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The unique hydrologic conditions characterizing riparian ecosystems in dryland (arid and semi-arid) areas help maintain high biodiversity and support high levels of primary productivity compared to associated uplands. In western North America, many riparian ecosystems have been damaged by altered flow regimes (e.g., impoundments and diversions) and over utilization of water resources (e.g., groundwater pumping for agriculture and human consumption). This has led some state and national governments to provide occasional environmental flows to address the declining condition of such riparian systems. In a historic agreement between the United States and Mexico, 130 million cubic meters (mcm) of water was released...
This dataset portrays 61 forest group types across the southeastern United States. These data were derived from a product created by the USFS Forest Inventory and Analysis (FIA) program and the Remote Sensing Applications Center (RSAC). Â The original dataset (accessible from the US Forest Service Website) consists of 141 forest types across the contiguous United States. The original dataset was downloaded on 12/13/2013, clipped to the southeastern states, Â and used in a generalization procedure which involved the application of a majority filter (8 neighbors, half replacement threshold) followed by a sieving process which removed pixels in groups of four or less by reassigning them to their nearest neighbor value....
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of Field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha-1 for a range of biomass between 0 and 454 Mg ha-1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate...
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of Field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha-1 for a range of biomass between 0 and 454 Mg ha-1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate...
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of Field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha-1 for a range of biomass between 0 and 454 Mg ha-1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate...
This dataset portrays 141 forest types across Alaska. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, and ecoregions. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center.
Abstract: This dataset portrays 141 forest types across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center. Purpose: The purpose of this dataset is to portray broad distribution patterns of forest cover in the United States and provide input to national scale modeling projects. The data should not be displayed at scales smaller than...
This dataset supports the following publication: "Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States" (DOI:10.1016/j.rse.2020.112013). The data release allows users to replicate, test, or further explore results. The dataset consists of 4 separate items based on the analysis approach used in the original publication 1) the 'Phenocam' dataset uses images from a phenocam in a pinyon juniper ecosystem in Grand Canyon National Park to determine phenological patterns of multiple plant species. The 'Phenocam' dataset consists of scripts and tabular data developed while performing analyses and includes the final NDVI values for all areas...
This dataset provides NDVI time series data in comma-delimited format from the phenocam location using five satellite products: 1) Proba-V L1c product 2) Landsat 7 SR product 3) Sentinel-2 Level-1C product 4) Sentinel 2 Level-2A data product 5) Suomi National Polar-Orbiting Partnership (S-NPP) NASA Visible Infrared Imaging Radiometer Suite (VIIRS) VNP13A1 data product The dataset also includes scripts to download these data from Google Earth Engine. The data are provided in support of the following publication: "Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States". The data and scripts allow users to replicate, test, or further...
Locating meadow study sitesMeadow centers as recorded in the ‘Copy of sitecords_areaelev from Caruthers thesis.xls’ file delivered by Debinski in November 2012 were matched to polygons as recorded in files ‘teton97map_area.shp’ and ‘gallatin97map_area.shp’ both also delivered by Debinski in November 2012.In cases where the meadow center did not fall within a meadow polygon, if there was a meadow polygon of the same meadow TYPE nearby (judgment was used here), the meadow center was matched with the meadow polygon of same meadow TYPE. In total, 29 of 30 Gallatin meadow sites and 21 of 25 Teton meadow sites were positively located.Identifying meadow pixels for analysisThe native MODIS 250-meter grid was reprojected...
Categories: Data;
Types: Citation;
Tags: Greater Yellowstone Ecosystem,
MODIS,
NDVI,
North Central CASC,
Plants,
The TopoWx ('Topography Weather') dataset contains historical 30-arcsec resolution (~800-m) interpolations of daily minimum and maximum topoclimatic air temperature for the conterminous U.S. Using both DEM-based variables and MODIS land skin temperature as predictors of air temperature, interpolation procedures include moving window regression kriging and geographically weighted regression. To avoid artificial climate trends, all input station data are homogenized using the GHCN/USHCN Pairwise Homogenization Algorithm (http://www.ncdc.noaa.gov/oa/climate/research/ushcn/#phas). The interpolation model is open source and information on obtaining model code can be found at http://www.ntsg.umt.edu/project/TopoWx. The...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
NetCDF OPeNDAP Service,
Raster;
Tags: MODIS,
air temperature,
climatologyMeteorologyAtmosphere,
dataset,
gridded meteorological data,
This data set replaces the 2010 edition (Edition 1.0) of the 2005 Land Cover of North America. Following the release of the first 2005 land cover data, several errors were identified in the data, including both errors in labeling and misinterpretation of thematic classes. To correct the labeling errors, each country focused on its national territory and corrected the errors which it considered most critical or misleading. For the continental data sets (including surrounding water fringe) 17440830 pixels (4.33% of the area) changed in the update. The following national counts exclude the water fringe: Canada, 10223412 pixels changed (6.44%); Mexico, 141142 pixels changed (0.45%), and U.S., 6878656 pixels changed...
This dataset portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center.
This dataset portrays 11 forest group types across the southeastern United States. These data were derived from a product created by the USFS Forest Inventory and Analysis (FIA) program and the Remote Sensing Applications Center (RSAC). Â The original dataset (accessible from the US Forest Service Website) consists of 28 forest type groups across the contiguous United States. The original dataset was downloaded on 12/13/2013, clipped to the southeastern states, Â and used in a generalization procedure which involved the application of a majority filter (8 neighbors, half replacement threshold) followed by a sieving process which removed pixels in groups of four or less by reassigning them to their nearest neighbor...
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of Field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha-1 for a range of biomass between 0 and 454 Mg ha-1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate...
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of Field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha-1 for a range of biomass between 0 and 454 Mg ha-1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate...
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of Field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha-1 for a range of biomass between 0 and 454 Mg ha-1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate...
This dataset represents 2000-2005 gross forest cover loss for the biome. A separate regression estimator (i.e. separate regression models and parameter estimates allowed for each stratum) and post-stratification were employed to estimate Landsat-calibrated forest cover loss area. For sample blocks with intensive change a simple linear regression model was applied using the proportion of area within the sample block classified as MODIS-derived forest loss as the auxiliary variable. For low-change blocks post-stratification based on VCF tree canopy cover and road density data was implemented to partition blocks into areas of nearly zero change and areas of some change. The forest cover loss area estimates were then...
This dataset portrays 28 forest type groups across the contiguous United States. These data were derived from MODIS composite images from the 2002 and 2003 growing seasons in combination with nearly 100 other geospatial data layers, including elevation, slope, aspect, ecoregions, and PRISM climate data. The dataset was developed as a collaborative effort between the USFS Forest Inventory and Analysis and Forest Health Monitoring programs and the USFS Remote Sensing Applications Center.
This data set shows areas where the land cover classification changed between 2005and 2010. The 2005-2010 Land Cover Change of North America at 250 meters wasproduced as part of the North American Land Change Monitoring System (NALCMS), atrilateral effort between the Canada Centre for Remote Sensing, the United StatesGeological Survey, and three Mexican organizations including the National Instituteof Statistics and Geography (Instituto Nacional de Estadistica y Geografia),National Commission for the Knowledge and Use of the Biodiversity (ComisiónNacional Para el Conocimiento y Uso de la Biodiversidad), and the National ForestryCommission of Mexico (Comisión Nacional Forestal). The collaboration isfacilitated by...
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