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

2016-02-11

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

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

Science.gov (United States)

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

2010-01-01

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

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

Estonian energy forest project

International Nuclear Information System (INIS)

Koppel, A.; Kirt, E.; Kull, K.; Lasn, R.; Noormets, A.; Roostalu, H.; Ross, J.; Ross, V.; Sulev, M.

1994-04-01

In February 1993 an agreement of Swedish-Estonian scientific co-operation on energy forest was signed. In may five energy forest plantations (altogether 2 ha) were established in Estonia with Swedish selected clones of Salix viminalis and Salix dasyclados. The research within this project is carried out within three main directions. The studies of basic ecophysiological processes and radiation regime of willow canopy will be carried out in Toravere. The production ecology studies, comparison of the productivity of multiple clones on different soil types is based on the plantations as vegetation filter for wastewater purification is studied on the basis of plantations in Vaeike-Maarja and Valga (author)

Projecting national forest inventories for the 2000 RPA timber assessment.

Science.gov (United States)

John R. Mills; Xiaoping. Zhou

2003-01-01

National forest inventories were projected in a study that was part of the 2000 USDA Forest Service Resource Planning Act (RPA) timber assessment. This paper includes an overview of the status and structure of timber inventory of the National Forest System and presents 50-year projections under several scenarios. To examine a range of possible outcomes, results are...

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

DEFF Research Database (Denmark)

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

2011-01-01

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

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

Directory of Open Access Journals (Sweden)

Xiliang Ni

2015-06-01

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

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.

77 FR 12002 - Mount Baker-Snoqualmie National Forest Site-Specific Invasive Plant Treatment Project and Forest...

Science.gov (United States)

2012-02-28

... Invasive Plant Treatment Project and Forest Plan Amendment Number 28 AGENCY: Forest Service, USDA. ACTION... Forest. The current Forest-wide treatment approach pre-dates the Pacific Northwest Region Invasive Plant... interdisciplinary analysis: (1) Whether or not to authorize site- specific invasive plant treatments using...

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.

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

OpenAIRE

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

2013-01-01

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

STEER Coastal Use Mapping Project

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Coastal Use Mapping Project is designed to collect critical information on human activities in and near the St. Thomas East End Reserves (STEER). The project...

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

Science.gov (United States)

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

2017-12-01

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

76 FR 69700 - Klamath National Forest; California; Pumice Vegetation Management Project

Science.gov (United States)

2011-11-09

... Management Project AGENCY: Forest Service, USDA. ACTION: Notice of intent to prepare an environmental impact.... Grantham, Forest Supervisor, Attn: Ben Haupt, Pumice Vegetation Management Project Team Leader, Goosenest... Management Project will recommend implementation of one of the following: (1) The proposed action; (2) an...

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

Science.gov (United States)

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

2017-12-01

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

Automatic crown cover mapping to improve forest inventory

Science.gov (United States)

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

2009-01-01

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

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.

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

Directory of Open Access Journals (Sweden)

Khamma Homsysavath

2011-08-01

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

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

Science.gov (United States)

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

2017-12-01

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

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

Directory of Open Access Journals (Sweden)

Chuang Qian

2016-12-01

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

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

NARCIS (Netherlands)

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

2004-01-01

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

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

Science.gov (United States)

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

2018-05-01

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

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.

Supplementing forest ecosystem health projects on the ground

Science.gov (United States)

Cathy Barbouletos; Lynette Z. Morelan

1995-01-01

Understanding the functions and processes of ecosystems is critical before implementing forest ecosystem health projects on the landscape. Silvicultural treatments such as thinning, prescribed fire, and reforestation can simulate disturbance regimes and landscape patterns that have regulated forest ecosystems for centuries. As land managers we need to understand these...

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

Science.gov (United States)

Saatchi, Sasan; Rignot, Eric; Vanzyl, Jakob

1995-01-01

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

EnviroAtlas - Ecosystem Service Market and Project Locations, U.S., 2015, Forest Trends' Ecosystem Marketplace

Science.gov (United States)

This EnviroAtlas dataset contains points depicting the location of market-based programs, referred to herein as markets, and projects addressing ecosystem services protection in the United States. The data were collected via surveys and desk research conducted by Forest Trends' Ecosystem Marketplace from 2008 to 2016 on biodiversity (i.e., imperiled species/habitats; wetlands and streams), carbon, and water markets. Additional biodiversity data were obtained from the Regulatory In-lieu Fee and Bank Information Tracking System (RIBITS) database in 2015. Points represent the centroids (i.e., center points) of market coverage areas, project footprints, or project primary impact areas in which ecosystem service markets or projects operate. National-level markets are an exception to this norm with points representing administrative headquarters locations. Attribute data include information regarding the methodology, design, and development of biodiversity, carbon, and water markets and projects. This dataset was produced by Forest Trends' Ecosystem Marketplace for EnviroAtlas in order to support public access to and use of information related to environmental markets. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) o

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

Science.gov (United States)

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

2015-01-01

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

76 FR 19313 - Chequamegon-Nicolet National Forest, Wisconsin, Lakewood Southeast Project

Science.gov (United States)

2011-04-07

... stream bank improvement, forest age, forest composition, and stocking. DATES: Comments concerning the... Southeast Project AGENCY: Forest Service, USDA. ACTION: Notice of intent to prepare an environmental impact statement. SUMMARY: The Forest Service will prepare an environmental impact statement (EIS) to document the...

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.

The use of process mapping in healthcare quality improvement projects.

Science.gov (United States)

Antonacci, Grazia; Reed, Julie E; Lennox, Laura; Barlow, James

2018-05-01

Introduction Process mapping provides insight into systems and processes in which improvement interventions are introduced and is seen as useful in healthcare quality improvement projects. There is little empirical evidence on the use of process mapping in healthcare practice. This study advances understanding of the benefits and success factors of process mapping within quality improvement projects. Methods Eight quality improvement projects were purposively selected from different healthcare settings within the UK's National Health Service. Data were gathered from multiple data-sources, including interviews exploring participants' experience of using process mapping in their projects and perceptions of benefits and challenges related to its use. These were analysed using inductive analysis. Results Eight key benefits related to process mapping use were reported by participants (gathering a shared understanding of the reality; identifying improvement opportunities; engaging stakeholders in the project; defining project's objectives; monitoring project progress; learning; increased empathy; simplicity of the method) and five factors related to successful process mapping exercises (simple and appropriate visual representation, information gathered from multiple stakeholders, facilitator's experience and soft skills, basic training, iterative use of process mapping throughout the project). Conclusions Findings highlight benefits and versatility of process mapping and provide practical suggestions to improve its use in practice.

Modeling Research Project Risks with Fuzzy Maps

Science.gov (United States)

Bodea, Constanta Nicoleta; Dascalu, Mariana Iuliana

2009-01-01

The authors propose a risks evaluation model for research projects. The model is based on fuzzy inference. The knowledge base for fuzzy process is built with a causal and cognitive map of risks. The map was especially developed for research projects, taken into account their typical lifecycle. The model was applied to an e-testing research…

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

Science.gov (United States)

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

2009-01-01

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

NASA LCLUC Program: An Integrated Forest Monitoring System for Central Africa

Science.gov (United States)

Laporte, Nadine; LeMoigne, Jacqueline; Elkan, Paul; Desmet, Olivier; Paget, Dominique; Pumptre, Andrew; Gouala, Patrice; Honzack, Miro; Maisels, Fiona

2004-01-01

Central Africa has the second largest unfragmented block of tropical rain forest in the world; it is also one of the largest carbon and biodiversity reservoirs. With nearly one-third of the forest currently allocated for logging, the region is poised to undergo extensive land-use change. Through the mapping of the forests, our Integrated Forest Monitoring System for Central Africa (INFORMS) project aims to monitor habitat alteration, support biodiversity conservation, and promote better land-use planning and forest management. Designed as an interdisciplinary project, its goal is to integrate data acquired from satellites with field observations from forest inventories, wildlife surveys, and socio-economic studies to map and monitor forest resources. This project also emphasizes on collaboration and coordination with international, regional, national, and local partners-including non-profit, governmental, and commercial sectors. This project has been focused on developing remote sensing products for the needs of forest conservation and management, insuring that research findings are incorporated in forest management plans at the national level. The societal impact of INFORMS can be also appreciated through the development of a regional remote sensing network in central Africa. With a regional office in Kinshasa, (www.OSFAC.org), the contribution to the development of forest management plans for 1.5 million hectares of forests in northern Republic of Congo (www.tt-timber.com), and the monitoring of park encroachments in the Albertine region (Uganda and DRC) (www.albertinerift.org).

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

Science.gov (United States)

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

2009-01-01

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

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

Directory of Open Access Journals (Sweden)

Tomislav Hengl

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

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

OpenAIRE

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

2016-01-01

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

Site productivity and forest carbon stocks in the United States: Analysis and implications for forest offset project planning

Science.gov (United States)

Coeli M. Hoover; James E. Smith

2012-01-01

The documented role of United States forests in sequestering carbon, the relatively low cost of forest-based mitigation, and the many co-benefits of increasing forest carbon stocks all contribute to the ongoing trend in the establishment of forest-based carbon offset projects. We present a broad analysis of forest inventory data using site quality indicators to provide...

Assessing IT Projects Success with Extended Fuzzy Cognitive Maps & Neutrosophic Cognitive Maps in comparison to Fuzzy Cognitive Maps

Directory of Open Access Journals (Sweden)

Kanika Bhutani

2016-08-01

Full Text Available IT projects hold a huge importance to economic growth. Today, half of the capital investments are in IT technology. IT systems and projects are extensive and time consuming; thus implying that its failure is not affordable, so proper feasibility study of assessing project success factors is required. A current methodology like Fuzzy Cognitive Maps has been experimented for identifying and evaluating the success factors in IT projects, but this technique has certain limitations. This paper discusses two new approaches to evaluate IT project success: Extended Fuzzy Cognitive Maps (E-FCM & Neutrosophic Cognitive Maps (NCM.The limitations of FCM like non consideration for non-linear, conditional, time delay weights and indeterminate relations are targeted using E-FCM and NCM in this paper.

Mapping Fuels on the Okanogan and Wenatchee National Forests

Science.gov (United States)

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

2006-01-01

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

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

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Grant Connette

2016-10-01

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

Livelihood impacts of forest carbon project and its implications for ...

African Journals Online (AJOL)

This study examines the impacts of forest carbon project on the livelihoods of rural households and its implications for the sustainability of forest by focusing on a regenerated forest in Humbo district of Southwestern Ethiopia. The methods through which primary data were gathered are a triangulation of household survey, ...

Quantifying and mapping spatial variability in simulated forest plots

Science.gov (United States)

Gavin R. Corral; Harold E. Burkhart

2016-01-01

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

Mapping project on land use changes in the carboniferous region of Santa Catarina

Science.gov (United States)

Valeriano, D. D.; Pereira, M. D. B.

1983-01-01

The utilization of remote sensing data for monitoring land use changes by means of digital image analysis is described. The following data were utilized: LANDSAT data from September 4, 1975, April 24, 1978, and September 8, 1981; LANDSAT paper photography data; area IV color photographs; IBGE topography maps, and auxiliary data about the Brazilian state of Santa Catarina. Three kinds of analyses of digital images were carried out. The project identified and mapped major classes of land use areas including urban areas, coal deposits, agricultural areas, forests, lakes, and flood plains. Five areas directly affected by coal exploration southeast of Santa Catarina are identified and described. In addition, the classification system used for organizing data about land cover in a hierarchical arrangement is presented. The project made use of two remote sensing data sources: data of MSS spectral (Mulitspectral Scanner System)/LANDSAT on a scale of 1:100,000 with approximately 80 m resolution, and infrared color aerial photographs on a scale of 1:45,000 with approximately 5 m resolution. Therefore, the classification system included three levels, two selected to be compatible with aerial photography data and the third to conform to the resolution of MSS/LANDSAT.

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

Mapping tropical forest trees using high-resolution aerial digital photographs

NARCIS (Netherlands)

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

2013-01-01

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

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

African Journals Online (AJOL)

EJIRO

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

Brain/MINDS: brain-mapping project in Japan

Science.gov (United States)

Okano, Hideyuki; Miyawaki, Atsushi; Kasai, Kiyoto

2015-01-01

There is an emerging interest in brain-mapping projects in countries across the world, including the USA, Europe, Australia and China. In 2014, Japan started a brain-mapping project called Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS). Brain/MINDS aims to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain, and takes advantage of a unique non-human primate animal model, the common marmoset (Callithrix jacchus). In Brain/MINDS, the RIKEN Brain Science Institute acts as a central institute. The objectives of Brain/MINDS can be categorized into the following three major subject areas: (i) structure and functional mapping of a non-human primate brain (the marmoset brain); (ii) development of innovative neurotechnologies for brain mapping; and (iii) human brain mapping; and clinical research. Brain/MINDS researchers are highly motivated to identify the neuronal circuits responsible for the phenotype of neurological and psychiatric disorders, and to understand the development of these devastating disorders through the integration of these three subject areas. PMID:25823872

Brain/MINDS: brain-mapping project in Japan.

Science.gov (United States)

Okano, Hideyuki; Miyawaki, Atsushi; Kasai, Kiyoto

2015-05-19

There is an emerging interest in brain-mapping projects in countries across the world, including the USA, Europe, Australia and China. In 2014, Japan started a brain-mapping project called Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS). Brain/MINDS aims to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain, and takes advantage of a unique non-human primate animal model, the common marmoset (Callithrix jacchus). In Brain/MINDS, the RIKEN Brain Science Institute acts as a central institute. The objectives of Brain/MINDS can be categorized into the following three major subject areas: (i) structure and functional mapping of a non-human primate brain (the marmoset brain); (ii) development of innovative neurotechnologies for brain mapping; and (iii) human brain mapping; and clinical research. Brain/MINDS researchers are highly motivated to identify the neuronal circuits responsible for the phenotype of neurological and psychiatric disorders, and to understand the development of these devastating disorders through the integration of these three subject areas.

Climate Ready Estuaries Partner Projects Map

Science.gov (United States)

CRE partners with the National Estuary Program to develop climate change projects in coastal U.S. areas, such as bays and harbors; to develop adaptation action plans, identify climate impacts and indicators, and more. This map shows project locations.

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

Science.gov (United States)

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

2016-08-01

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

Projected wood energy impact on US forest wood resources

Energy Technology Data Exchange (ETDEWEB)

Skog, K.E. [USDA Forest Service, Madison, WI (United States)

1993-12-31

The USDA Forest Service has developed long-term projections of wood energy use as part of a 1993 assessment of demand for and supply of resources from forest and range lands in the United States. To assess the impact of wood energy demand on timber resources, a market equilibrium model based on linear programming was developed to project residential, industrial, commercial, and utility wood energy use from various wood energy sources: roundwood from various land sources, primary wood products mill residue, other wood residue, and black liquor. Baseline projections are driven by projected price of fossil fuels compared to price of wood fuels and the projected increase in total energy use in various end uses. Wood energy use is projected to increase from 2.67 quad in 1986 to 3.5 quad in 2030 and 3.7 quad in 2040. This is less than the DOE National Energy Strategy projection of 5.5 quad in 2030. Wood energy from forest sources (roundwood) is projected to increase from 3.1 billion (10{sup 9}) ft{sup 3} in 1986 to 4.4. billion ft{sup 3} in 2030 and 4.8 billion ft{sup 3} in 2040 (88, 124 and 136 million m{sup 3}, respectively). This rate of increase of roundwood use for fuel -- 0.8 percent per year -- is virtually the same as the projected increase rate for roundwood for pulpwood. Pulpwood roundwood is projected to increase from 4.2 billion ft{sup 3} in 1986 to 6.0 billion ft{sup 3} in 2030 and 6.4 billion ft{sup 3} in 2040 (119, 170 and 183 million m{sup 3}, respectively).

The experimental design of the Missouri Ozark Forest Ecosystem Project

Science.gov (United States)

Steven L. Sheriff; Shuoqiong. He

1997-01-01

The Missouri Ozark Forest Ecosystem Project (MOFEP) is an experiment that examines the effects of three forest management practices on the forest community. MOFEP is designed as a randomized complete block design using nine sites divided into three blocks. Treatments of uneven-aged, even-aged, and no-harvest management were randomly assigned to sites within each block...

Global Land Survey Impervious Mapping Project Web Site

Science.gov (United States)

DeColstoun, Eric Brown; Phillips, Jacqueline

2014-01-01

The Global Land Survey Impervious Mapping Project (GLS-IMP) aims to produce the first global maps of impervious cover at the 30m spatial resolution of Landsat. The project uses Global Land Survey (GLS) Landsat data as its base but incorporates training data generated from very high resolution commercial satellite data and using a Hierarchical segmentation program called Hseg. The web site contains general project information, a high level description of the science, examples of input and output data, as well as links to other relevant projects.

