Filters: Tags: Unmanned Aircraft System (X)
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Aerial images in the vicinity of USGS gaging station #07094500 Arkansas River at Parkdale, Colorado were collected on March 20-22, 2018, using Unmanned Aircraft Systems (UAS, or "drones"). Data were processed using structure-from-motion analysis to generate a three-dimensional point cloud that identifies pixels from multiple images representing the same object and calculates the x, y, and z coordinates of that object/pixel. The point cloud was processed to create a digital surface model of the site. Finally, source images were stitched together based on shared pixels and orthogonally adjusted to create a high resolution (approximately 2 cm pixel size) orthoimage for the study area. The orthomosaic image captures...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service,
Raster;
Tags: Arkansas River,
Canon City,
Colorado,
Colorado,
North America,
This child item contains the Mathworks Matlab mat-file outputs from the scripts described in the Ancillary Scripts child item. Each file contains the results for a particular field site. See the FGDC metadata Process Steps section for more information about opening these files. The mat-files included here have a standard set of output variables and include a variable named "zzVariableDescriptions" in each mat-file which describes the contents of the file. The following variables and descriptions are included in each mat-file (extracted from the "zzVariableDescriptions" variable): calibration_distance: The distance between calibration points in meters. calibration_points: Pixel coordinates of the calibration points....
This child item contains Mathworks MATLAB script files which reproduce the processing steps for each dataset. The following scripts are included: MATLAB scripts to process the images extracted from sUAS videos for each site. See the FGDC metadata Data Quality Section Process Step 1 for details on these scripts: ACR_PIVLab_Script.m AFR_PIVLab_Script.m CCC_PIVLab_Script.m CMC_PIVLab_Script.m GLR_PIVLab_Script.m RMC_PIVLab_Script.m SMC_PIVLab_Script.m WMD_PIVLab_Script.m MATLAB scripts to post process the data into the form supplied in this data release. See the FGDC metadata Data Quality Section Process Steps 2 and 3 for details on these scripts: CalibrateData.m CreatePlots.m Each Field Site is abbreviated in...
To support an investigation of the feasibility of measuring river bathymetry using remotely sensed data acquired from a small unmanned aircraft system (sUAS), remotely sensed bathymetry and field measurements were collected from two cross-sections on the Colorado River near Parshall, CO on June 13, 2019. This parent data release includes links to child pages for the following data sets: 1) Lidar data used for mapping channel bathymetry (depth), acquired with a novel instrument that was developed by ASTRALiTe to distinguish between returns from the water surface and riverbed based on the polarization of laser pulses. 2) Field-based wading surveys of bed topography used to evaluate the bathymetric mapping capabilities...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry,
Colorado River, CO,
Parshall, CO,
Remote Sensing,
UAS,
The U.S. Geological Survey contracted with Juniper Unmanned to conduct field tests of the ASTRALiTe bathymetric lidar system on the Colorado River near Parshall, Colorado, on June 13, 2019. The objective of this project was to assess the potential to map river bathymetry (i.e., channel bed topography) using lidar data collected from an unmanned aircraft system (UAS). The ASTRALiTe lidar instrument was mounted on a DJI Matrice 600 Pro UAS owned and operated by Juniper Unmanned. As part of the study, Juniper's pilot flew the ASTRALiTe instrument across 2 river transects (cross-stream) on the Colorado River. This data release includes data delivered to the USGS by ASTRALite on August 1, 2019. The data have been parsed...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry,
Colorado River, CO,
Parshall, CO,
Remote Sensing,
UAS,
This child item contains images associated with each field site showing example output of PIV results as processed using the "CreatePlots.m" script file found in the Ancillary Scripts child item of this data release. Each Field Site is abbreviated in various files in this data release. File and folder names are used to quickly identify which site a particular file or dataset represents. The following abbreviations are used: ACR: Androscoggin River, Auburn, Maine, USA AFR: Agua Fria River, near Rock Springs, Arizona, USA CCC: Coachella Canal above All-American Canal Diversion, California, USA CMC: Cochiti East Side Main Channel, near Cochiti, New Mexico, USA GLR: Gila River near Dome, Arizona, USA RMC: Reservation...
The Hydrologic Remote Sensing Branch (HRSB) community is intended to host remote sensing technology datasets and information products to help WMA and Water Science Center (WSC) staff more safely and effectively gage streams, monitor water quality, and measure the hydrologic cycle.
The U.S. Geological Survey contracted with Juniper Unmanned to conduct field tests of the ASTRALiTe bathymetric lidar system on the Blue River and Colorado River near Kremmling, Colorado, on October 18, 2018. The objective of this project was to assess the potential to map river bathymetry (i.e., channel bed topography) using lidar data collected from an unmanned aircraft system (UAS). The ASTRALiTe lidar instrument was mounted on a DJI Matrice 600 Pro UAS owned and operated by Juniper Unmanned. As part of the study, Juniper's pilot flew the ASTRALiTe instrument across 2 river transects (cross-stream) on the Blue River and 2 river transects (cross-stream) on the Colorado River. This data release includes data delivered...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry,
Blue River,
Colorado River, CO,
Kremmling, Colorado,
Remote Sensing,
This page provides access to infrared, multispectral, visual image data, and derivative products collected along a beaver-impacted section of the East River from August 12-17, 2017 and July 28-August 2, 2018. This page may be updated in the future with additional data and analysis related to drone-based imaging.
