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This data release accompanies a U.S Geological Survey study that assessed sediment, salinity, and selenium yields following the Dead Dog wildfire in northwestern Colorado. The Dead Dog fire ignited on June 11, 2017, near Rangely, Colorado, and burned over 17,000 acres, including the B2 study area. Two methodologies were used to quantify erosion and associated salinity and sediment yields in the B2 study area: (1) modeled soil loss post-fire using a physically based erosion model, and (2) measured post-fire volumetric soil erosion and deposition using a time series of digital elevation models (DEMs) created from Uncrewed Aerial Vehicle (UAV) imagery. The first methodology used a physically based erosion model, the...
U.S. Geological Survey (USGS) and Virginia Institute of Marine Science (VIMS) scientists conducted field data collection efforts during June 11th - 16th, 2020, using a combination of remote sensing technologies to map riverbank and wetland topography and vegetation at five sites in the Chesapeake Bay Region of Virginia. The five sites are located along the James, Severn, and York Rivers. The work was initiated to evaluate the utility of different remote sensing technologies in mapping river bluff and wetland topography and vegetation for change detection and sediment transport modeling. The USGS team collected Global Navigation Satellite System (GNSS), total station, and ground based lidar (GBL) data while the VIMS...
The Chesapeake Bay Estuary is the largest estuary in the United States and provides habitats for diverse wildlife and aquatic species, protects communities against flooding, reduces pollution to waterways, and supports local economies through commercial and recreational activities. In the Spring of 2018, the U.S. Geological Survey (USGS) Coastal National Elevation Database (CoNED) Applications Project at the USGS Earth Resources Observation and Science (EROS) Center and the Virginia Institute of Marine Science (VIMS) Center for Coastal Resources Management (CCRM) initiated collaborative work. The goal of this collaboration is to evaluate how various remote sensing technologies can be employed to model estuarine...
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,
These data were compiled to enable estimation of aeolian dune field sediment budgets calculated using remote sensing methods. The objective of the study was to evaluate sediment budgets calculated for the Lees Ferry dune field in Grand Canyon, Earth as a terrestrial analog for aeolian dune fields in Valles Marineris, Mars. These data represent digital elevation models (DEM) of the topography of the Lees Ferry dune field in February and May, 2019, respectively. These data were collected with an Uncrewed Aerial Vehicle (UAV) remote sensing survey conducted on February 28th and then repeated on May 2nd, 2019. The images acquired with the UAV surveys were processed with photogrammetric modelling to produce the DEMs....
U.S. Geological Survey (USGS) and University of Hawaii - Mānoa (UH) scientists conducted field data collection efforts from August 19th - 27th, 2019 at Pu‘uhonua O Hōnaunau National Historical Park on the Big Island of Hawaii. The data collection efforts utilized a combination of remote sensing technologies to map the topography, critical infrastructure, and most importantly, the cultural assets of Pu‘uhonua O Hōnaunau National Historical Park. The USGS and UH team collected Global Navigation Satellite System (GNSS), total station, and ground based lidar (GBL) data, along with utilizing Uncrewed Aerial Systems (UAS) to collect imagery and UAS lidar to map these features. This data release contains shapefiles of...
U.S. Geological Survey (USGS) scientists conducted field data collection efforts during the weeks of September 9-13 and November 18-22, 2019, using a combination of technologies to map and validate topography, vegetation, and features in two areas of interest (AOI's) in north central Colorado. The western AOI included land managed by the Bureau of Land Management and the U.S. Forest Service. The eastern AOI included agricultural and urban areas. The work was initiated as an effort to test and evaluate the Leica Geosystems CountryMapper sensor. The CountryMapper is a hybrid sensor that collects imagery and light detection and ranging (lidar) data simultaneously. The CountryMapper has the potential to collect data...
This dataset contains magnetometry data and design files related to testing of new drone-based magnetometer configurations and magnetic compensation software. Data were collected in Santa Cruz (CA) in September 2020 to compare two magnetometer systems that are flown with Unmanned Aerial Systems (UAS). Each system was flown using different suspension designs. To compare the systems and to characterize noise levels of the systems, calibration patterns and dense grid surveys were flown with each configuration. This dataset was further used to test magnetic compensation software. The overall aim of this study was to compare the variability of different UAS-based magnetometry systems that can be used for geophysical...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Geophysics,
Santa Cruz, CA,
Surprise Valley, CA,
UAS,
UAV,
U.S. Geological Survey (USGS) and Virginia Institute of Marine Science (VIMS) scientists conducted field data collection efforts during the week of April 8th - 14th, 2018, using a combination of remote sensing technologies to map riverbank and wetland topography and vegetation at four sites in the Chesapeake Bay Region of Virginia. The four sites are located along the James, Severn, and York Rivers. The work was initiated to evaluate the utility of different remote sensing technologies in mapping river bluff and wetland topography and vegetation for change detection and sediment transport modeling. The USGS team collected Global Navigation Satellite System (GNSS), total station, and ground based lidar (GBL) data...
The UAV imagery was collected by the Hawaii Coastal Geology Group of the University of Hawai'i, Manoa in August of 2017 for USGS. The UAV model is Phantom 4 with the camera model FC6310. The UAV was flown 90 meters above sea level at site Rita and 100 meters above sea level at site AIPA.
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