The Effect of China’s New Circular Collective Forest Tenure Reform on Household Non-Timber Forest Product Production in Natural Forest Protection Project Regions

Directory of Open Access Journals (Sweden)

Yang Ren

2018-04-01

Full Text Available The implementation of China’s natural forest protection project (Protection Project in 1998 changed households’ forestry production modes in project regions, and China’s new circular collective forest tenure reform (Tenure Reform has been implemented since 2003 with the goal of motivating household forestry production and increasing household income from forests. Policymakers expect that Tenure Reform could also stimulate households to engage in non-timber forest products (NTFPs production in Protection Project regions. However, only a few studies have investigated the effect of Tenure Reform on household NTFP production in Protection Project regions. To fill this gap, we built an integrative conceptual framework and estimated a corresponding structural equation model (SEM using survey data from 932 households in Protection Project regions in southwestern China. In our research framework, there are four factors, including household characteristics, labour and social capital, forestland characteristics, and the Tenure Reform, affecting household NTFP production. The results substantiate that Tenure Reform has had a significant positive effect on household NTFP production. Additionally, household and forestland characteristics have promoted household NTFP production, but quantitatively less than Tenure Reform. This report can be used to inform the government that future investment in Tenure Reform still needs to be enhanced, and policy enforcement still needs to be strengthened.

Projection Mapping User Interface for Disabled People.

Science.gov (United States)

Gelšvartas, Julius; Simutis, Rimvydas; Maskeliūnas, Rytis

2018-01-01

Difficulty in communicating is one of the key challenges for people suffering from severe motor and speech disabilities. Often such person can communicate and interact with the environment only using assistive technologies. This paper presents a multifunctional user interface designed to improve communication efficiency and person independence. The main component of this interface is a projection mapping technique used to highlight objects in the environment. Projection mapping makes it possible to create a natural augmented reality information presentation method. The user interface combines a depth sensor and a projector to create camera-projector system. We provide a detailed description of camera-projector system calibration procedure. The described system performs tabletop object detection and automatic projection mapping. Multiple user input modalities have been integrated into the multifunctional user interface. Such system can be adapted to the needs of people with various disabilities.

Projection Mapping User Interface for Disabled People

Science.gov (United States)

Simutis, Rimvydas; Maskeliūnas, Rytis

2018-01-01

Difficulty in communicating is one of the key challenges for people suffering from severe motor and speech disabilities. Often such person can communicate and interact with the environment only using assistive technologies. This paper presents a multifunctional user interface designed to improve communication efficiency and person independence. The main component of this interface is a projection mapping technique used to highlight objects in the environment. Projection mapping makes it possible to create a natural augmented reality information presentation method. The user interface combines a depth sensor and a projector to create camera-projector system. We provide a detailed description of camera-projector system calibration procedure. The described system performs tabletop object detection and automatic projection mapping. Multiple user input modalities have been integrated into the multifunctional user interface. Such system can be adapted to the needs of people with various disabilities. PMID:29686827

The European radon mapping project

International Nuclear Information System (INIS)

Bossew, P.; Tollefsen, T.; Gruber, V.; De Cort, M.

2013-01-01

There is almost unanimous agreement that indoor radon (Rn) represents a hazard to human health. Large-scale epidemiological studies gave evidence that Rn is the second-most important cause o flung cancer after smoking and that also relatively low Rn concentrations can be detrimental. This has increasingly led to attempts to limit Rn exposure through regulation, mainly building codes. The proposed Euratom Basic Safety Standards (BSS) require Member States to establish Rn action plans aimed at reducing Rn risk, and to set reference values for Imitating indoor Rn concentration. In 2006 the JRC started a project on mapping Rn at the European level, in addition and complementary lo (but not as a substitute for) national efforts. These maps are part of the European Atlas of Natural Radiation project. which is planned eventually 10 comprise geographical assessments of ali sources of exposure to natural radiation. Started first, a map of indoor Rn is now in an advanced phase, but still incomplete as national Rn surveys are ongoing in a number of European countries. A European map of geogenic Rn, conceptually and technically more complicated, was started in 2008. The main difficulty encountered is heterogeneity of survey designs, measurement and evaluation methods and database semantics and structures. An important part or the work on the Atlas is therefore to harmonize data and methods. We present the current state of the Rn maps and discuss some of the methodological challenges. (author)

The European radon mapping project

Energy Technology Data Exchange (ETDEWEB)

Bossew, P., E-mail: pbossew@bfs.de [German Federal Office for Radiation Protection, Berlin (Germany); Tollefsen, T.; Gruber, V.; De Cort, M., E-mail: tore.tollefsen@jrc.ec.europa.eu, E-mail: valeria.gruber@gmail.com, E-mail: marc.de-cort@jrc.ec.europa.eu [Institute for Transuranium Elements, Ispra, VA (Italy). DG Joint Research Centre. European Commission

2013-07-01

There is almost unanimous agreement that indoor radon (Rn) represents a hazard to human health. Large-scale epidemiological studies gave evidence that Rn is the second-most important cause o flung cancer after smoking and that also relatively low Rn concentrations can be detrimental. This has increasingly led to attempts to limit Rn exposure through regulation, mainly building codes. The proposed Euratom Basic Safety Standards (BSS) require Member States to establish Rn action plans aimed at reducing Rn risk, and to set reference values for Imitating indoor Rn concentration. In 2006 the JRC started a project on mapping Rn at the European level, in addition and complementary lo (but not as a substitute for) national efforts. These maps are part of the European Atlas of Natural Radiation project. which is planned eventually 10 comprise geographical assessments of ali sources of exposure to natural radiation. Started first, a map of indoor Rn is now in an advanced phase, but still incomplete as national Rn surveys are ongoing in a number of European countries. A European map of geogenic Rn, conceptually and technically more complicated, was started in 2008. The main difficulty encountered is heterogeneity of survey designs, measurement and evaluation methods and database semantics and structures. An important part or the work on the Atlas is therefore to harmonize data and methods. We present the current state of the Rn maps and discuss some of the methodological challenges. (author)

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

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

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

Science.gov (United States)

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

2013-09-01

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

Prioritization of Forest Restoration Projects: Tradeoffs between Wildfire Protection, Ecological Restoration and Economic Objectives

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Kevin C. Vogler

2015-12-01

Full Text Available The implementation of US federal forest restoration programs on national forests is a complex process that requires balancing diverse socioecological goals with project economics. Despite both the large geographic scope and substantial investments in restoration projects, a quantitative decision support framework to locate optimal project areas and examine tradeoffs among alternative restoration strategies is lacking. We developed and demonstrated a new prioritization approach for restoration projects using optimization and the framework of production possibility frontiers. The study area was a 914,657 ha national forest in eastern Oregon, US that was identified as a national priority for restoration with the goal of increasing fire resiliency and sustaining ecosystem services. The results illustrated sharp tradeoffs among the various restoration goals due to weak spatial correlation of forest stressors and provisional ecosystem services. The sharpest tradeoffs were found in simulated projects that addressed either wildfire risk to the urban interface or wildfire hazard, highlighting the challenges associated with meeting both economic and fire protection goals. Understanding the nature of tradeoffs between restoration objectives and communicating them to forest stakeholders will allow forest managers to more effectively design and implement economically feasible restoration projects.

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

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S. K. Farber

2017-12-01

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

RegionsТ Competition for Investment Projects in Forest Development

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Valentina Fedorovna Lapo

2014-06-01

Full Text Available The author considers the problem of competition between regions for investments. It is hypothesized that the presence of legislative stimulating benefits in a particular region, ceteris paribus, promotes investment flows in forest projects from other regions and is an instrumentl of inter-regional competition. To test the hypotheses the researcher uses a modified model with spatial weighted exogenous variables in order to assess the spatial effects. The obtained estimates indicate the presence of spatial effects, both negative (an inter-regional competition for investment and positive (agglomeration effects. The author argues that the process of inter-regional competition for investment in projects on forest development is caused by benefits under taxes and payments into the regional budget, regulation of pricing (including actions by natural and local monopolies and depreciation policy and solutions to put some forest projects in the list of priority ones. Along with this, the paper identifies agglomeration effects induced by a number of benefits: direct dealings in investment by financing or property contribution, subsidies, state guarantees, credit security and partial payment of interest

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...

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

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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.

Projection Mapping User Interface for Disabled People

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Julius Gelšvartas

2018-01-01

Full Text Available Difficulty in communicating is one of the key challenges for people suffering from severe motor and speech disabilities. Often such person can communicate and interact with the environment only using assistive technologies. This paper presents a multifunctional user interface designed to improve communication efficiency and person independence. The main component of this interface is a projection mapping technique used to highlight objects in the environment. Projection mapping makes it possible to create a natural augmented reality information presentation method. The user interface combines a depth sensor and a projector to create camera-projector system. We provide a detailed description of camera-projector system calibration procedure. The described system performs tabletop object detection and automatic projection mapping. Multiple user input modalities have been integrated into the multifunctional user interface. Such system can be adapted to the needs of people with various disabilities.

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

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Susana Mestre

2018-02-01

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

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

International Nuclear Information System (INIS)

Torahi, A.A.

2013-01-01

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

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

Science.gov (United States)

Hakkenberg, Christopher R.

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

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

Science.gov (United States)

Akay, A. E.; Erdoğan, A.

2017-11-01

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

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

Science.gov (United States)

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

2009-01-01

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

Adapting the Water Erosion Prediction Project (WEPP) model for forest applications

Science.gov (United States)

Shuhui Dun; Joan Q. Wu; William J. Elliot; Peter R. Robichaud; Dennis C. Flanagan; James R. Frankenberger; Robert E. Brown; Arthur C. Xu

2009-01-01

There has been an increasing public concern over forest stream pollution by excessive sedimentation due to natural or human disturbances. Adequate erosion simulation tools are needed for sound management of forest resources. The Water Erosion Prediction Project (WEPP) watershed model has proved useful in forest applications where Hortonian flow is the major form of...

The Kings River Sustainable Forest Ecosystems Project: inception, objectives, and progress

Science.gov (United States)

Jared Verner; Mark T. Smith

2002-01-01

The Kings River Sustainable Forest Ecosystems Project, a formal administrative study involving extensive and intensive collaboration between Forest Service managers and researchers, is a response to changes in the agency’s orientation in favor of ecosystem approaches and to recent concern over issues associated with maintenance of late successional forest attributes...

Current Resource Imagery Projects

Data.gov (United States)

Farm Service Agency, Department of Agriculture — Map showing coverage of current Resource imagery projects. High resolution/large scale Resource imagery is typically acquired for the U.S. Forest Service and other...

78 FR 13315 - Bridger-Teton National Forest; Wyoming; Teton to Snake Fuels Management Project

Science.gov (United States)

2013-02-27

... Fuels Management Project AGENCY: Forest Service, USDA. ACTION: Notice of intent to prepare an...) to document the potential effects of the Teton to Snake Fuels Management Project. The analysis will... Caribou-Targhee National Forest. The Teton to Snake Fuels Management Project was previously scoped and...

The “Forest Fire Project”, National cartographic portal of the Italian Environmental Department: an example of management of cartographic data to support forest fires fighting plans in national parks

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Petrucci B

2010-02-01

Full Text Available The “Forest Fire Project” on the National cartographic portal (http://www.pcn.minambiente.it has been created by the Italian Ministry of Environment Territory and Sea (METS. The project is intended to support forest fire fighting plans in national protected areas as provided for by article 8 of the law November 21th 2000, no. 353 “Framework law on forest fires”. The project brings out the results of previous projects carried out in collaboration with several research institutes. Cartographic information is made available as free and reliable knowledge base in order to facilitate the draw up and implementation of the “Forest Fire Plans”, including the actual activity of forest fire extinction. Map information can be further implemented by various subjects such as researchers, land planning programmers or managers. The National cartographic portal gives the opportunity of overlaying various cartographic information and base maps supporting the “Forest Fire Project”; moreover it is possible to add other layers from other sources, through URL. Adequate “personalised” overlaps - which can be saved on one’s own GIS - allow in depth analysis and deductions aimed at specific objectives of territorial planning and management and in particular of Forest Fire Fighting Plans.

Land cover change map comparisons using open source web mapping technologies

Science.gov (United States)

Erik Lindblom; Ian Housman; Tony Guay; Mark Finco; Kevin. Megown

2015-01-01

The USDA Forest Service is evaluating the status of current landscape change maps and assessing gaps in their information content. These activities have been occurring under the auspices of the Landscape Change Monitoring System (LCMS) project, which is a joint effort between USFS Research, USFS Remote Sensing Applications Center (RSAC), USGS Earth Resources...

Stakeholders of Voluntary Forest Carbon Offset Projects in China: An Empirical Analysis

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Derong Lin

2015-01-01

Full Text Available Climate change is one of the defining challenges facing the planet. Voluntary forest carbon offset project which has the potential to boost forest carbon storage and mitigate global warming has aroused the global concern. The objective of this paper is to model the game situation and analyze the game behaviors of stakeholders of voluntary forest carbon offset projects in China. A stakeholder model and a Power-Benefit Matrix are constructed to analyze the roles, behaviors, and conflicts of stakeholders including farmers, planting entities, communities, government, and China Green Carbon Foundation. The empirical analysis results show that although the stakeholders have diverse interests and different goals, a win-win solution is still possible through their joint participation and compromise in the voluntary forest carbon offset project. A wide governance structure laying emphasis on benefit balance, equality, and information exchanges and being regulated by all stakeholders has been constructed. It facilitates the agreement among the stakeholders with conflicting or different interests. The joint participation of stakeholders in voluntary forest carbon offset projects might change the government-dominated afforestation/reforestation into a market, where all participators including government are encouraged to cooperate with each other to improve the condition of fund shortage and low efficiency.

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

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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.

Landowner and visitor response to forest landscape restoration: the Chequamegon-Nicolet National Forest Northeast Sands Project

Science.gov (United States)

Kristin Floress; Anna Haines; Emily Usher; Paul Gobster; Mike. Dockry

2018-01-01

This report is intended to support the ongoing pine barrens restoration on work in the Lakewood-Laona Ranger District on the Chequamegon-Nicolet National Forest (CNNF). The report provides the results from 2016 surveys and focus groups examining landowner and visitor attitudes toward forest management treatments, communication, and restoration project outcomes; their...

Prioritization of forest restoration projects: Tradeoffs between wildfire protection, ecological restoration and economic objectives

Science.gov (United States)

Kevin C. Vogler; Alan A. Ager; Michelle A. Day; Michael Jennings; John D. Bailey

2015-01-01

The implementation of US federal forest restoration programs on national forests is a complex process that requires balancing diverse socioecological goals with project economics. Despite both the large geographic scope and substantial investments in restoration projects, a quantitative decision support framework to locate optimal project areas and examine...

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

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Yihua Jin

2016-12-01

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

Mapping host-species abundance of three major exotic forest pests

Science.gov (United States)

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

2005-01-01

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

Analysis of the production and transaction costs of forest carbon offset projects in the USA.

Science.gov (United States)

Galik, Christopher S; Cooley, David M; Baker, Justin S

2012-12-15

Forest carbon offset project implementation costs, comprised of both production and transaction costs, could present an important barrier to private landowner participation in carbon offset markets. These costs likewise represent a largely undocumented component of forest carbon offset potential. Using a custom spreadsheet model and accounting tool, this study examines the implementation costs of different forest offset project types operating in different forest types under different accounting and sampling methodologies. Sensitivity results are summarized concisely through response surface regression analysis to illustrate the relative effect of project-specific variables on total implementation costs. Results suggest that transaction costs may represent a relatively small percentage of total project implementation costs - generally less than 25% of the total. Results also show that carbon accounting methods, specifically the method used to establish project baseline, may be among the most important factors in driving implementation costs on a per-ton-of-carbon-sequestered basis, dramatically increasing variability in both transaction and production costs. This suggests that accounting could be a large driver in the financial viability of forest offset projects, with transaction costs likely being of largest concern to those projects at the margin. Copyright © 2012 Elsevier Ltd. All rights reserved.

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...

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

STRATEGIC MAPS AND CRITICAL FACTORS FOR PROJECT MANAGEMENT MATURITY: A PROPOSAL

Directory of Open Access Journals (Sweden)

Sady Darcy Silva Junior

2010-06-01

Full Text Available Project Management (PM and Strategic Management (SM are two subjects of growing importance in the corporate environment which are normally considered in isolation. One way of integrating these two concepts might be via the concept of project management maturity (Westphal et al., 2008. Rabechini and Pessoa (2005 state that to obtain project management maturity, it is necessary to achieve success in a number of critical factors which include organizational culture and structure, as well as sponsorship at both tactical and strategic levels (Silva et al., 2008. Another way of achieving this connection is by using Balanced Scorecard (BSC as an auxiliary tool to integrate between projects and organizational strategy (Brock et al., 2003. The original developers of the BSC, Kaplan e Norton, subsequently developed the concept of strategy mapping, which they affirm "represents the missing link between the formulation and the execution of the strategy" (Kaplan e Norton, 2004. This paper proposes a strategy map identifying critical factors for attaining project management maturity. To formulate the map, we used a qualitative, exploratory approach oriented by Project Management theory and strategy mapping. We first identified 13 critical factors, then developed a strategy map, which was evaluated by six specialists (three in SM area and three in PM area.The results suggest links between strategic mapping nad critical factors in project management. It also contributes to both areas independently. Specifically, the study identifies critical factors for project management maturity while demonstrating the applicability of strategic mapping techniques to Balanced Scorecard concepts.

