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The importance of monitoring shrublands to detect and understand changes through time is increasingly recognized as critical to management. This dataset focuses on ecological change observation over ten years of field observation at 134 plots within two sites that are located in Southwestern of Wyoming, USA from 2008-2018. At sites 1 and 3, 134 long-term field observation plots were measured annually from 2008 to 2018. General plot locations were selected in 2006 using segments and spectral clusters on QuickBird imagery to identify the best locations for representing the variability of the entire site (one QuickBird image). Ground measurements were conducted using ocular measurements with cover was estimated from...
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This part of the Data Release contains the raster representation of the water-level altitude and water-level change maps developed every 5 years from 1980-2015 for the upper Rio Grande Focus Area Study. The input point data used to generate the water-level altitude maps can be found in the "Groundwater level measurement data used to develop water-level altitude maps in the upper Rio Grande Alluvial Basins" child item of this data release. These digital data accompany Houston, N.A., Thomas, J.V., Foster, L.K., Pedraza, D.E., and Welborn, T.L., 2020, Hydrogeologic framework, groundwater-level altitudes, groundwater-level changes, and groundwater-storage changes in selected alluvial basins of the upper Rio Grande...
Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Abiquiu Reservoir, Ahumada, Alamosa, Alamosa County, Alamosa Creek, All tags...
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Sandbars of large sand-bedded rivers of the Central U.S. serve important ecological functions to many species, including the endangered Interior Least Tern (Sternula antillarum) (ILT). ILT are colonial birds which feed on fish and nest primarily on riverine sandbars during their annual breeding season of approximately May through July, depending on region. During this time, ILT require bare sand of sufficient elevation so as not to be inundated during the period between nest initiation and fledging of hatchlings. ILT were originally listed as endangered due in part to decreases in available sandbar habitat from river channelization and impoundment. Sandbars in Central U.S. rivers used by ILT are highly dynamic,...
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We produced a time series of maps of habitat structure within wetlands of the Central Valley of California. The structure of open water and tall emergent vegetation, such as Typha spp. and Schoenoplectus spp., is critical for migratory birds. Through field observation and digitization of high resolution imagery we identified the locations of tall emergent vegetation, water, and other land cover. Using a random forest classification, we classified multispectral Landsat 8 imagery 2013-2017. We used images from the fall when most wetlands are flooded and the summer to separate trees and tall emergent vegetation. The final maps show the distribution and extent of tall emergent vegetation within wetlands. Final time...
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We produced a series of maps of moist soil seed plants within managed wetlands in the Central Valley of California from 2007-2011 & 2013-2017. Moist soil seed plants, such as swamp timothy (Crypsis schoenoides) and watergrass (Echinochloa crusgallim), are a critical food source for migratory birds. Vegetation maps were created by classifying Landsat imagery from 2007-2011 and 2013-2017. A support vector machine learning classifier was trained using phenology metrics of moist soil seed plants, emergent vegetation, water, and other land cover observed via field surveys and high resolution imagery. Productivity maps of swamp timothy were based on a regression model of seed head weight with Landsat vegetation indices....
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These data are a compilation of four mask layers (regions), and enhanced vegetation indices calculated from airborne or satellite imagery. The mask layers were used created to extract satellite EVI data from the four airborne or satellite imagery datasets. The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. These data were created to compare Landsat 5 (2000–2011), 8 (2013–2016) and the Visible Infrared...
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We produced a series of maps of moist soil seed plants within managed wetlands in the Central Valley of California from 2007-2011 & 2013-2017. Moist soil seed plants, such as swamp timothy (Crypsis schoenoides) and watergrass (Echinochloa crusgallim), are a critical food source for migratory waterfowl. Through field observation and digitization of high resolution imagery we identified the locations of moist soil seed plants, tall emergent vegetation, water, and other land cover. Using a Support Vector Machine classification, we classified multispectral Landsat imagery from 2007-2011 and 2013-2017. We used images from May through August to create phenology metrics. The final datasets were used to train and test the...
