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This product is the result of a comprehensive compilation of site-specific ground photographs taken where tectonic faulting and ground failure produced visible deformation that fractured and disturbed the ground surface. The resultant data is distributed as a tab-delimited text file. All post-earthquake photographs taken by investigators working for public agencies are in the public domain, including data that have been published in summary reports elsewhere.
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Hillshade of lidar-derived, bare earth digital elevation model, with 235-degree azimuth and 20-degree sun angle, 0.25m resolution, depicting earthquake effects following the August 24, 2014 South Napa Earthquake.
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This product is the result of a comprehensive compilation of site-specific ground photographs taken where tectonic faulting and ground failure produced visible deformation that fractured and disturbed the ground surface. The resultant data is distributed as collection of JPEG image files. All post-earthquake photographs taken by investigators working for public agencies are in the public domain, including data that have been published in summary reports elsewhere. These photographs are best viewed in context with fault rupture and other observations from the related KMZ file of summary field observations and photographs (https://www.sciencebase.gov/catalog/item/5c1d7ae0e4b0708288ca1322), or from the associated open-file...
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These digital images were taken at select locations over the Potomac River using 3DR Solo unmanned aircraft systems (UAS) in October 2019. These images were collected for the purpose of evaluating UAS assessment of river habitat data such as water depth, substrate type, and water clarity. Each UAS was equipped with a Ricoh GRII digital camera for natural color photos, used to produce digital elevation models and ortho images, a MicaSense RedEdge multi-spectral camera that captures five specific bands of the visible spectrum (blue, green, red, rededge, and near-infrared), which can be used to classify vegetation, or FLIR Vue Pro R 640 13mm radiometric thermal camera that provides temperature data embedded in every...
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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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Low-altitude (80 and 100 meters above ground level) digital images were collected at Sage Lot Pond in Waquoit, Massachusetts, two sites on the Mill River in Taunton, MA, Great Marsh in Barnstable, MA, the Wells National Estuarine Research Reserve in Wells, ME, and on the Woods Hole Oceanographic Institution Quissett Campus in Woods Hole, MA using 3DR Solo unoccupied aircraft systems (UAS) during 2018. These images were collected to support science and data needs in wetland research, topographic mapping, and landcover detection at the U.S. Geological Survey Woods Hole Coastal and Marine Science Center. The imagery and associated ground control points can be used to create Digital Elevation Models (DEMs), orthoimages,...
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Geophysical and geological survey data were collected off Town Neck Beach in Sandwich, Massachusetts, in May and July 2016. Approximately 130 linear kilometers of subbottom (seismic-reflection) and 234-kilohertz interferometric sonar (bathymetric and backscatter) data were collected along with sediment samples, sea floor photographs, and (or) video at 26 sites within the geophysical survey area. Sediment grab samples were collected at 19 of the 26 sampling sites and video and (or) photographic imagery of the sea floor were taken at all 26 sites. These survey data are used to characterize the sea floor by identifying sediment-texture, seabed morphology, and underlying geologic structure and stratigraphy. Data collected...
Categories: Data; Tags: Atlantic Ocean, CMGP, Cape Cod, Cape Cod Bay, Coastal and Marine Geology Program, All tags...
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Low-altitude (80-100 meters above ground level) Unmanned Aircraft Systems (UAS) imagery of Town Neck Beach in Sandwich, Massachusetts, were used in a structure-from-motion (SfM) photogrammetry workflow to create high-resolution topographic datasets. Imagery was collected at close to low tide on twelve days to observe changes in beach and dune morphology. Ground control points (GCPs), which are temporary targets on the ground located by using a real-time kinematic global navigation satellite system (RTK-GNSS) base station and rover, were used to constrain the SfM process. Photoscan (v. 1.2-1.4) was used to create a digital elevation model and orthomosaic for each data collection day. Collection of these data was...
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Low-altitude (80-100 meters above ground level) Unmanned Aircraft Systems (UAS) imagery of Town Neck Beach in Sandwich, Massachusetts, were used in a structure-from-motion (SfM) photogrammetry workflow to create high-resolution topographic datasets. Imagery was collected at close to low tide on twelve days to observe changes in beach and dune morphology. Ground control points (GCPs), which are temporary targets on the ground located by using a real-time kinematic global navigation satellite system (RTK-GNSS) base station and rover, were used to constrain the SfM process. Photoscan (v. 1.2-1.4) was used to create a digital elevation model and orthomosaic for each data collection day. Collection of these data was...