Selecting Map Projections in Minimizing Area Distortions in GIS Applications

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Ahmet Kaya

2008-12-01

Full Text Available Varioussoftware for Geographical Information Systems (GISs have been developed and used in many different engineering projects. In GIS applications, map coverage is important in terms of performing reliable and meaningful queries. Map projections can be conformal, equal-area and equidistant. The goal of an application plays an important role in choosing one of those projections. Choosing the equal-area projection for an application in which area information is used (forestry, agriculture, ecosystem etc reduces the amount of distortion on the area, but many users using GIS ignore this fact and continue to use applications with present map sheets no matter in what map projection it is. For example, extracting area information from data whose country system’s map sheet is in conformal projection is relatively more distorted, compared to an equal-area projection one. The goal of this study is to make the best decision in choosing the most proper equal-area projection among the choices provided by ArcGIS 9.0, which is a popular GIS software package, and making a comparison on area errors when conformal projection is used. In this study, the area of parcels chosen in three different regions and geographic coordinates and whose sizes vary between 0.01 to 1,000,000 ha are calculated according to Transversal Mercator (TM, 3°, Universal Transversal Mercator (UTM, 6° and 14 different equal-area projections existing in the ArcGIS 9.0 GIS software package. The parcel areas calculated with geographical coordinates are accepted as definite. The difference between the sizes calculated according to projection coordinates and real sizes of the parcels are determined. Consequently, the appropriate projections are decided for the areas smaller and equal than 1,000 ha and greater than 1,000 ha in the GIS software package.

Project of Near-Real-Time Generation of ShakeMaps and a New Hazard Map in Austria

Science.gov (United States)

Jia, Yan; Weginger, Stefan; Horn, Nikolaus; Hausmann, Helmut; Lenhardt, Wolfgang

2016-04-01

Target-orientated prevention and effective crisis management can reduce or avoid damage and save lives in case of a strong earthquake. To achieve this goal, a project for automatic generated ShakeMaps (maps of ground motion and shaking intensity) and updating the Austrian hazard map was started at ZAMG (Zentralanstalt für Meteorologie und Geodynamik) in 2015. The first goal of the project is set for a near-real-time generation of ShakeMaps following strong earthquakes in Austria to provide rapid, accurate and official information to support the governmental crisis management. Using newly developed methods and software by SHARE (Seismic Hazard Harmonization in Europe) and GEM (Global Earthquake Model), which allows a transnational analysis at European level, a new generation of Austrian hazard maps will be ultimately calculated. More information and a status of our project will be given by this presentation.

Research Progress in Mathematical Analysis of Map Projection by Computer Algebra

Directory of Open Access Journals (Sweden)

BIAN Shaofeng

2017-10-01

Full Text Available Map projection is an important component of modern cartography, and involves many fussy mathematical analysis processes, such as the power series expansions of elliptical functions, differential of complex and implicit functions, elliptical integral and the operation of complex numbers. The derivation of these problems by hand not only consumes much time and energy but also makes mistake easily, and sometimes can not be realized at all because of the impossible complexity. The research achievements in mathematical analysis of map projection by computer algebra are systematically reviewed in five aspects, i.e., the symbolic expressions of forward and inverse solution of ellipsoidal latitudes, the direct transformations between map projections with different distortion properties, expressions of Gauss projection by complex function, mathematical analysis of oblique Mercator projection, polar chart projection with its transformation. Main problems that need to be further solved in this research field are analyzed. It will be helpful to promote the development of map projection.

An assessment of uncertainty in forest carbon budget projections

Science.gov (United States)

Linda S. Heath; James E. Smith

2000-01-01

Estimates of uncertainty are presented for projections of forest carbon inventory and average annual net carbon flux on private timberland in the US using the model FORCARB. Uncertainty in carbon inventory was approximately ±9% (2000 million metric tons) of the estimated median in the year 2000, rising to 11% (2800 million metric tons) in projection year 2040...

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

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

Science.gov (United States)

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

2013-05-01

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

Projection matrices as a forest management tool: an invasive tree case study

Science.gov (United States)

Ian J. Renne; Benjamin F. Tracy; Timothy P. Spira

2003-01-01

Life history parameters of many forest-dwelling species are affected by native and non-native pests. In turn, these pests alter forest processes and cost the United States billions of dollars annually. Population projection matrices can aid ecologists and managers in evaluating the impact of pests on forest species as well as devising effective strategies for pest...

Projection Mapping amb Shadertoy i openFrameworks

OpenAIRE

Borràs Massaguer, Lluís

2015-01-01

El projection mapping és un món molt complex, cada projecció explica una història diferent i hi ha molts perfils de persona treballant-hi al darrera, des del dissenyador gràfic, passant pels tècnics de vídeo i so fins a l’autor de la història. Les aplicacions que s’utilitzen per fer projection mapping, de les quals les més conegudes: ’Resolume Arena’, ’Mad Mapper’ i ’arkaos GrandVJ XT’ són aplicacions comercials a gran escala. És un tipus de software molt específic i, per tant, ...

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.

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.

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

Directory of Open Access Journals (Sweden)

Christopher S.R. Neigh

2014-03-01

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

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

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

Directory of Open Access Journals (Sweden)

G. Blöschl

2012-07-01

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

Forest resource projection tools at the European level

NARCIS (Netherlands)

Schelhaas, M.; Nabuurs, G.J.; Verkerk, P.J.; Hengeveld, G.M.; Packalen, Tuula; Sallnäs, O.; Pilli, Roberto; Grassi, J.; Forsell, Nicklas; Frank, S.; Gusti, Mykola; Havlik, Petr

2017-01-01

Many countries have developed their own systems for projecting forest resources and wood availability. Although studies using these tools are helpful for developing national policies, they do not provide a consistent assessment for larger regions such as the European Union or Europe as a whole.

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

Directory of Open Access Journals (Sweden)

Abdurrahim Aydın

2016-07-01

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

EUFODOS: European Forest Downstream Services – Improved Information on Forest Structure and Damage

Directory of Open Access Journals (Sweden)

M. Hirschmugl

2013-05-01

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

The Italian forest sites of FunDivEUROPE: a new FP7 project on the functional significance of forest biodiversity in Europe

Directory of Open Access Journals (Sweden)

Bussotti F

2012-12-01

Full Text Available The Italian forest sites of FunDivEUROPE: a new FP7 project on the functional significance of forest biodiversity in Europe. FunDivEUROPE is a new project aiming at a deeper understanding of the role of forest diversity on ecosystem functions and service provisioning for society. This project combines three scientific platforms: experimental, exploratory and inventory. The exploratory platform is based on the observation of a broad range of properties, traits and ecological processes on a network of ca. 240 natural forest sites representing a gradient of tree species diversity in six focal regions of Europe (Spain, Italy, Germany, Poland, Finland and Romania. The Italian sites are located on the hills of central and Southern Tuscany and represent the category “thermophilous deciduous forest”. Almost one year of fieldwork was needed to select and characterize 36 plots measuring 30 x 30 m. Selection was based on criteria concerning tree mixtures and richness, structural parameters and main environmental variables. The main features of these sites are synthetically presented in this paper together with a short description of the project structure and scope. The aim is also to enhance dissemination of the potential implications for a sustainable forest management in Italy.

76 FR 22075 - Divide Ranger District, Rio Grande National Forest; CO; Black Mesa Vegetation Management Project

Science.gov (United States)

2011-04-20

... Ranger District, Rio Grande National Forest; CO; Black Mesa Vegetation Management Project AGENCY: Forest... Web site http://www.fs.usda.gov/riogrande under ``Land & Resource Management'', then ``Projects'' on... need for the Black Mesa Vegetation Management Project is move toward achieving long-term desired...

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

Mapping the above and belowground biomass in three landscapes in Cameroon, Rwanda and DRC: pilot cases in REDD+ pilot project.

Science.gov (United States)

Sufo Kankeu, R.

2017-12-01

A number of biomass/carbon maps have been recently produced using different approaches and despite their comparison there is still a gap. To fill this gap there is a need to provide accurate maps based on the field data on all types of land use and land cover. Based on the field data from plots established in three pilot projects around Virunga National park in Rwanda, Tri-national Sangha landscape in Cameroon and lac Télé-Lac Tumba landscape in DRC, this paper intend to analyse the relationship between land use change and biomass and present the variability through biomass/carbon maps. The above and belowground biomass was calculated from 95 nested plots of 20 meters radius. The value of biomass/carbon per plot were thus used to elaborate carbon maps of each study site. In the same the way the correlation between the land use and underground and above ground carbon stock were analysed using geographically weighted regression. These data have been joint with classified Spot 5 image and aggregated to come out will acceptable result. Results show that there is a strong relationship between land use in various project sites and the carbon stock related, the change of a forest cover directly impact on carbon stock/biomass.in the same way carbon map realized base on field data and IDW, Kriging or spline module show an idea on the carbon distribution but the maps are not accurate giving the distance between plots,

Uav Photogrammetry: a Practical Solution for Challenging Mapping Projects

Science.gov (United States)

Saadatseresht, M.; Hashempour, A. H.; Hasanlou, M.

2015-12-01

We have observed huge attentions to application of unmanned aerial vehicle (UAV) in aerial mapping since a decade ago. Though, it has several advantages for handling time/cost/quality issues, there are a dozen of challenges in working with UAVs. In this paper, we; as the Robotic Photogrammetry Research Group (RPRG), will firstly review these challenges then show its advantages in three special practical projects. For each project, we will share our experiences through description of the UAV specifications, flight settings and processing steps. At the end, we will illustrate final result of each project and show how this technology could make unbelievable benefits to clients including 3D city realistic model in decimetre level, ultra high quality map production in several centimetre level, and accessing to a high risk and rough relief area for mapping aims.

77 FR 33158 - Plumas National Forest, California, Sugarloaf Hazardous Fuels Reduction Project

Science.gov (United States)

2012-06-05

... Fuels Reduction Project AGENCY: Forest Service, USDA. ACTION: Notice of intent to prepare an... National Forest (PNF) will prepare an environmental impact statement (EIS) on the Sugarloaf Hazardous Fuels... to the economic stability of rural communities through: fuels treatments; group selections (GS); area...

Cartographic science: a compendium of map projections, with derivations

National Research Council Canada - National Science Library

Fenna, Donald

2007-01-01

"From basic projecting to advanced transformations, Cartographic Science: A Compendium of Map Projections, with Derivations comprehensively explores the depiction of a curved world on a flat surface...

Mapping of information and identification of construction waste at project life cycle

Science.gov (United States)

Wibowo, Mochamad Agung; Handayani, Naniek Utami; Nurdiana, Asri; Sholeh, Moh Nur; Pamungkas, Gita Silvia

2018-03-01

The development of construction project towards green construction is needed in order to improve the efficiency of construction projects. One that needs to be minimized is construction waste. Construction waste is waste generated from construction project activities, both solid waste and non solid waste. More specifically, the waste happens at every phase of the project life cycle. Project life cycle are the stage of idea, design, construction, and operation/maintenance. Each phase is managed by different stakeholders. Therefore it requires special handling from the involved stakeholders. The objective of the study is to map the information and identify the waste at each phase of the project life cycle. The purpose of mapping is to figure out the process of information and product flow and with its timeline. This mapping used Value Stream Mapping (VSM). Identification of waste was done by distributing questionnaire to respondents to know the waste according to owner, consultant planner, contractor, and supervisory consultant. The result of the study is the mapping of information flow and product flow at the phases of idea, design, construction, and operation/ maintenance.

Single-edition quadrangle maps

Science.gov (United States)

,

1998-01-01

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

75 FR 23666 - Huron-Manistee National Forests, White Pines Wind Farm Project, Mason County, MI

Science.gov (United States)

2010-05-04

... DEPARTMENT OF AGRICULTURE Forest Service Huron-Manistee National Forests, White Pines Wind Farm Project, Mason County, MI AGENCY: Forest Service, USDA. ACTION: Cancellation Notice of notice of intent to prepare an environmental impact statement. SUMMARY: The Forest Service proposed to prepare an...

Understanding old-growth red and white pine dominated forests in Ontario. Forest fragmentation and biodiversity project technical report No. 2

Energy Technology Data Exchange (ETDEWEB)

Carleton, T.J.; Gordon, A.M.

1992-01-01

In summer 1991, a variety of forest stands dominated by old specimens of white pine and red pine were sampled across a representative portion of the species' range in northcentral Ontario. Plots were established in 40 stands of those surveyed to identify the salient structural components of old-growth, to survey the floristic composition (vascular plants and autotrophic non- vascular plants), to survey site characteristics, and to estimate the links in understorey alpha diversity with site conditions and stand structure. Long-term objectives include a definition of old- growth pine forest, recognition criteria, and prospective management options. Forest stand structure was enumerated through mapping, mensurational, and age estimation techniques. Forest vegetation, including over and understorey species, was non- destructively sampled and a range of data on stand and soil-site variables was also collected in conjunction with information on stand variables peculiar to old growth forests.

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

Chicago's urban forest ecosystem: results of the Chicago Urban Forest Climate Project

Science.gov (United States)

Gregory E. McPherson; David J. Nowak; Rowan A. Rowntree

1994-01-01

Results of the 3-year Chicago Urban Forest Climate Project indicate that there are an estimated 50.8 million trees in the Chicago area of Cook and DuPage Counties; 66 percent of these trees rated in good or excellent condition. During 1991, trees in the Chicago area removed an estimated 6,145 tons of air pollutants, providing air cleansing valued at $9.2 million...

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.

Mapping and industrial IT project to a 2nd semester design-build project

DEFF Research Database (Denmark)

Nyborg, Mads; Høgh, Stig

2010-01-01

CDIO means bringing the engineer's daily life and working practice into the educational system. In our opinion this is best done by selecting an appropriate project from industry. In this paper we describe how we have mapped an industrial IT project to a 2nd semester design-build project in the D......CDIO means bringing the engineer's daily life and working practice into the educational system. In our opinion this is best done by selecting an appropriate project from industry. In this paper we describe how we have mapped an industrial IT project to a 2nd semester design-build project...... in the Diploma IT program at the Technical University of Denmark. The system in question is a weighing system operating in a LAN environment. The system is used in the medical industry for producing tablets. We present the design of a curriculum to support the development of major components of the weighing...... system. A simple teaching model for software engineering is presented which combines technical disciplines with disciplines from section 2-4 in the CDIO syllabus. The implementation of a joint project involving several courses supports the CDIO perspective. Already the traditional IT-diploma education...

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

Science.gov (United States)

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

2018-04-01

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

Coastal Use Mapping Project - Northwest Hawai'i

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Hawaii Coastal Use Mapping Project is an innovative partnership between NOAA's National Marine Protected Areas Center, NOAA's Pacific Islands Fisheries Science...

Futures project anticipates changes and challenges facing forests of the northern United States

Science.gov (United States)

Stephen R. Shifley; W. Keith Moser; Michael E. Goerndt; Nianfu Song; Mark D. Nelson; David J. Nowak; Patrick D. Miles; Brett J. Butler; Ryan D. DeSantis; Francisco X. Aguilar; Brian G. Tavernia

2014-01-01

The Northern Forest Futures Project aims to reveal how today's trends and choices are likely to change the future forest landscape in the northeastern and midwestern United States. The research is focused on the 20-state quadrant bounded by Maine, Maryland, Missouri, and Minnesota. This area, which encompasses most of the Central Hardwood Forest region, is the...

Projected changes in the future distribution and production of sessile oak forests near the xeric limit

Science.gov (United States)

Gulyás, Krisztina; Berki, Imre; Veperdi, Gábor

2017-04-01

As a result of regional climate change, most European countries are experiencing an increase in mean annual temperature and CO2 concentration and a decrease in mean annual precipitation. In low-elevation areas in Southeast Europe, where precipitation is a limiting factor, the projected climate change threatens the health, production, and potential distribution of forest ecosystems. The intensive summer droughts and commonly occurring extreme weather events create negative influences that cause health declines, changes in yield potential, and tree mortality. Due to the observed damages, attention has been focused on these problems. The impacts of climatic extremes cause difficulties in forest management; these difficulties occur more frequently in Hungary, which is a region that is the most sensitive to climatic extremes. Regional climate model simulations project that the frequency of extremely high temperatures and long-term dry periods will increase; both of these factors have negative effects on future tree species distribution and production. Thus, the aim of our study is to utilize the sessile oak (Quercus petraea) as a climate indicator tree species to investigate potential future distribution and estimate changes in growth trends. For future spatial distribution, we used the Fuzzy membership distribution model in a new Decision Support System (DSS) which was developed for the Hungarian forestry and agricultural sectors. Through study techniques we can employ DSS, which contains various environmental layers (topography, vegetation, past and projected future climate, soils, and hydrology), to create probability distribution maps. The results, based on 12 regional climate model simulations (www.ensembles-eu.org), show that the area of sessile oak forests is shrinking continuously and will continue to do so to the end of the 21st century. For future production estimations, we analysed intensive long-term growth monitoring network plots that were established in

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

Earth-moving equipment as base machines in forest work. Final report of an NSR project

Energy Technology Data Exchange (ETDEWEB)

Johansson, Jerry [ed.

1997-12-31

Excavators have been used for forest draining for a long time in the Nordic countries. Only during the 1980s they were introduced as base machines for other forest operations, such as mounding, processing, harvesting, and road construction and road maintenance. Backhoe loaders were introduced in forestry at a somewhat later stage and to a smaller degree. The number of this type of base machines in forestry is so far small and is increasing very slowly. The NSR project `Earth moving equipment as base machines in forest work` started in 1993 and the project ended in 1995. The objective of the project was to obtain an overall picture of this type of machines up to a point where the logs are at landing site, ready for transportation to the industry. The project should cover as many aspects as possible. In order to obtain this picture, the main project was divided into sub projects. The sub projects separately described in this volume are (1) Excavators in ditching operations and site preparation, (2) Backhoe loaders in harvesting operations, (3) Excavators in wood cutting operations, (4) Tracked excavators in forestry operations, (5) Crawler versus wheeled base machines for single-grip harvester, and (6) Soil changes - A comparison between a wheeled and a tracked forest machine

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...