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We developed an approach to quantify Urban Heat Island (UHI) extent and intensity in Atlanta, GA and its surrounding area by using surface temperature from Landsat surface temperature product in a time series manner. Landsat land surface temperature from Landsat Analysis Ready Data (ARD) were used to quantify surface temperature changes from 1985 to 2018. The current study assessed UHI intensity and its variations associated with urban development in an annual basis. Two datasets, over the study period, show that the maximum surface temperature in the high intensity urban area significantly increased while no significant trend was found in surrounding non-urban areas. These released datasets were spatially in 30...
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The passage of the North American Trade Agreement (NAFTA),establishment of the Border Environmental Cooperation Commissionas well as the EPA U.S./Mexico Border XXI Program has focusedattention to the environmental social-cultural, and economicconditions in the United States-Mexico frontier and to theenhanced necessity of a binational, transborder approach inaddressing problems. Towards this end, this U.S.-Mexicoborderlands Thematic Mapper selection is designed to be utilizedas fundamental part of a basic geographic information systemdatabase for natural resource, environmental, and land-managementstudies.
Tags: 04003 = Cochise, 04013 = Maricopa, 04019 = Pima, 04023 = Santa Cruz, 04027 = Yuma, All tags...
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These data were compiled to compare the ability of matched filtering (MF) and linear spectral mixture analysis (LSMA) to map isolated wetland sites using Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) data. We analyzed 81 stock ponds corresponding to a 2007 Landsat 5 image and 73 sites corresponding to a 2014 Landsat 8 image in southern Arizona and northern Sonora, Mexico, with ponds ranging from completely dry to ~17,000 m2 surface water. Both Landsat images we used were Tier 1 Level-1 terrain corrected scenes acquired from Earth Explorer (https://earthexplorer.usgs.gov), which were provided as individual bands represented by digital numbers (DNs). The inundation extent of stock ponds...
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We produced a series of maps of moist soil seed plants within managed wetlands in the Central Valley of California from 2007-2011 & 2013-2017. Moist soil seed plants, such as swamp timothy (Crypsis schoenoides) and watergrass (Echinochloa crusgallim), are a critical food source for migratory birds. For each of the Moist Soil Seed maps from 2007 to 2017, we mapped productivity of swamp timothy where swamp timothy was mapped according to a multiple regression of the average log seed head weight per Landsat pixel to Landsat derived values for green chlorophyll index (NIR/green - 1), swir1 reflectance, red green simple ratio (red/green) and SSURGO derived percent clay (STprod). For areas mapped as watergrass, we mapped...
We established a Landsat-derived geospatial database of unburned islands within 2,298 fires across the Inland Northwestern US (including eastern Washington, eastern Oregon, and Idaho) from 1984-2014. The detection of unburned areas within these fires is based upon a classification tree approach that uses two pre- and post-fire Landsat image pairs (see Meddens et al 2016 for details). The data set consist of unburned patches within each fire that are two pixels or larger. This database will be useful for identifying fire refugia, seed sources, and can be used as an overall metric of fire impacts across the northwestern US. (Meddens, A.J., Kolden, C.A., & Lutz, J.A. (2016). Detecting unburned areas within wildfire...
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These data are spatial polygon data and remote sensing image-based classification maps of surface water and vegetation species for 2012 along the Rio Grande River in Big Bend National Park in Texas. The geographic extent of the classification spans from the end of Mariscal Canyon to 5 km after the end of Boquillas Canyon, totaling approximately 77 Km of the river. The maps are also restricted to a digitized extent of riparian vegetation that is defined by the alluvial valley of the Rio Grande River. The 2012 classification maps are created using 20 cm multispectral (Near Infrared (NIR), Red and Green) imagery and LiDAR data collected in June 2012. The accuracy assessment for the classification product is based on...
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We developed an approach to quantify Urban Heat Island (UHI) extent and intensity in selected metropolitan areas in the United States by using Landsat surface temperature product in a time series manner. Landsat land surface temperature from Landsat Analysis Ready Data (ARD) were used to quantify surface temperature and change from 1985 to the current. These data were used to calculate the temperature difference between urban and surrounding rural areas as the UHI intensity in an annual basis. The annual changes of UHI intensity associated with urban development were also quantified. Two datasets containing the annual mean and annual maximum surface temperatures that were spatially in 30 meters resolution were included....
