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The capacity of ecosystems to provide services such as carbon storage, clean water, and forest products is determined not only by variations in ecosystem properties across landscapes, but also by ecosystem dynamics over time. ForWarn is a system developed by the U.S. Forest Service to monitor vegetation change using satellite imagery for the continental United States. It provides near real-time change maps that are updated every eight days, and summaries of these data also provide long-term change maps from 2000 to the present. Based on the detection of change in vegetation productivity, the ForWarn system monitors the effects of disturbances such as wildfires, insects, diseases, drought, and other effects of weather,...
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This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus madritensis L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., and medusahead (Taeniatherum caput-medusae. The dataset was generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; Harmonized...
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These datasets provide early estimates of 2022 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a bi-weekly basis from May to early July. The EAG estimates are developed within one week of the latest satellite observation used for that version. Each bi-weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized Landsat...
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This study uses growth in vegetation during the monsoon season measured from LANDSAT imagery as a proxy for measured rainfall. NDVI values from 26 years of pre- and post-monsoon season Landsat imagery were derived across Yuma Proving Ground (YPG) in southwestern Arizona, USA. The LANDSAT imagery (1986-2011) was downloaded from USGS’s GlobeVis website (http://glovis.usgs.gov/). Change in NDVI was calculated within a set of 2,843 Riparian Area Polygons (RAPs) up to 1 km in length defined in ESRI ArcMap 10.2.
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This dataset provides an estimate of 2015 cheatgrass percent cover in the northern Great Basin at 250 meter spatial resolution. The dataset was generated by integrating eMODIS NDVI satellite data with independent variables that influence cheatgrass germination and growth into a regression-tree model. Individual pixel values range from 0 to 100 with an overall mean value of 9.85 and a standard deviation of 12.78. A mask covers areas not classified as shrub/scrub or grass/herbaceous by the 2001 National Land Cover Database. The mask also covers areas higher than 2000 meters in elevation because cheatgrass is unlikely to exist at more than 2% cover above this threshold. Cheatgrass is an invasive grass that has invaded...
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These datasets provide early estimates of 2023 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from May to early July. The EAG estimates are developed typically within 7-13 days of the latest satellite observation used for that version. Each weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized...
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These datasets provide early estimates of 2021 fractional cover for exotic annual grass (EAG) species and a native perennial grass predicted on July 1 using satellite observation data available no later than June 28th. Four fractional cover maps comprise this release, along with the corresponding confidence maps, for: 1) a group of 17 species of EAGs (i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus hordeaceus spp. hordeaceus, Bromus japonicus, Bromus madritensis L., Bromus madritensis L. ssp. rubens (L.) Duvin, Bromus L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus tectorum L., Bromus texensis (Shear) Hitchc.,...
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These datasets provide early estimates of 2022 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a bi-weekly basis from May to early July. The EAG estimates are developed within one week of the latest satellite observation used for that version. Each bi-weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized Landsat...
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The Middle East and North Africa (MENA) region is the most water-scarce region with only two percent of the global average annual rainfall, hence underground aquifers are the major source of water. The need to improve water productivity and increase aquifer storage and recovery (ASR) is driving the efforts for this acceleration of aquifer storage and recovery project. The objective was to model runoff in the study area using multi-source satellite data and identify regions of runoff retention and recharge. Daily runoff is simulated using a saturation excess principle with the VegET model (Senay 2008). It is a spatially explicit (500m grid cell), one-dimensional root-zone water balance model that is driven by precipitation,...
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The dataset provides a near real time estimation of 2020 herbaceous mostly annual fractional cover predicted on July 1st with an emphasis on annual exotic grasses Historically, similar maps were produced at a spatial resolution of 250m (Boyte et al. 2019 https://doi.org/10.5066/P96PVZIF., Boyte et al. 2018 https://doi.org/10.5066/P9RIV03D.), but starting this year we are mapping at a 30m resolution (Pastick et al. 2020 doi:10.3390/rs12040725). This dataset was generated using in situ observations from Bureau of Land Management’s (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; weekly composites of harmonized Landsat and Sentinel-2 (HLS) data (https://hls.gsfc.nasa.gov/); relevant environmental, vegetation,...
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These datasets provide early estimates of 2023 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from May to early July. The EAG estimates are developed typically within 7-13 days of the latest satellite observation used for that version. Each weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized...
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These datasets provide early estimates of 2023 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from May to early July. The EAG estimates are developed typically within 7-13 days of the latest satellite observation used for that version. Each weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized...
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The dataset provides a spatially explicit estimate of 2019 herbaceous annual percent cover predicted on May 1st with an emphasis on annual grasses. The estimate is based on the mean output of two regression-tree models. For one model, we include, as an independent variable amongst other independent variables, a dataset that is the mean of 17-years of annual herbaceous percent cover (https://doi.org/10.5066/F71J98QK). This model's test mean error rate (n = 1670), based on nine different randomizations, equals 4.9% with a standard deviation of +/- 0.15. A second model was developed that did not include the mean of 17-years of annual herbaceous percent cover, and this model's test mean error rate (n = 1670), based...