SAR China Land Mapping Project: Development, Production and Potential Applications

International Nuclear Information System (INIS)

Zhang, Lu; Guo, Huadong; Liu, Guang; Fu, Wenxue; Yan, Shiyong; Song, Rui; Ji, Peng; Wang, Xinyuan

2014-01-01

Large-area, seamless synthetic aperture radar (SAR) mosaics can reflect overall environmental conditions and highlight general trends in observed areas from a macroscopic standpoint, and effectively support research at the global scale, which is in high demand now across scientific fields. The SAR China Land Mapping Project (SCLM), supported by the Digital Earth Science Platform Project initiated and managed by the Center for Earth Observation and Digital Earth, Chinese Academy of Sciences (CEODE), is introduced in this paper. This project produced a large-area SAR mosaic dataset and generated the first complete seamless SAR map covering the entire land area of China using EnviSat-ASAR images. The value of the mosaic map is demonstrated by some potential applications in studies of urban distribution, rivers and lakes, geologic structures, geomorphology and paleoenvironmental change

75 FR 48305 - Kaibab National Forest; Arizona; Uranium Exploratory Drilling Project

Science.gov (United States)

2010-08-10

... Drilling Project AGENCY: Forest Service, USDA. ACTION: Notice; correction. SUMMARY: This is a correction to a notice of intent to prepare an Environmental Impact Statement for the Uranium Exploratory Drilling... Exploratory Drilling Project, 800 S. 6th St., Williams, AZ 86046. Questions may also be submitted by facsimile...

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

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Gregory P. Asner

2018-03-01

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

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

Science.gov (United States)

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

2017-10-01

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

Fisher research and the Kings River Sustainable Forest Ecosystem Project: current results and future efforts

Science.gov (United States)

Brian B. Boroski; Richard T. Golightly; Amie K. Mazzoni; Kimberly A. Sager

2002-01-01

The Kings River Sustainable Forest Ecosystems Project was initiated on the Kings River Ranger District of the Sierra National Forest, California, in 1993, with fieldwork beginning in 1994. Knowledge of the ecology of the fisher (Martes pennanti) in the Project area, and in the Sierra Nevada of California in general, is insufficient to develop...

75 FR 64243 - Umatilla National Forest, Walla Walla Ranger District; Oregon Tollgate Fuels Reduction Project

Science.gov (United States)

2010-10-19

.... This project was planned and will be implemented using Healthy Forest Restoration Act (HFRA) of 2004... actions will be conducted in accordance with the Healthy Forest Restoration Act (HFRA), National Forest... (fiber optic lines, telephone lines, power transmission lines, and communication equipment) is...

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

Science.gov (United States)

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

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 satellite data. A project was initiated in 1981 to compile a forestry map of southern Africa (Republic of South-Africa, Swaziland, Lesotho, Ciskei, Venda, Transkei and Bophuthatswana). A portfolio of 31 maps on a scale of 1:250 000 has now been produced...

A synthesis of evaluation monitoring projects by the forest health monitoring program (1998-2007)

Science.gov (United States)

William A. Bechtold; Michael J. Bohne; Barbara L. Conkling; Dana L. Friedman

2012-01-01

The national Forest Health Monitoring Program of the Forest Service, U.S. Department of Agriculture, has funded over 200 Evaluation Monitoring projects. Evaluation Monitoring is designed to verify and define the extent of deterioration in forest ecosystems where potential problems have been identified. This report is a synthesis of results from over 150 Evaluation...

Equidistant map projections of a triaxial ellipsoid with the use of reduced coordinates

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Pędzich Paweł

2017-12-01

Full Text Available The paper presents a new method of constructing equidistant map projections of a triaxial ellipsoid as a function of reduced coordinates. Equations for x and y coordinates are expressed with the use of the normal elliptic integral of the second kind and Jacobian elliptic functions. This solution allows to use common known and widely described in literature methods of solving such integrals and functions. The main advantage of this method is the fact that the calculations of x and y coordinates are practically based on a single algorithm that is required to solve the elliptic integral of the second kind. Equations are provided for three types of map projections: cylindrical, azimuthal and pseudocylindrical. These types of projections are often used in planetary cartography for presentation of entire and polar regions of extraterrestrial objects. The paper also contains equations for the calculation of the length of a meridian and a parallel of a triaxial ellipsoid in reduced coordinates. Moreover, graticules of three coordinates systems (planetographic, planetocentric and reduced in developed map projections are presented. The basic properties of developed map projections are also described. The obtained map projections may be applied in planetary cartography in order to create maps of extraterrestrial objects.

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

Science.gov (United States)

Ranson, K. J.; Sun, Guoqing

1992-01-01

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

Outlook for coastal plain forests: a subregional report from the Southern Forest Futures Project

Science.gov (United States)

Kier Klepzig; Richard Shelfer; Zanethia Choice

2014-01-01

The U.S. Coastal Plain consists of seven sections: the Northern Atlantic, Eastern Atlantic, Peninsular Florida, Southern Gulf, Middle Gulf-East, Middle Gulf-West, and Western Gulf. It covers a large area, consists of a diverse array of habitats, and supports a diverse array of uses. This report presents forecasts from the Southern Forest Futures Project that are...

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

Science.gov (United States)

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

2011-11-24

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

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.

Forest resources of the Nez Perce National Forest

Science.gov (United States)

Michele Disney

2010-01-01

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

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.

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

Directory of Open Access Journals (Sweden)

John Hogland

2018-04-01

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

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.

The mouse-human anatomy ontology mapping project.

Science.gov (United States)

Hayamizu, Terry F; de Coronado, Sherri; Fragoso, Gilberto; Sioutos, Nicholas; Kadin, James A; Ringwald, Martin

2012-01-01

The overall objective of the Mouse-Human Anatomy Project (MHAP) was to facilitate the mapping and harmonization of anatomical terms used for mouse and human models by Mouse Genome Informatics (MGI) and the National Cancer Institute (NCI). The anatomy resources designated for this study were the Adult Mouse Anatomy (MA) ontology and the set of anatomy concepts contained in the NCI Thesaurus (NCIt). Several methods and software tools were identified and evaluated, then used to conduct an in-depth comparative analysis of the anatomy ontologies. Matches between mouse and human anatomy terms were determined and validated, resulting in a highly curated set of mappings between the two ontologies that has been used by other resources. These mappings will enable linking of data from mouse and human. As the anatomy ontologies have been expanded and refined, the mappings have been updated accordingly. Insights are presented into the overall process of comparing and mapping between ontologies, which may prove useful for further comparative analyses and ontology mapping efforts, especially those involving anatomy ontologies. Finally, issues concerning further development of the ontologies, updates to the mapping files, and possible additional applications and significance were considered. DATABASE URL: http://obofoundry.org/cgi-bin/detail.cgi?id=ma2ncit.

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

Directory of Open Access Journals (Sweden)

Pierre Dubeau

2017-10-01

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

Ecosystem services to enhance sustainable forest management in the US: moving from forest service national programmes to local projects in the Pacific Northwest

Science.gov (United States)

Robert L. Deal; Nikola Smith; Joe Gates

2017-01-01

Ecosystem services are increasingly recognized as a way of framing and describing the broad suite of benefits that people receive from forests. The USDA Forest Service has been exploring use of an ecosystem services framework to describe forest values provided by federal lands and to attract and build partnerships with stakeholders to implement projects. Recently, the...

MAPPING DISTURBANCE DYNAMICS IN WET SCLEROPHYLL FORESTS USING TIME SERIES LANDSAT

Directory of Open Access Journals (Sweden)

A. Haywood

2016-06-01

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

Vegetation (MCV / NVCS) Mapping Projects - California [ds515

Data.gov (United States)

California Natural Resource Agency — This metadata layer shows the footprint of vegetation mapping projects completed in California that have used the Manual California of Vegetation ( MCV 1st edition)...

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

Science.gov (United States)

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

2017-09-01

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

75 FR 9388 - Prescott National Forest, Bradshaw Ranger District; Arizona; Bradshaw Vegetation Management Project

Science.gov (United States)

2010-03-02

...; Arizona; Bradshaw Vegetation Management Project AGENCY: Forest Service, USDA. ACTION: Notice of intent to prepare an environmental impact statement. SUMMARY: This project is a proposal to improve the health of.... The project area encompasses about 55,554 acres. Within the project area, the proposal is to...

75 FR 16728 - Beaver Creek Landscape Management Project, Ashland Ranger District, Custer National Forest...

Science.gov (United States)

2010-04-02

... DEPARTMENT OF AGRICULTURE Forest Service Beaver Creek Landscape Management Project, Ashland Ranger... manner that increases resiliency of the Beaver Creek Landscape Management Project area ecosystem to... requirements to require. The Beaver Creek Landscape Management Project includes treatments previously proposed...

Economics of forests and REDD+ projects: Translating lessons learned into national REDD+ implementation

Energy Technology Data Exchange (ETDEWEB)

Zaballa Romero, M.; Traerup, S.; Wieben, E.; Ravnkilde Moeller, L.; Koch, A.

2012-11-15

The financial implications of implementing a new forest management paradigm have not been well understood and have often been underestimated. Resource needs for e.g., stakeholder consultation, capacity building and addressing the political economy are seldom fully accounted for in the resource needs estimates put forward in connection to REDD+. This report investigates the economics of implementing forest and REDD+ projects through eight case studies from Africa, Latin America and Asia, analyzing real forest and REDD+ investments. (Author)

76 FR 13344 - Beaver Creek Landscape Management Project, Ashland Ranger District, Custer National Forest...

Science.gov (United States)

2011-03-11

... DEPARTMENT OF AGRICULTURE Forest Service Beaver Creek Landscape Management Project, Ashland Ranger... Impact Statement for the Beaver Creek Landscape Management Project was published in the Federal Register... Responsible Official for the Beaver Creek Landscape Management Project. DATES: The Final Environmental Impact...

Spatio-temporal evolution of forest fires in Portugal

Science.gov (United States)

Tonini, Marj; Pereira, Mário G.; Parente, Joana

2017-04-01

southern areas spread hot-spot are spatially randomly distributed and temporally more concentrated in the frame 2000 - 2004. To conclude, this study let us to identify a multitude of clustering space-time features of forest fires in Portugal, which can be useful for a better planning of educational activities and prevention campaigns as well as for a better allocation of monitoring systems and firefighting. References: Tonini M., Pereira M. G., Parente J. (2016) - Evolution of forest fires in Portugal: from spatio-temporal point events to smoothed density maps. Natural Hazard, doi:10.1007/s11069-016-2637-x Lu B., Harris P., Charlton M., Brunsdon C. (2014) - The GWmodel R package: further topics for exploring spatial heterogeneity using geographically weighted models. Geo-spatial Information Science, Vol. 17: 85-101 Rowlingson B., Diggle P., Bivand M.R. (2012) - Splancs: spatial point pattern analysis code in S-Plus. Computers and Geosciences, Vol. 19: 627-655 Acknowledgements: This work was supported by: (i) the FIREXTR project, PTDC/ATP¬GEO/0462/2014; (ii) the project Interact - Integrative Research in Environment,Agro-Chain and Technology, NORTE-01-0145-FEDER-000017, research line BEST, cofinanced by FEDER/NORTE 2020; and, (iii) European Investment Funds by FEDER/COMPETE/POCI-Operacional Competitiveness and Internacionalization Programme, under Project POCI-01-0145-FEDER-006958 and National Funds by FCT - Portuguese Foundation for Science and Technology, under the project UID/AGR/04033. We are especially grateful to ICNF for providing the fire.

Topography of the complete corticopontine projection: From experiments to principal maps

Directory of Open Access Journals (Sweden)

Trygve B Leergaard

2007-10-01

Full Text Available The mammalian brain is characterized by orderly spatial distribution of its cellular components, commonly referred to as topographical organization. The topography of cortical and subcortical maps is thought to represent functional or computational properties. In the present investigation, we have studied map transformations and organizing principles in the projections from the cerebral cortex to the pontine nuclei, with emphasis on the mapping of the cortex as a whole onto the pontine nuclei. Following single or multiple axonal tracer injections into different cortical regions, three-dimensional (3-D distributions of anterogradely labeled axons in the pontine nuclei were mapped. All 3-D reconstructed data sets were normalized to a standardized local coordinate system for the pontine nuclei and uploaded in a database application (FACCS, Functional Anatomy of the Cerebro-Cerebellar System, available via The Rodent Brain Workbench, http://www.rbwb.org. The database application allowed flexible use of the data in novel combinations, and use of a previously published data sets. Visualization of different combinations of data was used to explore alternative principles of organization. As a result of these analyses, a principal map of the topography of corticopontine projections was developed. This map followed the organization of early spatiotemporal gradients present in the cerebral cortex and the pontine nuclei. With the principal map for corticopontine projections, a fairly accurate prediction of pontine target area can be made for any site of origin in the cerebral cortex. The map and the underlying shared data sets represent a basis for modeling of topographical organization and structure-function relationships in this system.

Global Rural-Urban Mapping Project (GRUMP), Alpha Version

Data.gov (United States)

National Aeronautics and Space Administration — The Global Rural-Urban Mapping Project (GRUMP), Alpha Version consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km)...

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

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

Directory of Open Access Journals (Sweden)

Särkinen Tiina

2011-11-01

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

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

Science.gov (United States)

2011-01-01

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

Mapping practices of project management – merging top-down and bottom-up perspectives

DEFF Research Database (Denmark)

Thuesen, Christian

2015-01-01

This paper presents a new methodology for studying different accounts of project management practices based on network mapping and analysis. Drawing upon network mapping and visualization as an analytical strategy top-down and bottom-up accounts of project management practice are analysed...... and compared. The analysis initially reveals a substantial difference between the top-down and bottom-up accounts of practice. Furthermore it identifies a soft side of project management that is central in the bottom-up account but absent from the top-down. Finally, the study shows that network mapping...

76 FR 41192 - Mines Management Inc. Montanore Project, Kootenai National Forest, Lincoln County, MT

Science.gov (United States)

2011-07-13

... DEPARTMENT OF AGRICULTURE Forest Service Mines Management Inc. Montanore Project, Kootenai... can be reviewed at: http://www.fs.fed.usda.gov/goto/kootenai/projects . Mines Management Inc. owns two... of Environmental Quality, issued a Draft Environmental Impact Statement for the Montanore Project. In...

Projector primary-based optimization for superimposed projection mappings

Science.gov (United States)

Ahmed, Bilal; Lee, Jong Hun; Lee, Yong Yi; Lee, Kwan H.

2018-01-01

Recently, many researchers have focused on fully overlapping projections for three-dimensional (3-D) projection mapping systems but reproducing a high-quality appearance using this technology still remains a challenge. On top of existing color compensation-based methods, much effort is still required to faithfully reproduce an appearance that is free from artifacts, colorimetric inconsistencies, and inappropriate illuminance over the 3-D projection surface. According to our observation, this is due to the fact that overlapping projections are treated as an additive-linear mixture of color. However, this is not the case according to our elaborated observations. We propose a method that enables us to use high-quality appearance data that are measured from original objects and regenerate the same appearance by projecting optimized images using multiple projectors, ensuring that the projection-rendered results look visually close to the real object. We prepare our target appearances by photographing original objects. Then, using calibrated projector-camera pairs, we compensate for missing geometric correspondences to make our method robust against noise. The heart of our method is a target appearance-driven adaptive sampling of the projection surface followed by a representation of overlapping projections in terms of the projector-primary response. This gives off projector-primary weights to facilitate blending and the system is applied with constraints. These samples are used to populate a light transport-based system. Then, the system is solved minimizing the error to get the projection images in a noise-free manner by utilizing intersample overlaps. We ensure that we make the best utilization of available hardware resources to recreate projection mapped appearances that look as close to the original object as possible. Our experimental results show compelling results in terms of visual similarity and colorimetric error.

77 FR 53839 - Shasta-Trinity National Forest; California; East McCloud Plantations Thinning Project

Science.gov (United States)

2012-09-04

... actions include road maintenance and reconstruction of National Forest System, new road construction and... maintenance and 36 miles of reconstruction on National Forest System (NFS) roads. Existing unauthorized routes... be rehabilitated when no longer needed for this project. Maintenance Level 1 (intermittent use) roads...

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

Directory of Open Access Journals (Sweden)

Sebastián Martinuzzi

2008-06-01

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

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

Science.gov (United States)

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

2018-01-01

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

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}.

Forest Islands and Castaway Communities: REDD+ and Forest Restoration in Prey Lang Forest

Directory of Open Access Journals (Sweden)

Courtney Work

2017-02-01

Full Text Available Climate Change policies are playing an ever-increasing role in global development strategies and their implementation gives rise to often-unforeseen social conflicts and environmental degradations. A landscape approach to analyzing forest-based Climate Change Mitigation policies (CCM and land grabs in the Prey Lang Forest landscape, Cambodia revealed two Korea-Cambodia partnership projects designed to increase forest cover that are juxtaposed in this paper. Case study data revealed a REDD+ project with little negative impact or social conflict in the project area and an Afforestation/Reforestation (A/R project that created both social and ecological conflicts. The study concludes that forest-based CCM policies can reduce conflict through efforts at minimal transformation of local livelihoods, maximal attention to the tenure rights, responsibilities, and authority of citizens, and by improving, not degrading, the project landscapes. The paper presents the circumstances under which these guidelines are sidestepped by the A/R project, and importantly reveals that dramatic forest and livelihood transformation had already affected the community and environment in the REDD+ project site. There are deep contradictions at the heart of climate change policies toward which attention must be given, lest we leave our future generations with nothing but forest islands and castaway communities.