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These data are a species-level classification map of riparian vegetation in the Colorado River riparian corridor in Grand Canyon, Arizona, USA. The classification is derived from 0.2 m pixel resolution multispectral aerial imagery acquired in May 2013. The classification spans the riparian zone of the river corridor between Glen Canyon Dam near Page, Arizona, and Lake Mead at Pearce Ferry, Arizona. The classification is divided into 5 distinct reaches of the river: Glen Canyon, Marble Canyon, Eastern Grand Canyon, Western Grand Canyon upstream of Diamond Creek, and Western Grand Canyon downstream of Diamond Creek. The method used for classification was a combination of supervised Classification And Regression Tree...
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Consumptive use (CU) of water is an important factor for determining water availability and groundwater storage. Many regional stakeholders and water-supply managers in the Upper Rio Grande Basin have indicated CU is of primary concern in their water-management strategies, yet CU data is sparse for this area. This polygon feature class, which represents irrigated acres for 2015, is a geospatial component of the U.S. Geological Survey National Water Census Upper Rio Grande Basin (URGB) focus area study's effort to improve quantification of CU in parts of New Mexico, west Texas, and northern Chihuahua. These digital data accompany Ivahnenko, T.I., Flickinger, A.K., Galanter, A.E., Douglas-Mankin, K.R., Lentz, W.,...
Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Abiquiu Reservoir, Ahumada, Alamosa, Alamosa County, Alamosa Creek, All tags...
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This data bundle contains some of the inputs, all of the processing instructions and all outputs from two VisTrails/SAHM workflow. These models specifically include field data of locations with >40% cover of cheatgrass (presence) and <40% cover of cheatgrass (absence). Predictors included rasters derived from LandSat 8 imagery (_archive_FinalModel_revised) or from a digital elevation model (_archive_TopoOnly_revised). Details about all inputs are included in the associated manuscript. The three bundle documentation files in each data bundle are: 1) '_archive_bundle_metadata.xml' (this file) which contains FGDC metadata describing the archive bundle. 2) '_archive_raster_inputs.csv' a list of the raster inputs that...
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We developed an approach to quantify Urban Heat Island (UHI) extent and intensity in Minneapolis, MN and its surrounding area by using surface temperature from Landsat surface temperature products in a time series manner. Landsat land surface temperature data from Landsat Analysis Ready Data (ARD) were used to quantify surface temperature changes from 1985 to 2018. The current study assessed UHI intensity and its variations associated with urban development on an annual basis. This dataset, over the study period, show that the maximum surface temperature in the high intensity urban area significantly increased while no significant trend was found in surrounding non-urban areas. The datasets were annual averages...
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We developed an approach to quantify Urban Heat Island (UHI) extent and intensity in Sioux Falls, SD and its surrounding area by using surface temperature from Landsat surface temperature products in a time series manner. Landsat land surface temperature data from Landsat Analysis Ready Data (ARD) were used to quantify surface temperature changes from 1985 to 2018. The current study assessed UHI intensity and its variations associated with urban development on an annual basis. This dataset, over the study period, show that the maximum surface temperature in the high intensity urban area significantly increased while no significant trend was found in surrounding non-urban areas. The released datasets were annual...
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The U.S. Geological Survey collected multispectral and visible light imagery via a quadcopter, small unoccupied aircraft system (sUAS) deployed near Ashville Bridge Creek in Virginia Beach, VA. Approximately 0.25 sq mi surrounding U.S.Fish and Wildlife Service (USFWS) Back Bay National Wildlife Refuge along Ashville Bridge Creek approximately 0.5 mi south of Lotus Garden Park on July 17 and 18, 2018. Photos were collected at a height of 400ft above ground level (AGL) with approximately 70% frontlap between photos and approximately 30% sidelap between survey lines. Multispectral images were collected in a tif format using a Micasense RedEdge M with a Ground Sample Distance of 8.2 cm/pixel, visible light images were...


