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Filters: partyWithName: U.S. Geological Survey (X) > partyWithName: Eric K Waller (X)

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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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To determine if invasive annual grasses increased around energy developments after the construction phase, we calculated an invasives index using Landsat TM and ETM+ imagery for a 34-year time period (1985-2018) and assessed trends for 1,755 wind turbines (from the U.S. Wind Turbine Database) installed between 1988 and 2013 in the southern California desert. The index uses the maximum normalized difference vegetation index (NDVI) for early season greenness (January-June), and mean NDVI (July-October) for the later dry season. We estimated the relative cover of invasive annuals each year at turbine locations and control sites and tested for changes before and after each turbine was installed. These data were used...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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USGS researchers with the Patterns in the Landscape – Analyses of Cause and Effect (PLACE) project are releasing a collection of high-frequency surface water map composites derived from daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Using Google Earth Engine, the team developed customized image processing steps and adapted the Dynamic Surface Water Extent (DSWE) to generate surface water map composites in California for 2003-2019 at a 250-m pixel resolution. Daily maps were merged to create 6, 3, 2, and 1 composite(s) per month corresponding to approximately 5-day, 10-day, 15-day, and monthly products, respectively. The resulting maps are available as downloadable files for each year. Each...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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This data release contains spatial data on the location, number, size and extent of energy-related surface disturbances on the Colorado Plateau of Utah, Colorado, and New Mexico as of 2016. The database includes: 1) polygons of oil and gas pads generated from automated and manual classification of aerial imagery, and 2) polylines of roads derived from the U.S. Census Bureau TIGER/Line Shapefile, supplemented with additional oil and gas access roads digitized from aerial imagery. Pad polygons and road segments are attributed with a "spud year" date based on spud information from the nearest well point. Spudding is the process of beginning to drill a well in the oil and gas industry, and the spud year is a close approximation...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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The Dynamic Surface Water Extent MODIS (DSWEmod) surface water maps for the conterminous United States were used for a study conducted by the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team quantifying seasonal and annual surface water trends within Environmental Protection Agency (EPA) Level I and Level III Ecoregions (Omernik, 1987) across the U.S. from 2003 through 2019. The overarching objectives of this study were to, (i) generate the monthly DSWEmod maps for the conterminous United States, (ii) review the spatial and temporal dynamics of surface water extent across ecoregions, and (iii) compare surface water area trends to streamgage discharge trends to determine...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...
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Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class...


map background search result map search result map Data supporting Landsat time series assessment of invasive annual grasses following energy development DSWEmod surface water map composites generated from daily MODIS images - California Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2003 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2004 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2005 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2006 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2007 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2008 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2009 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2011 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2012 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2013 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2014 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2015 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2016 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2017 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2018 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2019 Surface Water Trends for the Conterminous United States using monthly DSWEmod Surface Water Maps, 2003–2019 Spatial data of oil and gas pads and access roads on the Colorado Plateau, Utah, Colorado, and New Mexico Data supporting Landsat time series assessment of invasive annual grasses following energy development Spatial data of oil and gas pads and access roads on the Colorado Plateau, Utah, Colorado, and New Mexico DSWEmod surface water map composites generated from daily MODIS images - California Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2003 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2004 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2005 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2006 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2007 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2008 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2009 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2011 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2012 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2013 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2014 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2015 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2016 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2017 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2018 Monthly Dynamic Surface Water Extent MODIS (DSWEmod) Images for the Conterminous United States – 2019 Surface Water Trends for the Conterminous United States using monthly DSWEmod Surface Water Maps, 2003–2019