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

Science.gov (United States)

Victor A. Rudis

2000-01-01

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

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

Science.gov (United States)

Victor A. Rudis

2000-01-01

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

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

Deforestation projections for carbon-rich peat swamp forests of Central Kalimantan, Indonesia.

Science.gov (United States)

Fuller, Douglas O; Hardiono, Martin; Meijaard, Erik

2011-09-01

We evaluated three spatially explicit land use and cover change (LUCC) models to project deforestation from 2005-2020 in the carbon-rich peat swamp forests (PSF) of Central Kalimantan, Indonesia. Such models are increasingly used to evaluate the impact of deforestation on carbon fluxes between the biosphere and the atmosphere. We considered both business-as-usual (BAU) and a forest protection scenario to evaluate each model's accuracy, sensitivity, and total projected deforestation and landscape-level fragmentation patterns. The three models, Dinamica EGO (DE), GEOMOD and the Land Change Modeler (LCM), projected similar total deforestation amounts by 2020 with a mean of 1.01 million ha (Mha) and standard deviation of 0.17 Mha. The inclusion of a 0.54 Mha strict protected area in the LCM simulations reduced projected loss to 0.77 Mha over 15 years. Calibrated parameterizations of the models using nearly identical input drivers produced very different landscape properties, as measured by the number of forest patches, mean patch area, contagion, and Euclidean nearest neighbor determined using Fragstats software. The average BAU outputs of the models suggests that Central Kalimantan may lose slightly less than half (45.1%) of its 2005 PSF by 2020 if measures are not taken to reduce deforestation there. The relatively small reduction of 0.24 Mha in deforestation found in the 0.54 Mha protection scenario suggests that these models can identify potential leakage effects in which deforestation is forced to occur elsewhere in response to a policy intervention.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Science.gov (United States)

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

2014-02-01

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

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

Science.gov (United States)

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

2015-11-01

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

The Impact of Charcoal Production on Forest Degradation: a Case Study in Tete, Mozambique

Science.gov (United States)

Sedano, F.; Silva. J. A.; Machoco, R.; Meque, C. H.; Sitoe, A.; Ribeiro, N.; Anderson, K.; Ombe, Z. A.; Baule, S. H.; Tucker, C. J.

2016-01-01

Charcoal production for urban energy consumption is a main driver of forest degradation in sub-Saharan Africa. Urban growth projections for the continent suggest that the relevance of this process will increase in the coming decades. Forest degradation associated to charcoal production is difficult to monitor and commonly overlooked and underrepresented in forest cover change and carbon emission estimates. We use a multi-temporal dataset of very high-resolution remote sensing images to map kiln locations in a representative study area of tropical woodlands in central Mozambique. The resulting maps provided a characterization of the spatial extent and temporal dynamics of charcoal production. Using an indirect approach we combine kiln maps and field information on charcoal making to describe the magnitude and intensity of forest degradation linked to charcoal production, including aboveground biomass and carbon emissions. Our findings reveal that forest degradation associated to charcoal production in the study area is largely independent from deforestation driven by agricultural expansion and that its impact on forest cover change is in the same order of magnitude as deforestation. Our work illustrates the feasibility of using estimates of urban charcoal consumption to establish a link between urban energy demands and forest degradation. This kind of approach has potential to reduce uncertainties in forest cover change and carbon emission assessments in sub-Saharan Africa.

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 ...

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

OpenAIRE

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

2018-01-01

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

Moving Forest di Expo 2015

Directory of Open Access Journals (Sweden)

Michela Moretti

2015-12-01

Full Text Available The paper proposes a reading of the Expo 2015 landscape project through the essay "Moving Forest "by Franco Zagari and Benedetto Selleri; in which the authors trace the design process of the exposition site. It describes the design features of the green spaces that surround and mark the Exposition City. The green project is the connection between innovation, technology and rural landscape, like that surrounds the site. The Expo map represents one of the largest landscape projects in the last years in Europe, with its 300,000 square meters, organized in a sequence of different landscape that improve a gradual transition from the rural and natural landscape outside, to the urban landscape inside the exposition city.

Digitizing geographic data with GRIDOT; a generalized program for drawing overlay grids in various map projections

International Nuclear Information System (INIS)

Edwards, R.G.; Durfee, R.C.

1976-09-01

The GRIDOT computer program draws overlay grids on a Calcomp plotter for use in digitizing information from maps, rectified aerial photographs, and other sources of spatially distributed data related to regional environmental problems. The options of the program facilitate use of the overlays with standard maps and map projections of the continental United States. The overlay grid may be defined as a latitude-longitude grid (geodetic grid), a Universal Transverse Mercator Grid, or one of the standard state-plane coordinate system grids. The map for which the overlay is intended may be in an Albers Equal Area projection, a Lambert Conformal projection, a Polyconic projection, a Transverse Mercator projection, a Universal Transverse Mercator projection, or any of the standard state-plane projections

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-04-01

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

Forest Management and the Evolution of Project Design in Dynamic Wildland Urban Interface Fire Environments

Science.gov (United States)

Conway, S.

2014-12-01

The Truckee Ranger District on the Tahoe National Forest, in the heart of the Sierra Nevada Mountains, has a rich history of human activities. Native American influences, comstock-era logging, fire suppression, development, and recreation have all shaped the natural environment into what it is today. Like much of our national forests in California, forest conditions that have developed are generally much more homogenous and less resistant to disturbance from fire, insect, and disease than they might have been without the myriad of human influences. However, in order to improve the resiliency of our forests to stand replacing disturbances like high severity fire, while managing for integrated anthropomorphic values, it is imperative that management evolve to meet those dynamic needs. Recent advances in remote sensing and GIS allow land managers more access to forest information and can inform site specific prescriptions to change site specific undesirable conditions. It is ecologically and politically complex, yet our forests deserve that microscope. This particular presentation will focus on how the Truckee Ranger District began this process of incorporating several values, generated from stakeholder collaboration, into one project's goals and how those lessons learned informed their most recent project.

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.

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.

Forest biomass observation: current state and prospective

Directory of Open Access Journals (Sweden)

D. G. Schepaschenko

2017-08-01

Full Text Available With this article, we provide an overview of the methods, instruments and initiatives for forest biomass observation at global scale. We focus on the freely available information, provided by both remote and in-situ observations. The advantages and limitation of various space borne methods, including optical, radar (C, L and P band and LiDAR, as well as respective instruments available on the orbit (MODIS, Proba-V, Landsat, Sentinel-1, Sentinel-2 , ALOS PALSAR, Envisat ASAR or expecting (BIOMASS, GEDI, NISAR, SAOCOM-CS are discussed. We emphasize the role of in-situ methods in the development of a biomass models, providing calibration and validation of remote sensing data. We focus on freely available forest biomass maps, databases and empirical models. We describe the functionality of Biomass.Geo-Wiki.org portal, which provides access to a collection of global and regional biomass maps in full resolution with unified legend and units overplayed with high-resolution imagery. The Forest-Observation-System.net is announced as an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. Prospects of unmanned aerial vehicles in the forest inventory are briefly discussed. The work was partly supported by ESA IFBN project (contract 4000114425/15/NL/FF/gp.

Radarsat Antarctic Mapping Project Digital Elevation Model, Version 2

Data.gov (United States)

National Aeronautics and Space Administration — The high-resolution Radarsat Antarctic Mapping Project (RAMP) Digital Elevation Model (DEM) combines topographic data from a variety of sources to provide consistent...

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

International Nuclear Information System (INIS)

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

2011-01-01

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

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

Assessment of global and individual reproducibility of projective mapping with consumers

OpenAIRE

VIDAL, LETICIA; CADENA, RAFAEL SILVA; CORREA, SILVANA; ÁBALOS, ROSA A.; GÓMEZ, BEATRIZ; GIMÉNEZ, ANA; Varela, Paula; Ares, Gaston

2014-01-01

The popularity of projective mapping with consumers for sensory characterization has markedly increased in the last 5 years. To have confidence in this methodology,it is necessary to ensure that a similar product profile would emerge if the test was repeated. Also, deciding whether the study should be replicated or not is a key issue in test implementation. In this context, the aim of the present work was to evaluate global and individual reproducibility of projective mapping for sensory char...

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

Science.gov (United States)

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

1995-01-01

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

Improving Post-Hurricane Katrina Forest Management with MODIS Time Series Products

Science.gov (United States)

Lewis, Mark David; Spruce, Joseph; Evans, David; Anderson, Daniel

2012-01-01

Hurricane damage to forests can be severe, causing millions of dollars of timber damage and loss. To help mitigate loss, state agencies require information on location, intensity, and extent of damaged forests. NASA's MODerate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series data products offers a potential means for state agencies to monitor hurricane-induced forest damage and recovery across a broad region. In response, a project was conducted to produce and assess 250 meter forest disturbance and recovery maps for areas in southern Mississippi impacted by Hurricane Katrina. The products and capabilities from the project were compiled to aid work of the Mississippi Institute for Forest Inventory (MIFI). A series of NDVI change detection products were computed to assess hurricane induced damage and recovery. Hurricane-induced forest damage maps were derived by computing percent change between MODIS MOD13 16-day composited NDVI pre-hurricane "baseline" products (2003 and 2004) and post-hurricane NDVI products (2005). Recovery products were then computed in which post storm 2006, 2007, 2008 and 2009 NDVI data was each singularly compared to the historical baseline NDVI. All percent NDVI change considered the 16-day composite period of August 29 to September 13 for each year in the study. This provided percent change in the maximum NDVI for the 2 week period just after the hurricane event and for each subsequent anniversary through 2009, resulting in forest disturbance products for 2005 and recovery products for the following 4 years. These disturbance and recovery products were produced for the Mississippi Institute for Forest Inventory's (MIFI) Southeast Inventory District and also for the entire hurricane impact zone. MIFI forest inventory products were used as ground truth information for the project. Each NDVI percent change product was classified into 6 categories of forest disturbance intensity. Stand age

Mapping Best and Emerging Practices of Project Management

OpenAIRE

Thuesen, Christian; Aaris Boas, Charlotte; Thorslund, Michael V.; Marmier, Francois; Grex, Sara; Lybecker, Søren

2013-01-01

This paper presents results of a study of the connection between Best and Emerging practices of project management. Drawing upon network mapping as an analytical strategy, cases of Best and Emerging practices is analysed and juxtaposed. The case of Best practice is represented by the newly published ISO 21500 standard and the case for the Emerging practices by a deconstruction of the practices of a group of experienced project managers. The network analysis reveals a substantial difference be...

Mapping Forest Edge Using Aerial Lidar

Science.gov (United States)

MacLean, M. G.

2014-12-01

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

Project Mapping to Build Capacity and Demonstrate Impact in the Earth Sciences

Science.gov (United States)

Hemmings, S. N.; Searby, N. D.; Murphy, K. J.; Mataya, C. J.; Crepps, G.; Clayton, A.; Stevens, C. L.

2017-12-01

Diverse organizations are increasingly using project mapping to communicate location-based information about their activities. NASA's Earth Science Division (ESD), through the Earth Science Data Systems and Applied Sciences' Capacity Building Program (CBP), has created a geographic information system of all ESD projects to support internal program management for the agency. The CBP's NASA DEVELOP program has built an interactive mapping tool to support capacity building for the program's varied constituents. This presentation will explore the types of programmatic opportunities provided by a geographic approach to management, communication, and strategic planning. We will also discuss the various external benefits that mapping supports and that build capacity in the Earth sciences. These include activities such as project matching (location-focused synergies), portfolio planning, inter- and intra-organizational collaboration, science diplomacy, and basic impact analysis.

Age structure and disturbance legacy of North American forests

Directory of Open Access Journals (Sweden)

Y. Pan

2011-03-01

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

78 FR 21590 - Coconino National Forest; Arizona; Flagstaff Watershed Protection Project

Science.gov (United States)

2013-04-11

... watersheds around Flagstaff. Specifically, two key areas have been identified for analysis and treatment... Mary Watershed. The FWPP analysis area includes portions of the Coconino National Forest that have... Watershed Protection Project, and is participating in the planning and analysis process. Responsible...

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

Science.gov (United States)

Mitri, George H.; Gitas, Ioannis Z.

2013-02-01

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

Recent trends, drivers, and projections of carbon cycle processes in forests and grasslands of North America

Science.gov (United States)

Domke, G. M.; Williams, C. A.; Birdsey, R.; Pendall, E.

2017-12-01

In North America forest and grassland ecosystems play a major role in the carbon cycle. Here we present the latest trends and projections of United States and North American carbon cycle processes, stocks, and flows in the context of interactions with global scale budgets and climate change impacts in managed and unmanaged grassland and forest ecosystems. We describe recent trends in natural and anthropogenic disturbances in these ecosystems as well as the carbon dynamics associated with land use and land cover change. We also highlight carbon management science and tools for informing decisions and opportunities for improving carbon measurements, observations, and projections in forests and grasslands.

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

Science.gov (United States)

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

2017-12-01

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

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

Science.gov (United States)

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

2017-09-01

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

Mapping critical levels/loads for the Slovak Republic. Final Report

Energy Technology Data Exchange (ETDEWEB)

Zavodsky, D; Babiakova, G; Mitosinkova, M [and others

1996-08-01

As a part of the Agreement on Environmental Cooperation between Norway and Slovakia a project ``Mapping Critical Levels/Loads for Slovakia`` was established. This report presents the final project results. Critical loads for forest, surface and ground waters and their exceedances were calculated by means of the steady-state mass balance model PROFILE for soils, and the steady-state water chemistry method for waters. A grid distance of 10 km was used. Because the sulphur deposition has been decreasing, the exceedances of critical load of acidity and critical sulphur deposition of forest soils have decreased from 1990 to 1995. Practically no acidity exceedances for surface water or ground water were found in 1995. The critical level of forest ozone was exceeded all over Slovakia. In the Tatra mountains the exceedance was over 25000 ppb.h. 23 refs., 3 figs., 3 tabs.

Evaluation of radionuclide migration in forest ecosystems in TEMAS project

International Nuclear Information System (INIS)

Claver, F.; Vazquez, C.

1998-01-01

The applicability study of the best countermeasures for the restoration of environments contaminated by the accidental liberation of radionuclides, requires the assessment of the space and the temporal flow of radionuclides. The objective of the multinational project TEMAS (Techniques and Management Strategies for environmental restoration and their ecological consequences), that is carried out under EU-CIEMAT contract n. TI4-CT95-0021, is the development of management tool that provides the necessary support in the selection of the best strategies of environmental restoration after a nuclear accident, considering all the possible affected environments (urban, agricultural, semi natural and forest). In the forest environment,CIEMAT is working with the University of Lund (Sweden) and the Physical Science Faculty of the University of Seville in the prognosis of the distribution of Cesium and Strontium in forest ecosystems and through the associated production systems. This paper summarizes the study of the response of two different models, FORM and FORESTPATH to predict the radionuclides flow in the event of an accidental contamination of a forest. The comparison of results has been carried out over a period of 100 years after deposition on a coniferous forest. Although the approaches are different, the results obtained (using generic parameters) indicate that either model could to be selected for the analysis of the intervention in TEMAS. (Author) 14 refs

Forest conservation and the clean development mechanism. Lessons from the Costa Rican protected areas project

International Nuclear Information System (INIS)

Voehringer, F.

2004-01-01

Deforestation is currently the source of about 20% of anthropogenic CO2 emissions. Avoided deforestation has, nonetheless, been ruled out as a Clean Development Mechanism (CDM) category in the Kyoto Protocol's first commitment period, because several methodological issues were considered too difficult to resolve. This paper explores whether CDM issues such as (1) carbon quantification, (2) additionality and baseline setting, (3) leakage risks, (4) non-permanence risks, and (5) sustainable development can be adequately dealt with in large, diversified forest conservation projects. To this aim, it studies the case of the Costa Rican Protected Areas Project (PAP), an Activities Implemented Jointly (AIJ) project which was meant to consolidate the national park system to avoid deforestation, promote the growth of secondary forests and regenerate pastures on an area that, in total, covers 10% of the national territory. The case study examines how the issues mentioned above have been addressed in the project design and in the certification process. It is found that baseline uncertainties are the major problem in this case. Nonetheless, the case suggests the possibility to address CDM issues by specific requirements for project design and very conservative and temporary crediting. Provided that other case studies support this conclusion, eligibility of well-designed forest conservation projects under the CDM in the second commitment period may be worth considering, given the secondary benefits of avoided deforestation

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

DEFF Research Database (Denmark)

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

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

The contribution of meteorological surveys to the analysis of forest ecosystems: the FutMon project

Directory of Open Access Journals (Sweden)

Salvati L

2013-09-01

Full Text Available Much of the wide variation in plant morphology, physiology and development biology is reflected in the capacity to adapt to climate changes. The aim of this paper is to contribute to the climate description of selected Italian forest sites (the CONECOFOR network where a permanent environmental monitoring was carried out since 1997 within the ICP-Forests, ICP-IM framework Forest Focus Reg. and the EU-funded FutMon research project.

