Filters: Tags: multispectral imaging (X)
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Surface Urban Heat Island (SUHI) hotspot data are defined as areas of statistically high land surface temperature (LST). A pixel is determined as statistically high if it exceeds one standard deviation above the mean of all pixels with similar land cover type. Data are provided across 50 regions throughout the Continental U.S. using previously generated annual maximum land surface temperature (MeanLST) – derived from Collection 1 Landsat U.S. Analysis Ready Data (ARD) for Surface Temperature. The data ranges from 1985-2020, and covers data within 5 km of each city. The data is further separated into persistent urban and new urban outputs. Persistent Urban is defined as areas that are reported as urban in 1985 and...
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...
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...
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...
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...
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., Pedraza, D.E.,...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Abiquiu Reservoir,
Ahumada,
Alamosa,
Alamosa County,
Alamosa Creek,
These orthophotos and digital surface model (DSM) were derived from low-altitude (approximately 92-m above ground surface) images collected from Unmanned Aerial System (UAS) flights over edge-of-field sites that are part of U.S. Geological Survey (USGS) Great Lakes Restoration Initiative (GLRI) monitoring. The objective of this UAS photogrammetry data collection was to provide information on the tile-drain network in individual fields with the goal of understanding already observed patterns in runoff amount and water quality from these sites. A 3DR Solo quadcopter served as the flight vehicle, flights were pre-planned using Mission Planner, and flights were flown using Tower. Geospatial data were originally in WGS84...
Categories: Data;
Tags: Door County,
Great Lakes,
USGS Science Data Catalog (SDC),
Water Resources,
Wisconsin,
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...
Categories: Data;
Types: Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Drought, Fire and Extreme Weather,
Drought, Fire and Extreme Weather,
Fire,
Idaho,
Landscapes,
Surface Urban Heat Island (SUHI) intensity data is intended to quantify the difference between urban surface temperatures and the surrounding non-urban environment. The calculation takes the difference between a specific urban pixel’s maximum land surface temperature (MeanLST) and the mean of the cities non-urban MeanLST. Data are provided across 50 regions throughout the Continental U.S. using previously generated annual MeanLST – derived from Collection 1 Landsat U.S. Analysis Ready Data (ARD) for Surface Temperature. The data ranges from 1985-2020, and covers data within 5 km of each city. NOTE: While a previous version is available from the author, all datasets for pilot cities can be found in version 5.0.
We developed an approach to quantify Urban Heat Island (UHI) extent and intensity in 50 cities of CONUS 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 2020. 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...
Categories: Data;
Tags: CONUS,
CONUS,
Landsat ARD,
Landsat Analysis Ready Data (ARD),
United States,
This data package includes 17,014 pairs of raster geotiffs. Each pair is made up of two geotiff rasters derived from historical observations from Landsat satellites (04-09) over the Yukon, Kuskokwim, and Tanana rivers in Alaska. One raster reports estimated mid-day water surface temperature (ST) in degrees Celsius (deg_Cc). The second raster reports the surface temperature quality assessment (sST_QA_c) and provides the ST product uncertainty (also in degrees). The period of observation is May through October for the years 1984-2022.
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...
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...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Ashville Bridge Creek,
Back Bay National Wildlife Refuge,
City of Virginia Beach,
Ecology,
Environmental Health,
The dataset comprises a Landsat-derived assessment of monthly surface water extent within the study area (California's greater Central Valley). The surface water dataset is based on the algorithm for the Dynamic Surface Water Extent (DSWE) (Jones, 2019), which was adapted to the Google Earth Engine JavaScript environment. The level of spatial aggregation is by level-8 hydrologic unit code (HUC).
Categories: Data;
Tags: California,
California Mountain,
California Valley,
Central California Valley,
Landsat,
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,...
Categories: Data;
Types: Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Arkansas River,
Canadian River,
Cheyenne River,
Cimarron River,
Interior Least Tern,
Multispectral remote sensing data acquired by Landsat 8 Operational Land Imager (OLI) sensor were analyzed using an automated technique to generate surficial mineralogy and vegetation maps of the conterminous western United States. Six spectral indices (e.g. band-ratios), highlighting distinct spectral absorptions, were developed to aid in the identification of mineral groups in exposed rocks, soils, mine waste rock, and mill tailings across the landscape. The data are centered on the western U.S. and cover portions of Texas, Oklahoma, Kansas, the Canada-U.S. border, and the Mexico-U.S. border during the summers of 2013 – 2014. Methods used to process the images and algorithms used to infer mineralogical composition...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Arizona,
California,
Canada,
Colorado,
Idaho,
SPECPRsplib07 This compressed archive includes: Files, in SPECPR format, containing spectral data and associated metadata descriptions: measured spectra (splib07a) spectra interpolated to a higher number of more finely-spaced channels (splib07b) spectra convolved to other spectrometers, for example Analytical Spectral Devices standard resolution (s07_ASD) AVIRIS-Classic 2014 characteristics (s07_AV14) Hyperspectral Mapper (HyMap) 2014 characteristics (s07_HY14) and others spectra resampled to multispectral sensors: ASTER Landsat 8 OLI Sentinel-2 MSI Worldview-3 Folders containing information linked to from the metadata descriptions in the SPECPR files: README: contains a HTML version of the USGS Data...
Surface Urban Heat Island (SUHI) intensity data is intended to quantify the difference between urban surface temperatures and the surrounding non-urban environment. The calculation takes the difference between a specific urban pixel’s maximum land surface temperature (MaxLST) and the mean of the cities non-urban MaxLST. Data are provided across 50 regions throughout the Continental U.S. using previously generated annual MaxLST – derived from Collection 1 Landsat U.S. Analysis Ready Data (ARD) for Surface Temperature. The data ranges from 1985-2020, and covers data within 5 km of each city. NOTE: While a previous version is available from the author, all datasets for pilot cities can be found in version 5.0.
This vector dataset consists of 2 polygon shapefiles representing the groundwater discharge areas (GDA) and evapotranspiration (ET) units for the Amargosa Wild and Scenic River and contributing areas. GDAs were delineated by visual interpretation and subdivided into ET units of moist soil, open water, and vegetated areas.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Amargosa River,
California,
California Valley,
Chicago Valley,
ET unit,
GIFplots Files containing GIF images of spectral plots: GIFplots_splib07a.zip contains plots of measured spectra, including plots showing the full wavelength range of the measured spectra, organized in chapter sub-folders as described previously for the ASCII data. plots showing specific portions of the electromagnetic spectrum are organized folders within the “plots_by_wavelength_region” folder, including: range1_uv_to_visible (0.2 - 1.0 microns) range2_visible_to_swir (0.2 - 2.5 microns) range3_swir (1.5 - 5.5 microns) range4_swir_to_mir (2.5 - 25 microns) range5_swir_to_fir_wavenumber (4,000 - 50 cm-1 which spans 2.5 - 200 microns) plots of spectra interpolated to a higher number of more finely-spaced...
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