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LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Cover (EVC) represents the vertically projected percent cover of the live canopy for a 30-m cell. EVC is produced separately for tree, shrub, and herbaceous lifeforms. Training data depicting percentages of canopy cover are obtained from plot-level ground-based visual assessments and lidar observations. These are combined with Landsat imagery (from multiple seasons), to inform models built independently for each lifeform. Tree, shrub, and herbaceous lifeforms each have a potential range from 10% to 100% (cover values less than 10% are binned into the 10% value). The three independent lifeform datasets are merged into a single product based on the dominant...
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LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. Historical Disturbance (HDist) is developed from the base annual LF disturbance products, and attribute code system, to represent the history of disturbance for a 10-year span. Each year's disturbance scenarios are checked against time relevant LF vegetation products to check for logical inconsistencies. Errant codes are flagged and updated to a discard code with the remaining disturbance types cross-walked/aggregated to Fuel Disturbance (FDist) types. HDist includes the year of disturbance that is recorded for that pixel. In LF 2022, the time since disturbance code is the same for both HDist...
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LANDFIRE (LF) 2022 Fuel Vegetation Type (FVT) represents the LF Existing Vegetation Type Ecological Systems (EVT) product, modified to represent pre-disturbance EVT in areas where disturbances have occurred over the past 10 years. Due to shifting EVT codes and labels throughout the years, the FVT codes are based on an early version of EVT codes translated from the current version. FVT is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVT is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances...
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These data represent total vegetation and surface water along approximately 12 kilometers of the Paria River upstream from the confluence of the Colorado River at Lees Ferry, Arizona. They are derived from airborne, multispectral imagery obtained in late May 2009, 2013, and 2021, collected with a push-broom sensor with 4 spectral bands depicting Blue, Green, Red and Near-Infrared wavelengths at a spatial resolution of 20 centimeters. The vegetation classification data were created using a supervised classification algorithm provided by Harris Geospatial in ENVI version 5.6.3 (Exelis Visual Information Solutions, Boulder, Colorado). The water data were created using a Green Normalized Difference Vegetation Index...
Tags: Arizona, Botany, Cloud Optimized GeoTIFF data, Colorado River, Ecology, All tags...
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LANDFIRE's (LF) 2022 Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand. CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. CC supplies information for fire behavior models to determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. To create this product, plot level CC values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance CC and Canopy Height (CH) are used as predictors of disturbed CC using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and...
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LANDFIRE (LF) 2022 Fuel Vegetation Cover (FVC) represents the LF Existing Vegetation Cover (EVC) product, modified to represent pre-disturbance EVC in areas where disturbances have occurred over the past 10 years. EVC is mapped as continuous estimates of canopy cover for tree, shrub, and herbaceous lifeforms with a potential range from 10% to 100%. Continuous EVC values are binned to align with fuel model assignments when creating FVC. FVC is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. To designate disturbed areas where FVC is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance...
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In May 2021, the Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey’s (USGS), Southwest Biological Science Center (SBSC) acquired airborne multispectral high resolution data for the Colorado River in Grand Canyon in Arizona, USA. The imagery data consist of four bands (Band 1 – red, Band 2 – green, Band 3 – blue, and Band 4 – near infrared) with a ground resolution of 20 centimeters (cm). These image data are available to the public as 16-bit GeoTIFF files, which can be read and used by most geographic information system (GIS) and image-processing software. The spatial reference of the image data are in the State Plane (SP) map projection using the central Arizona zone (FIPS 0202)...
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This imagery dataset consists of 3-meter resolution, lidar-derived imagery of the Carlisle 30 x 60 minute quadrangle in Pennsylvania. The source data used to construct this imagery consists of 1-meter resolution lidar-derived digital elevation models (DEMs). The lidar source data were compiled from different acquisitions published between 2019 and 2020 and downloaded from the USGS National Map TNM Download. The data were processed using geographic information systems (GIS) software. The data is projected in WGS 1984 Web Mercator. This representation illustrates the terrain as a hillshade with contrast adjusted to highlight local relief according to a topographic position index (TPI) calculation.