The National Map - Missouri Pilot Project

Science.gov (United States)

,

2001-01-01

Governments depend on a common set of geographic base information as a tool for economic and community development, land and natural resource management, and health and safety services. Emergency management and defense operations rely on this information. Private industry, nongovernmental organizations, and individual citizens use the same geographic data. Geographic information underpins an increasingly large part of the Nation's economy. Available geographic data often have the following problems: * They do not align with each other because layers are frequently created or revised separately, * They do not match across administrative boundaries because each producing organization uses different methods and standards, and * They are not up to date because of the complexity and cost of revision. The U.S. Geological Survey (USGS) is developing The National Map to be a seamless, continuously maintained, and nationally consistent set of online, public domain, geographic base information to address these issues. The National Map will serve as a foundation for integrating, sharing, and using other data easily and consistently. In collaboration with other government agencies, the private sector, academia, and volunteer groups, the USGS will coordinate, integrate, and, where needed, produce and maintain base geographic data. The National Map will include digital orthorectified imagery; elevation data; vector data for hydrography, transportation, boundary, and structure features; geographic names; and land cover information. The data will be the source of revised paper topographic maps. Many technical and institutional issues must be resolved as The National Map is implemented. To begin the refinement of this new paradigm, pilot projects are being designed to identify and investigate these issues. The pilots are the foundation upon which future partnerships for data sharing and maintenance will be built.

The National Map - Delaware Pilot Project

Science.gov (United States)

,

2001-01-01

Governments depend on a common set of geographic base information as a tool for economic and community development, land and natural resource management, and health and safety services. Emergency management and defense operations rely on this information. Private industry, nongovernmental organizations, and individual citizens use the same geographic data. Geographic information underpins an increasingly large part of the Nation's economy. Available geographic data often have the following problems: * They do not align with each other because layers are frequently created or revised separately, * They do not match across administrative boundaries because each producing organization uses different methods and standards, and * They are not up to date because of the complexity and cost of revision. The U.S. Geological Survey (USGS) is developing The National Map to be a seamless, continuously maintained, and nationally consistent set of online, public domain, geographic base information to address these issues. The National Map will serve as a foundation for integrating, sharing, and using other data easily and consistently. In collaboration with other government agencies, the private sector, academia, and volunteer groups, the USGS will coordinate, integrate, and, where needed, produce and maintain base geographic data. The National Map will include digital orthorectified imagery; elevation data; vector data for hydrography, transportation, boundary, and structure features; geographic names; and land cover information. The data will be the source of revised paper topographic maps. Many technical and institutional issues must be resolved as The National Map is implemented. To begin the refinement of this new paradigm, pilot projects are being designed to identify and investigate these issues. The pilots are the foundation upon which future partnerships for data sharing and maintenance will be built.

The National Map - Pennsylvania Pilot Project

Science.gov (United States)

,

2001-01-01

Governments depend on a common set of geographic base information as a tool for economic and community development, land and natural resource management, and health and safety services. Emergency management and defense operations rely on this information. Private industry, nongovernmental organizations, and individual citizens use the same geographic data. Geographic information underpins an increasingly large part of the Nation's economy. Available geographic data often have the following problems: * They do not align with each other because layers are frequently created or revised separately, * They do not match across administrative boundaries because each producing organization uses different methods and standards, and * They are not up to date because of the complexity and cost of revision. The U.S. Geological Survey (USGS) is developing The National Map to be a seamless, continuously maintained, and nationally consistent set of online, public domain, geographic base information to address these issues. The National Map will serve as a foundation for integrating, sharing, and using other data easily and consistently. In collaboration with other government agencies, the private sector, academia, and volunteer groups, the USGS will coordinate, integrate, and, where needed, produce and maintain base geographic data. The National Map will include digital orthorectified imagery; elevation data; vector data for hydrography, transportation, boundary, and structure features; geographic names; and land cover information. The data will be the source of revised paper topographic maps. Many technical and institutional issues must be resolved as The National Map is implemented. To begin the refinement of this new paradigm, pilot projects are being designed to identify and investigate these issues. The pilots are the foundation upon which future partnerships for data sharing and maintenance will be built.

The National Map - Texas Pilot Project

Science.gov (United States)

,

2001-01-01

Governments depend on a common set of geographic base information as a tool for economic and community development, land and natural resource management, and health and safety services. Emergency management and defense operations rely on this information. Private industry, nongovernmental organizations, and individual citizens use the same geographic data. Geographic information underpins an increasingly large part of the Nation's economy. Available geographic data often have the following problems: * They do not align with each other because layers are frequently created or revised separately, * They do not match across administrative boundaries because each producing organization uses different methods and standards, and * They are not up to date because of the complexity and cost of revision. The U.S. Geological Survey (USGS) is developing The National Map to be a seamless, continuously maintained, and nationally consistent set of online, public domain, geographic base information to address these issues. The National Map will serve as a foundation for integrating, sharing, and using other data easily and consistently. In collaboration with other government agencies, the private sector, academia, and volunteer groups, the USGS will coordinate, integrate, and, where needed, produce and maintain base geographic data. The National Map will include digital orthorectified imagery; elevation data; vector data for hydrography, transportation, boundary, and structure features; geographic names; and land cover information. The data will be the source of revised paper topographic maps. Many technical and institutional issues must be resolved as The National Map is implemented. To begin the refinement of this new paradigm, pilot projects are being designed to identify and investigate these issues. The pilots are the foundation upon which future partnerships for data sharing and maintenance will be built.

The National Map - Florida Pilot Project

Science.gov (United States)

,

2001-01-01

Governments depend on a common set of geographic base information as a tool for economic and community development, land and natural resource management, and health and safety services. Emergency management and defense operations rely on this information. Private industry, nongovernmental organizations, and individual citizens use the same geographic data. Geographic information underpins an increasingly large part of the Nation's economy. Available geographic data often have the following problems: * They do not align with each other because layers are frequently created or revised separately, * They do not match across administrative boundaries because each producing organization uses different methods and standards, and * They are not up to date because of the complexity and cost of revision. The U.S. Geological Survey (USGS) is developing The National Map to be a seamless, continuously maintained, and nationally consistent set of online, public domain, geographic base information to address these issues. The National Map will serve as a foundation for integrating, sharing, and using other data easily and consistently. In collaboration with other government agencies, the private sector, academia, and volunteer groups, the USGS will coordinate, integrate, and, where needed, produce and maintain base geographic data. The National Map will include digital orthorectified imagery; elevation data; vector data for hydrography, transportation, boundary, and structure features; geographic names; and land cover information. The data will be the source of revised paper topographic maps. Many technical and institutional issues must be resolved as The National Map is implemented. To begin the refinement of this new paradigm, pilot projects are being designed to identify and investigate these issues. The pilots are the foundation upon which future partnerships for data sharing and maintenance will be built.

Mapping data through concept maps: an auxiliary tool for decision making regarding institutional projects

International Nuclear Information System (INIS)

D’Avila, Adriana L.

2017-01-01

This paper reports a data mapping construction aimed to subsidize the decision making process regarding institutional projects, at different levels of responsibility, at the Instituto de Engenharia Nuclear. The conception models a systemic and adaptive tool which is based on the concept mapping theory developed by Novak. The Instituto de Engenharia Nuclear (IEN) is a research center of the Comissão de Energia Nuclear (CNEN), an autarchy attached to Ministério da Ciência, Tecnologia, Inovações e Comunicações. The main focus of IEN is research and development of nuclear science and technology. The developed tool creates a more effective and accessible way of sharing information. However, beyond project data integration into a specific instrument, it also has the intent to compensate the consequences of the continued reduction of the number of workers at IEN over recent years. The recent CNEN management report, published in 2016, showed the problematic situation caused by the loss of workers, stressing the high number of pensions granted and to be granted in the near future. The loss of labor force, besides exposing the urgent need for optimizing knowledge management efforts, also sheds light into another problem: the need for grouping responsibilities among the remaining workers. In this respect, the tool developed helps to face this challenge, enhancing autonomy at different levels but preserving the institutional guidelines. To conclude the report, and in order to exemplify the method, the paper also describes the map construction relative an innovative project proposal in a joint development towards the nuclear area. (author)

Mapping data through concept maps: an auxiliary tool for decision making regarding institutional projects

Energy Technology Data Exchange (ETDEWEB)

D’Avila, Adriana L., E-mail: adriana@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil). Divisão de Engenharia Nuclear

2017-11-01

This paper reports a data mapping construction aimed to subsidize the decision making process regarding institutional projects, at different levels of responsibility, at the Instituto de Engenharia Nuclear. The conception models a systemic and adaptive tool which is based on the concept mapping theory developed by Novak. The Instituto de Engenharia Nuclear (IEN) is a research center of the Comissão de Energia Nuclear (CNEN), an autarchy attached to Ministério da Ciência, Tecnologia, Inovações e Comunicações. The main focus of IEN is research and development of nuclear science and technology. The developed tool creates a more effective and accessible way of sharing information. However, beyond project data integration into a specific instrument, it also has the intent to compensate the consequences of the continued reduction of the number of workers at IEN over recent years. The recent CNEN management report, published in 2016, showed the problematic situation caused by the loss of workers, stressing the high number of pensions granted and to be granted in the near future. The loss of labor force, besides exposing the urgent need for optimizing knowledge management efforts, also sheds light into another problem: the need for grouping responsibilities among the remaining workers. In this respect, the tool developed helps to face this challenge, enhancing autonomy at different levels but preserving the institutional guidelines. To conclude the report, and in order to exemplify the method, the paper also describes the map construction relative an innovative project proposal in a joint development towards the nuclear area. (author)

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

Directory of Open Access Journals (Sweden)

A. Verhegghen

2012-12-01

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

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

Directory of Open Access Journals (Sweden)

Wilson Barry Tyler

2013-01-01

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

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

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

Corrosion map for metal pipes in coastal Louisiana : research project capsule.

Science.gov (United States)

2016-03-01

The objective of this project is to create a guidance document with maps : that delineate zones where metal pipe is prone to increased corrosion due : to environmental conditions. Results from this project will provide a logical : rationale to suppor...

Michigan forest ecosystem vulnerability assessment and synthesis: a report from the Northwoods Climate Change Response Framework project

Science.gov (United States)

Stephen Handler; Matthew J. Duveneck; Louis Iverson; Emily Peters; Robert M. Scheller; Kirk R. Wythers; Leslie Brandt; Patricia Butler; Maria Janowiak; P. Danielle Shannon; Chris Swanston; Amy Clark Eagle; Joshua G. Cohen; Rich Corner; Peter B. Reich; Tim Baker; Sophan Chhin; Eric Clark; David Fehringer; Jon Fosgitt; James Gries; Christine Hall; Kimberly R. Hall; Robert Heyd; Christopher L. Hoving; Ines Ibáñez; Don Kuhr; Stephen Matthews; Jennifer Muladore; Knute Nadelhoffer; David Neumann; Matthew Peters; Anantha Prasad; Matt Sands; Randy Swaty; Leiloni Wonch; Jad Daley; Mae Davenport; Marla R. Emery; Gary Johnson; Lucinda Johnson; David Neitzel; Adena Rissman; Chadwick Rittenhouse; Robert. Ziel

2014-01-01

Forests in northern Michigan will be affected directly and indirectly by a changing climate during the next 100 years. This assessment evaluates the vulnerability of forest ecosystems in Michigan's eastern Upper Peninsula and northern Lower Peninsula to a range of future climates. Information on current forest conditions, observed climate trends, projected climate...

Evidence and implications of recent and projected climate change in Alaska's forest ecosystems

Science.gov (United States)

Wolken, Jane M.; Hollingsworth, Teresa N.; Rupp, T. Scott; Chapin, Stuart III; Trainor, Sarah F.; Barrett, Tara M.; Sullivan, Patrick F.; McGuire, A. David; Euskirchen, Eugénie S.; Hennon, Paul E.; Beever, Erik A.; Conn, Jeff S.; Crone, Lisa K.; D'Amore, David V.; Fresco, Nancy; Hanley, Thomas A.; Kielland, Knut; Kruse, James J.; Patterson, Trista; Schuur, Edward A.G.; Verbyla, David L.; Yarie, John

2011-01-01

The structure and function of Alaska's forests have changed significantly in response to a changing climate, including alterations in species composition and climate feedbacks (e.g., carbon, radiation budgets) that have important regional societal consequences and human feedbacks to forest ecosystems. In this paper we present the first comprehensive synthesis of climate-change impacts on all forested ecosystems of Alaska, highlighting changes in the most critical biophysical factors of each region. We developed a conceptual framework describing climate drivers, biophysical factors and types of change to illustrate how the biophysical and social subsystems of Alaskan forests interact and respond directly and indirectly to a changing climate. We then identify the regional and global implications to the climate system and associated socio-economic impacts, as presented in the current literature. Projections of temperature and precipitation suggest wildfire will continue to be the dominant biophysical factor in the Interior-boreal forest, leading to shifts from conifer- to deciduous-dominated forests. Based on existing research, projected increases in temperature in the Southcentral- and Kenai-boreal forests will likely increase the frequency and severity of insect outbreaks and associated wildfires, and increase the probability of establishment by invasive plant species. In the Coastal-temperate forest region snow and ice is regarded as the dominant biophysical factor. With continued warming, hydrologic changes related to more rapidly melting glaciers and rising elevation of the winter snowline will alter discharge in many rivers, which will have important consequences for terrestrial and marine ecosystem productivity. These climate-related changes will affect plant species distribution and wildlife habitat, which have regional societal consequences, and trace-gas emissions and radiation budgets, which are globally important. Our conceptual framework facilitates

Project risk and appeals in U.S. Forest Service planning

International Nuclear Information System (INIS)

Stern, Marc J.; Predmore, S. Andrew; Morse, Wayde C.; Seesholtz, David N.

2013-01-01

The National Environmental Policy Act (NEPA) requires U.S. Forest Service planning processes to be conducted by interdisciplinary teams of resource specialists to analyze and disclose the likely environmental impacts of proposed natural resource management actions on Forest Service lands. Multiple challenges associated with these processes have been a source of frustration for the agency. One of these challenges involves administrative appeals through which public entities can challenge a Forest Service decision following a NEPA process. These appeals instigate an internal review process and can result in an affirmation of the Forest Service decision, a reversal of that decision, or additional work that re-initiates all or part of the NEPA process. We examine the best predictors of appeals and their outcomes on a representative sample of 489 Forest Service NEPA processes that were decided between 2007 and 2009. While certain factors associated with pre-existing social contexts (such as a history of controversy) or pre-determined elements of a proposed action (such as the extraction of forest products) predispose certain processes to a higher risk of appeals, other practices and process-related strategies within the control of the agency also appear to bear meaningful influence on the occurrence of appeals and their outcomes. Appeals and their outcomes were most strongly related to programmatic, structural (turnover of personnel in particular), and relationship risks (both internal and external) within the processes, suggesting the need for greater focus within the agency on cultivating positive internal and external relationships to manage the risk of appeals. -- Highlights: ► We examined appeals and their outcomes on 489 U.S. Forest Service NEPA processes. ► Project type, context, team turnover, and personal relationships predicted appeals. ► External relationship management and staff turnover best predicted appeal outcomes. ► Positive internal and

Project risk and appeals in U.S. Forest Service planning

Energy Technology Data Exchange (ETDEWEB)

Stern, Marc J., E-mail: mjstern@vt.edu [Department of Forest Resources and Environmental Conservation, Virginia Tech, 304 Cheatham Hall (0324), Blacksburg, VA 24061 (United States); Predmore, S. Andrew, E-mail: spred2@uis.edu [Department of Environmental Studies, University of Illinois-Springfield, Public Affairs Center, Room 314, Springfield, IL 62703 (United States); Morse, Wayde C., E-mail: morsewc@auburn.edu [School of Forestry and Wildlife Sciences, Auburn University, 3301 Forestry and Wildlife Bldg., Auburn, AL 36849 (United States); Seesholtz, David N., E-mail: dseesholtz@fs.fed.us [Focused Science Delivery Program, Pacific Northwest Research Station, USDA Forest Service, 1249S Vinnell Way, Suite 200, Boise, ID 83709 (United States)

2013-09-15

The National Environmental Policy Act (NEPA) requires U.S. Forest Service planning processes to be conducted by interdisciplinary teams of resource specialists to analyze and disclose the likely environmental impacts of proposed natural resource management actions on Forest Service lands. Multiple challenges associated with these processes have been a source of frustration for the agency. One of these challenges involves administrative appeals through which public entities can challenge a Forest Service decision following a NEPA process. These appeals instigate an internal review process and can result in an affirmation of the Forest Service decision, a reversal of that decision, or additional work that re-initiates all or part of the NEPA process. We examine the best predictors of appeals and their outcomes on a representative sample of 489 Forest Service NEPA processes that were decided between 2007 and 2009. While certain factors associated with pre-existing social contexts (such as a history of controversy) or pre-determined elements of a proposed action (such as the extraction of forest products) predispose certain processes to a higher risk of appeals, other practices and process-related strategies within the control of the agency also appear to bear meaningful influence on the occurrence of appeals and their outcomes. Appeals and their outcomes were most strongly related to programmatic, structural (turnover of personnel in particular), and relationship risks (both internal and external) within the processes, suggesting the need for greater focus within the agency on cultivating positive internal and external relationships to manage the risk of appeals. -- Highlights: ► We examined appeals and their outcomes on 489 U.S. Forest Service NEPA processes. ► Project type, context, team turnover, and personal relationships predicted appeals. ► External relationship management and staff turnover best predicted appeal outcomes. ► Positive internal and

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

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

Directory of Open Access Journals (Sweden)

Adrienne Grêt-Regamey

2013-09-01

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

Examining fire-induced forest changes using novel remote sensing technique: a case study in a mixed pine-oak forest

Science.gov (United States)

Meng, R.; Wu, J.; Zhao, F. R.; Cook, B.; Hanavan, R. P.; Serbin, S.