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This dataset release provides historical (2016 - 2022) estimates of fractional cover for exotic annual grass (EAG) species and a native perennial bunch grass in the arid and semi-arid rangelands of the western United States. The dataset includes four fractional cover maps per year, accompanied by corresponding confidence maps, for a group of 16 species of EAGs, cheatgrass (Bromus tectorum); medusahead (Taeniatherum caput-medusae); and Sandberg bluegrass (Poa secunda). The data were generated using a combination of field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) plots; remotely sensed data from the Harmonized Landsat and Sentinel-2 (HLS) product (specifically Normalized...
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These datasets provide early estimates of 2023 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from May to early July. The EAG estimates are developed typically within 7-13 days of the latest satellite observation used for that version. Each weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized...
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This metadata record documents data files, an analysis script, and results from a land-surface greenness analysis of the Tuckahoe Creek watershed, covering parts of Caroline, Queen Anne's and Talbot Counties in Maryland from 1984 to 2017. Included in this record are: 1) 34 raster datasets containing maximum wintertime greenness values on an annual basis from 1984 to 2017, 2) a script used in Google Earth Engine to create the raster datasets, 3) tabular output from vegetation biomass analysis for 1984 to 2017 using a composite cropland layer, 4) a raster of the composite cropland layer, 5) tabular output from vegetation biomass analysis by preceding summer crop type for 2008 to 2017 using year-specific annual cropland...
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These datasets provide early estimates of 2022 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a bi-weekly basis from May to early July. The EAG estimates are developed within one week of the latest satellite observation used for that version. Each bi-weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized Landsat...
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These datasets provide early estimates of 2023 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from May to early July. The EAG estimates are developed typically within 7-13 days of the latest satellite observation used for that version. Each weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized...
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These datasets provide early estimates of 2023 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a weekly basis from May to early July. The EAG estimates are developed typically within 7-13 days of the latest satellite observation used for that version. Each weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) data plots; Harmonized...


map background search result map search result map Average Normalized Difference Vegetation Index (NDVI) for the western United States (1989-2002) Near-real-time cheatgrass percent cover in the northern Great Basin, USA--2015 ForWarn Mean Summer National Difference Vegetation Index 2009-2013 Mean of the Top Ten Percent of NDVI Values in the Yuma Proving Ground during Monsoon Season, 1986-2011 Early Estimates of Herbaceous Annual Cover in the Sagebrush Ecosystem (May 1, 2019) Landsat-derived wintertime greenness datasets and results from cover crop performance analysis within the Tuckahoe Creek watershed, Maryland, from 1984 to 2017 Modeling accumulated surface runoff and water availability for aquifer storage and recovery in the MENA region from 1984-2015 Near real time estimation of annual exotic herbaceous fractional cover in the sagebrush ecosystem 30m, USA, July 2020 Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1 Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, July 2021, (ver 2.0, January 2022) Fractional Estimates of Multiple Exotic Annual Grass (EAG) Species and Sandberg bluegrass in the Sagebrush Biome, USA, 2016 - 2022 (ver. 3.0, July 2023) 2. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 3.0, May 18th, 2022) 3. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 4.0, June 3rd, 2022) 5. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 6.0, July 1st, 2022) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 1.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 2.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 4.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 5.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 6.0, June 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 7.0, June 2023) Mean of the Top Ten Percent of NDVI Values in the Yuma Proving Ground during Monsoon Season, 1986-2011 Landsat-derived wintertime greenness datasets and results from cover crop performance analysis within the Tuckahoe Creek watershed, Maryland, from 1984 to 2017 Modeling accumulated surface runoff and water availability for aquifer storage and recovery in the MENA region from 1984-2015 Near-real-time cheatgrass percent cover in the northern Great Basin, USA--2015 Early Estimates of Herbaceous Annual Cover in the Sagebrush Ecosystem (May 1, 2019) Near real time estimation of annual exotic herbaceous fractional cover in the sagebrush ecosystem 30m, USA, July 2020 ForWarn Mean Summer National Difference Vegetation Index 2009-2013 Average Normalized Difference Vegetation Index (NDVI) for the western United States (1989-2002) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1 Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, July 2021, (ver 2.0, January 2022) Fractional Estimates of Multiple Exotic Annual Grass (EAG) Species and Sandberg bluegrass in the Sagebrush Biome, USA, 2016 - 2022 (ver. 3.0, July 2023) 2. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 3.0, May 18th, 2022) 3. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 4.0, June 3rd, 2022) 5. Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2022 (ver 6.0, July 1st, 2022) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 1.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 2.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 4.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 5.0, May 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 6.0, June 2023) Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2023 (ver. 7.0, June 2023)