map background search result map search result map Processed Thematic Mapper satellite imagery for selected areas within the U.S.-Mexico borderlands Cheatgrass mapping in Squirrel Creek Wildfire, WY in 2014 Unburned areas within fire perimeters across the Inland Northwestern USA from 1984 to 2014 Interior Least Tern Sandbar Nesting Habitat Measurements from Landsat TM Imagery: Land Cover Type Classification Files Wetland Habitat Structure Maps for the Central Valley of California 2013-2017 2015 Irrigated acres feature class for the Upper Rio Grande Basin, New Mexico and Texas, United States and Chihuahua, Mexico Enhanced Vegetation Index (EVI) parameter data products from Landsat 5, Landsat 8 MODIS and the Visible Infrared Imaging Radiometer Suite (VIIRS), Colorado River Delta, Mexico Wetland Moist Soil Seed Maps for the Central Valley of California 2007-2017 Surface water data for isolated stock ponds in southern Arizona, USA and northern Sonora, Mexico Riparian species vegetation classification data for the Colorado River within Grand Canyon derived from 2013 airborne imagery Multispectral and visual photogrammetric data collected via sUAS: Back Bay National Wildlife Refuge, Virginia, July 2018 Wetland Moist Soil Seed Maps for the Central Valley of California 2007-2017: Training and Testing Data Wetland Moist Soil Seed Productivity Maps for the Central Valley of California 2007 - 2017 Rio Grande 2012 Vegetation and Water Classification Data in the Big Bend Region Groundwater-level altitude and groundwater-level change maps developed for the groundwater component of the upper Rio Grande Focus Area Study Land surface thermal feature change monitoring in urban and urban wild land interface (ver. 2.0, August 2020) Long-term field observation of shrubland ecosystem in Wyoming, USA from 2008-2018 Land surface thermal feature (Tmax) change monitoring in urban and urban wild land interface in Atlanta, GA from 1985-2018 (version 2.0) Land surface thermal feature (Tmax) change monitoring in urban and urban wild land interface in Sioux Falls, SD from 1985-2018 (version 2.0) Land surface thermal feature (Tmax) change monitoring in urban and urban wild land interface in Minneapolis, MN from 1985-2018 (version 2.0) Multispectral and visual photogrammetric data collected via sUAS: Back Bay National Wildlife Refuge, Virginia, July 2018 Cheatgrass mapping in Squirrel Creek Wildfire, WY in 2014 Rio Grande 2012 Vegetation and Water Classification Data in the Big Bend Region Surface water data for isolated stock ponds in southern Arizona, USA and northern Sonora, Mexico Enhanced Vegetation Index (EVI) parameter data products from Landsat 5, Landsat 8 MODIS and the Visible Infrared Imaging Radiometer Suite (VIIRS), Colorado River Delta, Mexico Land surface thermal feature (Tmax) change monitoring in urban and urban wild land interface in Sioux Falls, SD from 1985-2018 (version 2.0) Riparian species vegetation classification data for the Colorado River within Grand Canyon derived from 2013 airborne imagery Land surface thermal feature (Tmax) change monitoring in urban and urban wild land interface in Minneapolis, MN from 1985-2018 (version 2.0) Long-term field observation of shrubland ecosystem in Wyoming, USA from 2008-2018 Land surface thermal feature (Tmax) change monitoring in urban and urban wild land interface in Atlanta, GA from 1985-2018 (version 2.0) Groundwater-level altitude and groundwater-level change maps developed for the groundwater component of the upper Rio Grande Focus Area Study Wetland Habitat Structure Maps for the Central Valley of California 2013-2017 Wetland Moist Soil Seed Maps for the Central Valley of California 2007-2017 Wetland Moist Soil Seed Maps for the Central Valley of California 2007-2017: Training and Testing Data Wetland Moist Soil Seed Productivity Maps for the Central Valley of California 2007 - 2017 2015 Irrigated acres feature class for the Upper Rio Grande Basin, New Mexico and Texas, United States and Chihuahua, Mexico Unburned areas within fire perimeters across the Inland Northwestern USA from 1984 to 2014 Processed Thematic Mapper satellite imagery for selected areas within the U.S.-Mexico borderlands Interior Least Tern Sandbar Nesting Habitat Measurements from Landsat TM Imagery: Land Cover Type Classification Files Land surface thermal feature change monitoring in urban and urban wild land interface (ver. 2.0, August 2020)