2017-12-01

Fire-induced forest changes has long been a central focus for forest ecology and global carbon cycling studies, and is becoming a pressing issue for global change biologists particularly with the projected increases in the frequency and intensity of fire with a warmer and drier climate. Compared with time-consuming and labor intensive field-based approaches, remote sensing offers a promising way to efficiently assess fire effects and monitor post-fire forest responses across a range of spatial and temporal scales. However, traditional remote sensing studies relying on simple optical spectral indices or coarse resolution imagery still face a number of technical challenges, including confusion or contamination of the signal by understory dynamics and mixed pixels with moderate to coarse resolution data (>= 30 m). As such, traditional remote sensing may not meet the increasing demand for more ecologically-meaningful monitoring and quantitation of fire-induced forest changes. Here we examined the use of novel remote sensing technique (i.e. airborne imaging spectroscopy and LiDAR measurement, very high spatial resolution (VHR) space-borne multi-spectral measurement, and high temporal-spatial resolution UAS-based (Unmanned Aerial System) imagery), in combination with field and phenocam measurements to map forest burn severity across spatial scales, quantify crown-scale post-fire forest recovery rate, and track fire-induced phenology changes in the burned areas. We focused on a mixed pine-oak forest undergoing multiple fire disturbances for the past several years in Long Island, NY as a case study. We demonstrate that (1) forest burn severity mapping from VHR remote sensing measurement can capture crown-scale heterogeneous fire patterns over large-scale; (2) the combination of VHR optical and structural measurements provides an efficient means to remotely sense species-level post-fire forest responses; (3) the UAS-based remote sensing enables monitoring of fire

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

Directory of Open Access Journals (Sweden)

Christian Hüttich

2014-07-01

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

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

Directory of Open Access Journals (Sweden)

Sebastian van der Linden

2013-05-01

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

Cowichan Valley energy mapping and modelling. Report 5 - Energy density mapping projections. Final report. [Vancouver Island, Canada

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-06-15

The driving force behind the Integrated Energy Mapping and Analysis project was the identification and analysis of a suite of pathways that the Cowichan Valley Regional District (CVRD) can utilise to increase its energy resilience, as well as reduce energy consumption and GHG emissions, with a primary focus on the residential sector. Mapping and analysis undertaken will support provincial energy and GHG reduction targets, and the suite of pathways outlined will address a CVRD internal target that calls for 75% of the region's energy within the residential sector to come from locally sourced renewables by 2050. The target has been developed as a mechanism to meet resilience and climate action target. The maps and findings produced are to be integrated as part of a regional policy framework currently under development. Task 5 focused on energy projection mapping to estimate and visualise the energy consumption density and GHG emissions under different scenarios. The scenarios from task 4 were built around the energy consumption density of the residential sector under future land use patterns and rely on different energy source combinations (the suite of pathways). In task 5 the energy usage under the different scenarios were fed back into GIS, thereby giving a visual representation of forecasted residential energy consumption per unit area. The methodology is identical to that used in task 2 where current usage was mapped, whereas the mapping in this task is for future forecasts. These results are documented in this report. In addition, GHG mapping under the various scenarios was also undertaken. (LN)

Variances in the projections, resulting from CLIMEX, Boosted Regression Trees and Random Forests techniques

Science.gov (United States)

Shabani, Farzin; Kumar, Lalit; Solhjouy-fard, Samaneh

2017-08-01

The aim of this study was to have a comparative investigation and evaluation of the capabilities of correlative and mechanistic modeling processes, applied to the projection of future distributions of date palm in novel environments and to establish a method of minimizing uncertainty in the projections of differing techniques. The location of this study on a global scale is in Middle Eastern Countries. We compared the mechanistic model CLIMEX (CL) with the correlative models MaxEnt (MX), Boosted Regression Trees (BRT), and Random Forests (RF) to project current and future distributions of date palm ( Phoenix dactylifera L.). The Global Climate Model (GCM), the CSIRO-Mk3.0 (CS) using the A2 emissions scenario, was selected for making projections. Both indigenous and alien distribution data of the species were utilized in the modeling process. The common areas predicted by MX, BRT, RF, and CL from the CS GCM were extracted and compared to ascertain projection uncertainty levels of each individual technique. The common areas identified by all four modeling techniques were used to produce a map indicating suitable and unsuitable areas for date palm cultivation for Middle Eastern countries, for the present and the year 2100. The four different modeling approaches predict fairly different distributions. Projections from CL were more conservative than from MX. The BRT and RF were the most conservative methods in terms of projections for the current time. The combination of the final CL and MX projections for the present and 2100 provide higher certainty concerning those areas that will become highly suitable for future date palm cultivation. According to the four models, cold, hot, and wet stress, with differences on a regional basis, appears to be the major restrictions on future date palm distribution. The results demonstrate variances in the projections, resulting from different techniques. The assessment and interpretation of model projections requires reservations

A comparison of selected parametric and non-parametric imputation methods for estimating forest biomass and basal area

Science.gov (United States)

Donald Gagliasso; Susan Hummel; Hailemariam. Temesgen

2014-01-01

Various methods have been used to estimate the amount of above ground forest biomass across landscapes and to create biomass maps for specific stands or pixels across ownership or project areas. Without an accurate estimation method, land managers might end up with incorrect biomass estimate maps, which could lead them to make poorer decisions in their future...

76 FR 22668 - Shasta-Trinity National Forest; California; I-5 Corridor Fuels Reduction Project

Science.gov (United States)

2011-04-22

... environmental impact statement. SUMMARY: The Shasta Unit of the Shasta-Trinity National Forest is proposing a hazardous fuels treatment project to reduce the risk of life, property and resource values from a high... 20,025 acres of the project area is proposed for treatment. Treatment methods include prescribe fire...

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

Hydrologic characteristics of benchmark soils of Hawaii’s forest watersheds-

Science.gov (United States)

L. R. Ahuja; S. A. El-Swaify

1975-01-01

The project was initiated in May, 1972. the initial effort involved mapping of forest soils on the islands of Oahu and Kawaii, and collection of relevant literature for preparing the study plan. The detailed study plan (el-Swaify, 1972) was prepared after cooperative discussions with staff of the Institute of Pacific Islands Forestry, Honolulu, Hawaii, and set forth...

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...

Are REDD+ community forest projects following the principles for collective action, as proposed by Ostrom?

Directory of Open Access Journals (Sweden)

Abdul-Razak Saeed

2017-03-01

Full Text Available Forested countries in the global south that have agreed to engage in REDD+, a policy mechanism for addressing climate change, are receiving support to improve laws, policies, systems and structures. As a mechanism initiated at the global level and seeking to use forests to address a global commons crisis (atmospheric carbon concentration, understanding how REDD+ translates into implementation at the local level is essential. Therefore, using a systematic review approach, we examined 15 studies of REDD+ in the context of public and/or community managed forests, drawn from a comprehensive application of inclusion criteria to identify relevant published peer-reviewed empirical research. The common property resources literature was used to highlight the role of local institutions in REDD+ and to distil how REDD+ community forest projects conform to Ostrom’s collective action principles. The review revealed limited sharing of information and decision-making authority with communities; a general absence of FPIC; and a lack of defined benefit sharing and conflict resolution arrangements in many of the REDD+ projects.

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

Science.gov (United States)

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

2016-12-01

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

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

Directory of Open Access Journals (Sweden)

H. Gu

2016-11-01

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

The Pilot Lunar Geologic Mapping Project: Summary Results and Recommendations from the Copernicus Quadrangle

Science.gov (United States)

Skinner, J. A., Jr.; Gaddis, L. R.; Hagerty, J. J.

2010-01-01

The first systematic lunar geologic maps were completed at 1:1M scale for the lunar near side during the 1960s using telescopic and Lunar Orbiter (LO) photographs [1-3]. The program under which these maps were completed established precedents for map base, scale, projection, and boundaries in order to avoid widely discrepant products. A variety of geologic maps were subsequently produced for various purposes, including 1:5M scale global maps [4-9] and large scale maps of high scientific interest (including the Apollo landing sites) [10]. Since that time, lunar science has benefitted from an abundance of surface information, including high resolution images and diverse compositional data sets, which have yielded a host of topical planetary investigations. The existing suite of lunar geologic maps and topical studies provide exceptional context in which to unravel the geologic history of the Moon. However, there has been no systematic approach to lunar geologic mapping since the flight of post-Apollo scientific orbiters. Geologic maps provide a spatial and temporal framework wherein observations can be reliably benchmarked and compared. As such, a lack of a systematic mapping program means that modern (post- Apollo) data sets, their scientific ramifications, and the lunar scientists who investigate these data, are all marginalized in regard to geologic mapping. Marginalization weakens the overall understanding of the geologic evolution of the Moon and unnecessarily partitions lunar research. To bridge these deficiencies, we began a pilot geologic mapping project in 2005 as a means to assess the interest, relevance, and technical methods required for a renewed lunar geologic mapping program [11]. Herein, we provide a summary of the pilot geologic mapping project, which focused on the geologic materials and stratigraphic relationships within the Copernicus quadrangle (0-30degN, 0-45degW).

St. Louis Area Earthquake Hazards Mapping Project - A Progress Report-November 2008

Science.gov (United States)

Karadeniz, D.; Rogers, J.D.; Williams, R.A.; Cramer, C.H.; Bauer, R.A.; Hoffman, D.; Chung, J.; Hempen, G.L.; Steckel, P.H.; Boyd, O.L.; Watkins, C.M.; McCallister, N.S.; Schweig, E.

2009-01-01

St. Louis has experienced minor earthquake damage at least 12 times in the past 200 years. Because of this history and its proximity to known active earthquake zones, the St. Louis Area Earthquake Hazards Mapping Project (SLAEHMP) is producing digital maps that show variability of earthquake hazards, including liquefaction and ground shaking, in the St. Louis area. The maps will be available free via the internet. Although not site specific enough to indicate the hazard at a house-by-house resolution, they can be customized by the user to show specific areas of interest, such as neighborhoods or transportation routes. Earthquakes currently cannot be predicted, but scientists can estimate how strongly the ground is likely to shake as the result of an earthquake. Earthquake hazard maps provide one way of conveying such estimates. The U.S. Geological Survey (USGS), which produces earthquake hazard maps for the Nation, is working with local partners to develop detailed maps for urban areas vulnerable to strong ground shaking. These partners, which along with the USGS comprise the SLAEHMP, include the Missouri University of Science and Technology-Rolla (Missouri S&T), Missouri Department of Natural Resources (MDNR), Illinois State Geological Survey (ISGS), Saint Louis University, Missouri State Emergency Management Agency, and URS Corporation. Preliminary hazard maps covering a test portion of the 29-quadrangle St. Louis study area have been produced and are currently being evaluated by the SLAEHMP. A USGS Fact Sheet summarizing this project was produced and almost 1000 copies have been distributed at several public outreach meetings and field trips that have featured the SLAEHMP (Williams and others, 2007). In addition, a USGS website focusing on the SLAEHMP, which provides links to project results and relevant earthquake hazard information, can be found at: http://earthquake.usgs.gov/regional/ceus/urban_map/st_louis/index.php. This progress report summarizes the

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

Science.gov (United States)

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

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

Forest report 2013; Waldzustandsbericht 2013

Energy Technology Data Exchange (ETDEWEB)

NONE

2013-07-01

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

National forest cover monitoring in mainland South and Southeast Asia: method development and capacity building

Science.gov (United States)

Tyukavina, A.; Potapov, P.; Hansen, M.; Talero, Y.; Turubanova, S.; Pickering, J.; Pickens, A. H.; Quyen, N. H.; Spirovska Kono, M.

2017-12-01

Timely forest monitoring data produced following good practice guidance are required for national reporting on greenhouse gas emissions, national forest resource assessments, and monitoring for REDD+ projects. Remote sensing provides a cost-efficient supplement to national forest inventories, and is often the single viable source of data on forest extent for countries still in the process of establishing field-based inventories. Operational forest monitoring using remotely sensed data requires technical capacity to store, process, and analyze high volumes of satellite imagery. The University of Maryland Global Land Analysis and Discovery (UMD GLAD) lab possesses such technical capacity and is seeking to transfer it to national agencies responsible for forest reporting, national academic institutions, and NGOs. Our projects in South and Southeast Asia include regional forest monitoring in the lower Mekong region in support of the Regional Land Cover Monitoring System (funded by the NASA SERVIR program) and building capacity for forest monitoring in Nepal, Bangladesh, Vietnam, Cambodia, Laos, and Thailand (funded by the SilvaCarbon program). Our forest monitoring approach is a regional scale adaptation of methods developed for the global analysis (Hansen et al. 2013). The methodology to track large-scale clearing of natural forests (e.g. in Brazil and Indonesia) is well established; however, the methods for small-scale disturbance mapping and tree cover rotation assessment are still in development. In Bangladesh our mapping of tree cover change between 2000-2014 revealed that 54% of the tree canopy cover was outside forests, and the majority of canopy changes were smaller than 0.1 ha. Landsat's 30-m resolution was therefore insufficient to monitor changes in tree cover. By using a probability sample of high resolution (circa 1 m) imagery we were able to quantify change in tree canopy cover outside forests (including village woodlots, tree plantations and agroforestry

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.

High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA.

Science.gov (United States)

Kebschull, Justus M; Garcia da Silva, Pedro; Reid, Ashlan P; Peikon, Ian D; Albeanu, Dinu F; Zador, Anthony M

2016-09-07

Neurons transmit information to distant brain regions via long-range axonal projections. In the mouse, area-to-area connections have only been systematically mapped using bulk labeling techniques, which obscure the diverse projections of intermingled single neurons. Here we describe MAPseq (Multiplexed Analysis of Projections by Sequencing), a technique that can map the projections of thousands or even millions of single neurons by labeling large sets of neurons with random RNA sequences ("barcodes"). Axons are filled with barcode mRNA, each putative projection area is dissected, and the barcode mRNA is extracted and sequenced. Applying MAPseq to the locus coeruleus (LC), we find that individual LC neurons have preferred cortical targets. By recasting neuroanatomy, which is traditionally viewed as a problem of microscopy, as a problem of sequencing, MAPseq harnesses advances in sequencing technology to permit high-throughput interrogation of brain circuits. Copyright © 2016 Elsevier Inc. All rights reserved.

Zombie projects, negative networks, and multigenerational science: The temporality of the International Map of the World.

Science.gov (United States)

Rankin, William

2017-06-01

The International Map of the World was a hugely ambitious scheme to create standardized maps of the entire world. It was first proposed in 1891 and remained a going concern until 1986. Over the course of the project's official life, nearly every country in the world took part, and map sheets were published showing all but a few areas of the planet. But the project ended quite unceremoniously, repudiated by cartographers and mapping institutions alike, and it is now remembered as a 'sad story' of network failure. How can we evaluate this kind of sprawling, multigenerational project? In order to move beyond practitioners' (and historians') habit of summarizing the entire endeavor using the blunt categories of success and failure, I propose a more temporally aware reading, one that both disaggregates the (persistent) project from the (always changing) network and sees project and network as invertible, with the possibility of zombie projects and negative networks that can remain robust even when disconnected from their original goals. I therefore see the abandonment of the International Map of the World as resulting from vigorous collaboration and new norms in cartography, not from lack of cooperation or other resources. New categories are required for analyzing science over the long durée.

Managing dependencies in forest offset projects: toward a more complete evaluation of reversal risk

Science.gov (United States)

David M Cooley; Chrsitopher S Galik; Thomas P Holmes; Carolyn Kousky; Roger M Cooke

2011-01-01

Although forest carbon offsets can play an important role in the implementation of comprehensive climate policy, they also face an inherent risk of reversal. If such risks are positively correlated across projects, it can affect the integrity of larger project portfolios and potentially the entire offsets program. Here, we discuss three types of risks that could affect...

Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): Coastlines

Data.gov (United States)

National Aeronautics and Space Administration — The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid...

76 FR 46721 - Salmon-Challis National Forest, ID; Upper North Fork HFRA Ecosystem Restoration Project...

Science.gov (United States)

2011-08-03

...-Challis National Forest, ID; Upper North Fork HFRA Ecosystem Restoration Project Environmental Impact... improve the health of the ecosystem and reach the desired future condition. DATES: Comments concerning the... Ecosystem Restoration Project EIS, P.O. Box 180, 11 Casey Rd., North Fork, ID 83466. Comments may also be...

Effects of Simulated Forest Cover Change on Projected Climate Change – a Case Study of Hungary

Directory of Open Access Journals (Sweden)

GÁLOS, Borbála

2011-01-01

Full Text Available Climatic effects of forest cover change have been investigated for Hungary applying theregional climate model REMO. For the end of the 21st century (2071–2100 case studies have beenanalyzed assuming maximal afforestation (forests covering all vegetated area and completedeforestation (forests replaced by grasslands of the country. For 2021–2025, the climatic influence ofthe potential afforestation based on a detailed national survey has been assessed. The simulationresults indicate that maximal afforestation may reduce the projected climate change through coolerand moister conditions for the entire summer period. The magnitude of the simulated climate changemitigating effect of the forest cover increase differs among regions. The smallest climatic benefit wascalculated in the southwestern region, in the area with the potentially strongest climate change. Thestrongest effects of maximal afforestation are expected in the northeastern part of the country. Here,half of the projected precipitation decrease could be relieved and the probability of summer droughtscould be reduced. The potential afforestation has a very slight feedback on the regional climatecompared to the maximal afforestation scenario.