This child item contains files representing Particle Image Velocimetry (PIV) processing masks which excluded regions of invalid velocities from the PIV results. Masks typically are used to screen out velocities or prevent the creation of velocities for regions of an image where computed PIV velocities would be nonsensical or invalid. For example, near or on the channel banks, where a tree overhangs the channel, or the presence of a boat or other object in the water. By using masks, these regions can be excluded from analysis. The PIVLab software allows for the designation of a rectangular Region of Interest (ROI). For five of the field sites, which were located at engineered canals, a rectangular ROI was sufficient...
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 U.S. Geological Survey contracted with Juniper Unmanned to conduct field tests of the ASTRALiTe bathymetric lidar system on the Blue River just upstream of its confluence with the Colorado River near Kremmling, Colorado, on October 18, 2018. The objective of this project was to assess the potential to map river bathymetry (i.e., channel bed topography) using lidar data collected from an unmanned aircraft system (UAS). The ASTRALiTe lidar instrument was mounted on a DJI Matrice 600 Pro UAS owned and operated by Juniper Unmanned. As part of the study, Juniper's pilot flew the ASTRALiTe instrument across 2 river transects (cross-stream) on the Blue River. This data release includes data delivered to the USGS by...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Blue River,
Colorado,
UAS,
Unmanned Aircraft System,
bathymetric lidar,
To suport an investigation of the feasibility of measuring river discharge using remotely sensed data acquired from an unmanned aircraft system (UAS), several types of remotely sensed data and field measurements were collected from two cross-sections on the Blue River in Colorado, just upstream of its confluence with the upper Colorado River, on October 18, 2018. This parent data release includes links to child pages for the following data sets: 1) Lidar data used for mapping channel bathymetry (depth), acquired with a novel instrument that was developed by ASTRALiTe to distinguish between returns from the water surface and riverbed based on the polarization of laser pulses. 2) Thermal image time series used to...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bathymetry,
Blue River,
Colorado,
Geomorphology,
Hydrology,
On May 25, 2014, a rain-on-snow induced rock avalanche occurred in the West Salt Creek Valley on the northern flank of Grand Mesa in western Colorado. The avalanche traveled 4.6 km down the confined valley, killing 3 people. The avalanche was rare for the contiguous U.S. because of its large size (54.5 Mm3) and long travel distance. To understand the avalanche failure sequence, mechanisms, and mobility, we mapped landslide structures, geology, and ponds at 1:1000-scale. We used high-resolution, Unmanned Aircraft System (UAS) imagery from July 2014 as a base for our field mapping. Here we present the map data and UAS imagery. The data accompany an interpretive paper published in the journal Geosphere. The full citation...
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Collbran,
Colorado,
Grand Mesa,
Green River Formation,
UAS,
The U.S. Geological Survey collected low-altitude airborne visual imagery via a multirotor, small unoccupied aircraft system (sUAS) along with Real Time Kinematic (RTK) GPS survey data at Childs along the Verde River in Arizona in December 2017. Visual imagery was collected in jpg format and Structure from Motion techniques were applied to the visual imagery to derive a time-specific high-resolution orthomosaic for the study site.
This dataset contains data collected during science flights using the drone-based QCam, which is a Doppler (velocity) radar designed to measure surface velocity and compute river discharge when channel bathymetry is known. Five science flights were conducted on the Arkansas River in Colorado and are presented as comma separated values (CSV) files.
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Canon City,
drone,
hydrographic datasets,
remote sensing,
sUAS,
This child item contains the image frames extracted from videos for each field site. The images serve as the input to the Particle Image Velocimetry (PIV) analysis. There are zip archive files for each field site included in this child item. Each of the zip files contain three directories of images: original: these are the image frames extracted from the videos without other modification. stable: these image frames have been created by running the original frames through an image stabilization program. See the FGDC metadata Process Steps for more information. stable_subtracted: these image frames have been created by using background subtraction on the stabilized images. See the FGDC metadata Process Steps for...
Small unoccupied aircraft systems (UAS) are now often used for collecting aerial visible image data and creating 3D digital surface models (DSM) that incorporate terrain and dense vegetation. Lightweight thermal sensors provide another sensor option for generation of sub meter resolution aerial thermal infrared orthophotos that can be used to infer hydrogeological processes. UAS-based sensors allow for the rapid and safe survey of groundwater discharge areas, often present in inaccessible, boggy, and/or dangerous terrain. Visible light and thermal infrared image data were collected March 2018 and March 2019, respectively, at Tidmarsh Farms, a former commercial cranberry bog located in coastal Massachusetts, USA...
A USGS Unoccupied Aircraft Systems (UAS) Aquatic Airshow field testing and demonstration event occurred March 20–21, 2018, on the Arkansas River at Parkdale, CO, USA. At the airshow, a group of USGS scientists and technicians gathered to test non-contact sensors for measuring stream discharge using UAS and a sensor mounted on a tag line. Scientists at the event performed a series of tests to measure river discharge with experimental non-contact techniques. USGS scientists and field personnel traditionally conduct a discharge measurement either by wading or working from a boat. Due to the potential danger and high risk to personnel safety, hydrologic measurement work is limited during very high flow events, ice break-up,...
Categories: Data;
Tags: Canon City,
Geomorphology,
Remote Sensing,
USGS Science Data Catalog (SDC),
Water Resources,
The U.S. Geological Survey collected low-altitude airborne visual imagery via a multirotor, small unoccupied aircraft system (sUAS) along with Real Time Kinematic (RTK) GPS survey data at Sheep Bridge along the Verde River in Arizona in December 2017. Visual imagery was collected in jpg format and Structure from Motion techniques were applied to the visual imagery to derive a time-specific high-resolution orthomosaic for the study site.
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