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Low-altitude (70 m above ground level) aerial images were collected over five areas of interest within the northern portion of Assateague Island National Seashore (ASIS) in mid-October, 2022. These images were collected to generate photogrammetric products (e.g. digital surface model (DSM), reflectance orthomosaic) to support science and data needs of National Park managers attempting to locate invasive Phragmites australis expansion. A DJI Matrice 600 uncrewed aircraft system (UAS) was equipped with a MicaSense Altum-PT multispectral camera and a Ricoh GRII true-color RGB camera to collect images simultaneously with sufficient overlap for photogrammetric processing. Ground control points (GCPs), black and white...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Freshwater Introduction South of Highway 82 (ME-16) project for 2018. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss...
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The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Oyster Bayou Marsh Creation and Terracing (CS-59) project for 2018. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within...


map background search result map search result map Photographs of fault rupture and ground deformation features produced by the Mw 6.0 South Napa earthquake of August 24, 2014 Hillshade raster (235-degree azimuth, 20-degree sun angle) derived from lidar data collected after the August 24, 2014 South Napa earthquake Table of photograph metadata and links to full-resolution photographs taken at observation stations by post-earthquake reconnaissance teams, Mw 6.0 South Napa Earthquake of August 24, 2014 Location of bottom photographs along with images collected in July 2016 by the U.S. Geological Survey off Town Neck Beach, Sandwich, Massachusetts, during field activity 2016-037-FA (JPEG images, point shapefile, and CSV file) Low-altitude aerial imagery from unmanned aerial systems (UAS) at select locations over the Potomac River, October 2019 Long-term field observation of shrubland ecosystem in Wyoming, USA from 2008-2018 Multispectral aerial imagery collected during unoccupied aircraft systems (UAS) operations in Massachusetts between March 2018 - September 2018 Town Neck Beach, Massachusetts, 10 cm 2016-2017 Digital Elevation Models Town Neck Beach, Massachusetts, 5 cm 2016-2017 Orthomosaics Freshwater Introduction South of Highway 82 (ME-16): 2018 land-water classification Oyster Bayou Marsh Creation and Terracing (CS-59): 2018 land-water classification Multispectral aerial imagery collected during uncrewed aircraft systems (UAS) operations: Assateague Island National Seashore (ASIS), MD, October 10 - 14, 2022 Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI Aerial imagery data of the Colorado River Corridor, Arizona - 2021 Town Neck Beach, Massachusetts, 10 cm 2016-2017 Digital Elevation Models Location of bottom photographs along with images collected in July 2016 by the U.S. Geological Survey off Town Neck Beach, Sandwich, Massachusetts, during field activity 2016-037-FA (JPEG images, point shapefile, and CSV file) Oyster Bayou Marsh Creation and Terracing (CS-59): 2018 land-water classification Town Neck Beach, Massachusetts, 5 cm 2016-2017 Orthomosaics Vegetation and water classifications for a segment of the Paria River upstream of the Colorado River Confluence, Arizona, USA Multispectral aerial imagery collected during uncrewed aircraft systems (UAS) operations: Assateague Island National Seashore (ASIS), MD, October 10 - 14, 2022 Hillshade raster (235-degree azimuth, 20-degree sun angle) derived from lidar data collected after the August 24, 2014 South Napa earthquake Freshwater Introduction South of Highway 82 (ME-16): 2018 land-water classification Photographs of fault rupture and ground deformation features produced by the Mw 6.0 South Napa earthquake of August 24, 2014 Table of photograph metadata and links to full-resolution photographs taken at observation stations by post-earthquake reconnaissance teams, Mw 6.0 South Napa Earthquake of August 24, 2014 Multispectral aerial imagery collected during unoccupied aircraft systems (UAS) operations in Massachusetts between March 2018 - September 2018 Low-altitude aerial imagery from unmanned aerial systems (UAS) at select locations over the Potomac River, October 2019 Enhanced Terrain Imagery of the Carlisle 30 x 60 Minute Quadrangle from Lidar-Derived Elevation Models at 3-Meter Resolution Aerial imagery data of the Colorado River Corridor, Arizona - 2021 Long-term field observation of shrubland ecosystem in Wyoming, USA from 2008-2018 LANDFIRE 2022 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands LANDFIRE 2022 Historical Disturbance (HDist) HI LANDFIRE 2022 Existing Vegetation Cover (EVC) AK LANDFIRE 2022 Fuel Vegetation Cover (FVC) CONUS LANDFIRE 2022 Forest Canopy Cover (CC) CONUS