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.

Assessing forest influences on torrential hazards and risks: IRSTEA mission within the European H2020 project NAIAD

Science.gov (United States)

Piton, Guillaume; Tacnet, Jean Marc; Berger, Frédéric; Curt, Corinne; Curt, Thomas; Arnaud, Patrick

2017-04-01

NAIAD (NAture Insurance value: Assessment and Demonstration) is a H2020 European project gathering 23 partners interested in ecosystems services related to water. The project more specifically links nature services to the assurance world and aims to operationalise "Natural Assurance Schemes", defined as a range of schemes to internalise the value of ecosystems services, e.g., the buffering role of river systems against water risks, in insurance policies. It is based on an assessment methodology that includes the physical, socio-cultural and valuation aspects of ecosystems services in relation to water, adapted to the institutional frame to align economic incentives and financial flows. Within the NAIAD projet, IRSTEA will more specifically try to highlight the role of mountain forests in torrential flood hazards and risks. The forest eventually acts on hydrology by buffering part of the rainwater. Vegetation has also a key role in soil conservation by curtailing primary sediment production in the hillslopes. Conversely, woody debris dramatically aggravate hazards by clogging bridges and key protections structures as open check dams. Finally this dual role may change in time due to the forest vulnerability to climatic, biologic or physical changes, e.g. after a wildfire. The first project step will be an extensive literature review on all these effects. Secondly indicators describing the torrential systems will be proposed and link to variably pronounced influence of forest. In a third time, case studies will be undertaken. The dramatic flood that occur in the region of Nice in summer 2015 (20 fatalities) will probably be used as a benchmark test. Several scenarios of alternative forest and river managements under varying climate forcing will be tested later. Complete torrential risk assessment studies will be performed on several sites within this project, with and without the forest influences in order to highlight its role. Numerous check dams have been built in

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

Science.gov (United States)

Michael Hoppus; Stan Arner; Andrew Lister

2001-01-01

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

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.

Quantifying the Carbon Balance of Forest Restoration and Wildfire under Projected Climate in the Fire-Prone Southwestern US.

Science.gov (United States)

Hurteau, Matthew D

2017-01-01

Climate projections for the southwestern US suggest a warmer, drier future and have the potential to impact forest carbon (C) sequestration and post-fire C recovery. Restoring forest structure and surface fire regimes initially decreases total ecosystem carbon (TEC), but can stabilize the remaining C by moderating wildfire behavior. Previous research has demonstrated that fire maintained forests can store more C over time than fire suppressed forests in the presence of wildfire. However, because the climate future is uncertain, I sought to determine the efficacy of forest management to moderate fire behavior and its effect on forest C dynamics under current and projected climate. I used the LANDIS-II model to simulate carbon dynamics under early (2010-2019), mid (2050-2059), and late (2090-2099) century climate projections for a ponderosa pine (Pinus ponderosa) dominated landscape in northern Arizona. I ran 100-year simulations with two different treatments (control, thin and burn) and a 1 in 50 chance of wildfire occurring. I found that control TEC had a consistent decline throughout the simulation period, regardless of climate. Thin and burn TEC increased following treatment implementation and showed more differentiation than the control in response to climate, with late-century climate having the lowest TEC. Treatment efficacy, as measured by mean fire severity, was not impacted by climate. Fire effects were evident in the cumulative net ecosystem exchange (NEE) for the different treatments. Over the simulation period, 32.8-48.9% of the control landscape was either C neutral or a C source to the atmosphere and greater than 90% of the thin and burn landscape was a moderate C sink. These results suggest that in southwestern ponderosa pine, restoring forest structure and surface fire regimes provides a reasonable hedge against the uncertainty of future climate change for maintaining the forest C sink.

Quantifying the Carbon Balance of Forest Restoration and Wildfire under Projected Climate in the Fire-Prone Southwestern US.

Directory of Open Access Journals (Sweden)

Matthew D Hurteau

Full Text Available Climate projections for the southwestern US suggest a warmer, drier future and have the potential to impact forest carbon (C sequestration and post-fire C recovery. Restoring forest structure and surface fire regimes initially decreases total ecosystem carbon (TEC, but can stabilize the remaining C by moderating wildfire behavior. Previous research has demonstrated that fire maintained forests can store more C over time than fire suppressed forests in the presence of wildfire. However, because the climate future is uncertain, I sought to determine the efficacy of forest management to moderate fire behavior and its effect on forest C dynamics under current and projected climate. I used the LANDIS-II model to simulate carbon dynamics under early (2010-2019, mid (2050-2059, and late (2090-2099 century climate projections for a ponderosa pine (Pinus ponderosa dominated landscape in northern Arizona. I ran 100-year simulations with two different treatments (control, thin and burn and a 1 in 50 chance of wildfire occurring. I found that control TEC had a consistent decline throughout the simulation period, regardless of climate. Thin and burn TEC increased following treatment implementation and showed more differentiation than the control in response to climate, with late-century climate having the lowest TEC. Treatment efficacy, as measured by mean fire severity, was not impacted by climate. Fire effects were evident in the cumulative net ecosystem exchange (NEE for the different treatments. Over the simulation period, 32.8-48.9% of the control landscape was either C neutral or a C source to the atmosphere and greater than 90% of the thin and burn landscape was a moderate C sink. These results suggest that in southwestern ponderosa pine, restoring forest structure and surface fire regimes provides a reasonable hedge against the uncertainty of future climate change for maintaining the forest C sink.

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

Resource communication: ApkFor©, an Android Open-Source Project for research and technology transfer in forest management

Directory of Open Access Journals (Sweden)

Fernando Pérez-Rodríguez

2018-01-01

Full Text Available Aim of the study: To introduce and describe ApkFor©, an Android Open-Source Project to generate basic mobile applications to transfer forest growth and yield models for even-aged stands. Material and methods: ApkFor© was developed in Android Studio using Java and XML languages integrating  transition functions for dominant height and basal area, equations of tree and stand volume and structural models. The project was applied and validated for Pinus pinaster Ait. stands in Northeastern Portugal. Main results: ApkFor© is an Open-Source project freely available from the Source Force repository: https://sourceforge.net/projects/apkfor/, licensed under the GNU General Public License version 3.0 (GPLv3. Research highlights: This project has been designed and created to provide the code and promote its re-use and modification to develop simple growth and yield mobile applications in Android, and with it to transfer research results of forest modelling to forest managers. Moreover, an example of application of the compiled code is provided using the models of Pinus pinaster Ait. previously validated for the Northeastern Region of Portugal.

Linking chemical elements in forest floor humus (Oh-horizon) in the Czech Republic to contamination sources

International Nuclear Information System (INIS)

Sucharova, Julie; Suchara, Ivan; Hola, Marie; Reimann, Clemens; Boyd, Rognvald; Filzmoser, Peter; Englmaier, Peter

2011-01-01

While terrestrial moss and other plants are frequently used for environmental mapping and monitoring projects, data on the regional geochemistry of humus are scarce. Humus, however, has a much larger life span than any plant material. It can be seen as the 'environmental memory' of an area for at least the last 60-100 years. Here concentrations of 39 elements determined by ICP-MS and ICP AES, pH and ash content are presented for 259 samples of forest floor humus collected at an average sample density of 1 site/300 km 2 in the Czech Republic. The scale of anomalies linked to known contamination sources (e.g., lignite mining and burning, metallurgical industry, coal fired power plants, metal smelters) is documented and discussed versus natural processes influencing humus quality. Most maps indicate a local impact from individual contamination sources: often more detailed sampling than used here would be needed to differentiate between likely sources. - Highlights: → Concentrations of 39 elements in forest floor humus are provided. → The capabilities of humus sampling for bio-monitoring purposes are demonstrated. → Geochemical anomalies are linked to known contamination sources. → The study shows the importance of scale for geochemical mapping projects. → Humus provides a picture of the long term contamination history of a country. - Forest floor humus, the atmosphere-biosphere-pedosphere interface, archives an environmental contamination signal over long time periods.

Mapping Best and Emerging Practices of Project Management

DEFF Research Database (Denmark)

Thuesen, Christian; Aaris Boas, Charlotte; Thorslund, Michael V.

2013-01-01

This paper presents results of a study of the connection between Best and Emerging practices of project management. Drawing upon network mapping as an analytical strategy, cases of Best and Emerging practices is analysed and juxtaposed. The case of Best practice is represented by the newly...... published ISO 21500 standard and the case for the Emerging practices by a deconstruction of the practices of a group of experienced project managers. The network analysis reveals a substantial difference between the Best and Emerging practices. Only two central concepts where shared namely Communication...... and Planning. Of these two concepts Communication where found to be the most central to both the Emerging and Best practices. The analysis further reveals a soft side of project management that is central in the Emerging practice but absent from the Best practices. Although this soft side might be interpreted...

Remotely sensed forest cover loss shows high spatial and temporal variation across Sumatera and Kalimantan, Indonesia 2000-2008

International Nuclear Information System (INIS)

Broich, Mark; Hansen, Matthew; Potapov, Peter; Margono, Belinda Arunarwati; Adusei, Bernard; Stolle, Fred

2011-01-01

The Indonesian islands of Sumatera and Kalimantan (the Indonesian part of the island of Borneo) are a center of significant and rapid forest cover loss in the humid tropics with implications for carbon dynamics, biodiversity conservation, and local livelihoods. The aim of our research was to analyze and interpret annual trends of forest cover loss for different sub-regions of the study area. We mapped forest cover loss for 2000-2008 using multi-resolution remote sensing data from the Landsat enhanced thematic mapper plus (ETM +) and moderate resolution imaging spectroradiometer (MODIS) sensors and analyzed annual trends per island, province, and official land allocation zone. The total forest cover loss for Sumatera and Kalimantan 2000-2008 was 5.39 Mha, which represents 5.3% of the land area and 9.2% of the year 2000 forest cover of these two islands. At least 6.5% of all mapped forest cover loss occurred in land allocation zones prohibiting clearing. An additional 13.6% of forest cover loss occurred where clearing is legally restricted. The overall trend of forest cover loss increased until 2006 and decreased thereafter. The trends for Sumatera and Kalimantan were distinctly different, driven primarily by the trends of Riau and Central Kalimantan provinces, respectively. This analysis shows that annual mapping of forest cover change yields a clearer picture than a one-time overall national estimate. Monitoring forest dynamics is important for national policy makers, especially given the commitment of Indonesia to reducing greenhouse gas emissions as part of the reducing emissions from deforestation and forest degradation in developing countries initiative (REDD +). The improved spatio-temporal detail of forest change monitoring products will make it possible to target policies and projects in meeting this commitment. Accurate, annual forest cover loss maps will be integral to many REDD + objectives, including policy formulation, definition of baselines, detection

MRO CRISM MAP-PROJECTED TARGETED REDUCED DATA RECORD V1.0

Data.gov (United States)

National Aeronautics and Space Administration — This volume contains the CRISM Map-projected Targeted Reduced Data Record (MTRDR) archive, a collection of multiband image cubes derived from targeted (gimbaled)...

75 FR 16422 - Plumas National Forest, California, Keddie Ridge Hazardous Fuels Reduction Project

Science.gov (United States)

2010-04-01

... Hazardous Fuels Reduction Project AGENCY: Forest Service, USDA. ACTION: Notice of intent to prepare an... District will prepare and environmental impact statement (EIS) on the Keddie Ridge Hazardous Fuels...: fuels treatments, group selections, road improvements, and herbicide and mechanical applications in the...

Projecting climate change in the United States: A technical document supporting the Forest Service RPA 2010 Assessment

Science.gov (United States)

Linda A. Joyce; David T. Price; David P. Coulson; Daniel W. McKenney; R. Martin Siltanen; Pia Papadopol; Kevin. Lawrence

2014-01-01

A set of climate change projections for the United States was developed for use in the 2010 USDA Forest Service RPA Assessment. These climate projections, along with projections for population dynamics, economic growth, and land use change in the United States, comprise the RPA scenarios and are used in the RPA Assessment to project future renewable resource conditions...

78 FR 23903 - Forest Service

Science.gov (United States)

2013-04-23

... DEPARTMENT OF AGRICULTURE Forest Service Dixie Resource Advisory Committee AGENCY: Forest Service... and to provide advice and recommendations to the Forest Service concerning projects and funding... review proposals for forest projects and recommending funding. DATES: The meeting will be held Thursday...

Project CAPTURE: using forest inventory and analysis data to prioritize tree species for conservation, management, and restoration

Science.gov (United States)

Kevin M. Potter; Barbara S. Crane; William W. Hargrove

2015-01-01

A variety of threats, most importantly climate change and insect and disease infestation, will increase the likelihood that forest tree species could experience population-level extirpation or species-level extinction during the next century. Project CAPTURE (Conservation Assessment and Prioritization of Forest Trees Under Risk of Extirpation) is a cooperative effort...

Forest inventory in Myanmar

Energy Technology Data Exchange (ETDEWEB)

Bo, Sit [Forest Resource Div., Forest Department (Myanmar)

1993-10-01

Forest inventory in Myanmar started in 1850s. Up till 1975, Myanmar Forest Department conducted forest inventories covering approximately one forest division every year. The National Forest Survey and Inventory Project funded by UNDP and assisted by FAO commenced in 1981 and the National Forest Management and Inventory project followed in 1986. Up till end March 1993, pre-investment inventory has covered 26.7 million acres, reconnaissance inventory 5.4 million acres and management inventory has carried out in 12 townships

Forest inventory in Myanmar

International Nuclear Information System (INIS)

Sit Bo

1993-01-01

Forest inventory in Myanmar started in 1850s. Up till 1975, Myanmar Forest Department conducted forest inventories covering approximately one forest division every year. The National Forest Survey and Inventory Project funded by UNDP and assisted by FAO commenced in 1981 and the National Forest Management and Inventory project followed in 1986. Up till end March 1993, pre-investment inventory has covered 26.7 million acres, reconnaissance inventory 5.4 million acres and management inventory has carried out in 12 townships

A framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps

Science.gov (United States)

Xu, Jin; Li, Zheng; Li, Shuliang; Zhang, Yanyan

2015-07-01

There is still a lack of effective paradigms and tools for analysing and discovering the contents and relationships of project knowledge contexts in the field of project management. In this paper, a new framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps under big data environments is proposed and developed. The conceptual paradigm, theoretical underpinning, extended topic model, and illustration examples of the ontology model for project knowledge maps are presented, with further research work envisaged.

Modeling carbon sequestration in afforestation, agroforestry and forest management projects: the CO2FIX V.2 approach

NARCIS (Netherlands)

Masera, O.R.; Garza-Caligaris, J.F.; Kanninen, M.; Karjalainen, T.; Liski, J.; Nabuurs, G.J.; Pussinen, A.; Jong de, B.H.J.; Mohren, G.M.J.

2003-01-01

The paper describes the Version 2 of the CO2FIX (CO2FIX V.2) model, a user-friendly tool for dynamically estimating the carbon sequestration potential of forest management, agroforesty and afforestation projects. CO2FIX V.2 is a multi-cohort ecosystem-level model based on carbon accounting of forest

Interdisciplinary collaboration within project-level NEPA teams in the US Forest Service

Science.gov (United States)

James W. Freeman; Marc J. Stern; Michael Mortimer; Dale J. Blahna; Lee K. Cerveny

2011-01-01

Interdisciplinary teamwork has become a foundation of natural resources planning and management in the US. Yet, we know little about the degree of interdisciplinary collaboration of natural resource planning teams. We conducted 10 case studies of Forest Service NEPA (National Environmental Policy Act) teams working on projects related to the 2005 Travel Management Rule...

Mapping research activity on mental health disorders in Europe: study protocol for the Mapping_NCD project.

Science.gov (United States)

Berg Brigham, Karen; Darlington, Meryl; Wright, John S F; Lewison, Grant; Kanavos, Panos; Durand-Zaleski, Isabelle

2016-05-26

Mental health disorders (MHDs) constitute a large and growing disease burden in Europe, although they typically receive less attention and research funding than other non-communicable diseases (NCDs). This study protocol describes a methodology for the mapping of MHD research in Europe as part of Mapping_NCD, a 2-year project funded by the European Commission which seeks to map European research funding and impact for five NCDs in order to identify potential gaps, overlaps, synergies and opportunities, and to develop evidence-based policies for future research. The project aims to develop a multi-focal view of the MHD research landscape across the 28 European Union Member States, plus Iceland, Norway and Switzerland, through a survey of European funding entities, analysis of research initiatives undertaken in the public, voluntary/not-for-profit and commercial sectors, and expert interviews to contextualize the gathered data. The impact of MHD research will be explored using bibliometric analyses of scientific publications, clinical guidelines and newspaper stories reporting on research initiatives. Finally, these research inputs and outputs will be considered in light of various metrics that have been proposed to inform priorities for the allocation of research funds, including burden of disease, treatment gaps and cost of illness. Given the growing burden of MHDs, a clear and broad view of the current state of MHD research is needed to ensure that limited resources are directed to evidence-based priority areas. MHDs pose a particular challenge in mapping the research landscape due to their complex nature, high co-morbidity and varying diagnostic criteria. Undertaking such an effort across 31 countries is further challenged by differences in data collection, healthcare systems, reimbursement rates and clinical practices, as well as cultural and socioeconomic diversity. Using multiple methods to explore the spectrum of MHD research funding activity across Europe

The Missouri Ozark Forest Ecosystem Project: the effects of forest management on the forest ecosystem

Science.gov (United States)