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 and projected to a local coordinate system for each site. Visible color (Vis-C) imagery was collected with a Ricoh GRII as a single band. Multispectral (MS) imagery was collected with a MicaSense RedEdge 3 as five co-located bands: blue (B; approximately 475-500 nanometers [nm]), green (G; 550-560 nm), red (R; 660-670 nm), red-edge (710-720 nm), and near infrared (NIR; 820-860 nm). Thermal-infrared (TIR) data were collected using a FLIR Vue Pro R 640 camera with an uncooled vanadium oxide microbolometer and a 13-mm lens. Images were collected at 2-second intervals, with a flight speed of 9 meters per second (m/s), 7 m/s, or 5 m/s (visible, multispectral, thermal, respectively) with approximately 75% overlap between sequential images and 70% sidelap between adjacent flight lines. Cameras used local time for visible and thermal imagery collection but Coordinated Universal Time (UTC) for multispectral imagery collection. Photogrammetry to integrate the individual images into an orthophoto and digital surface model (for visible imagery) was done using Agisoft Metashape.

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 and projected to a local coordinate system for each site. Visible color (Vis-C) imagery was collected with a Ricoh GRII as a single band. Multispectral (MS) imagery was collected with a MicaSense RedEdge 3 as five co-located bands: blue (B; approximately 475-500 nanometers [nm]), green (G; 550-560 nm), red (R; 660-670 nm), red-edge (710-720 nm), and near infrared (NIR; 820-860 nm). Thermal-infrared (TIR) data were collected using a FLIR Vue Pro R 640 camera with an uncooled vanadium oxide microbolometer and a 13-mm lens. Images were collected at 2-second intervals, with a flight speed of 9 meters per second (m/s), 7 m/s, or 5 m/s (visible, multispectral, thermal, respectively) with approximately 75% overlap between sequential images and 70% sidelap between adjacent flight lines. Cameras used local time for visible and thermal imagery collection but Coordinated Universal Time (UTC) for multispectral imagery collection. Photogrammetry to integrate the individual images into an orthophoto and digital surface model (for visible imagery) was done using Agisoft Metashape.

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 and projected to a local coordinate system for each site. Visible color (Vis-C) imagery was collected with a Ricoh GRII as a single band. Multispectral (MS) imagery was collected with a MicaSense RedEdge 3 as five co-located bands: blue (B; approximately 475-500 nanometers [nm]), green (G; 550-560 nm), red (R; 660-670 nm), red-edge (710-720 nm), and near infrared (NIR; 820-860 nm). Thermal-infrared (TIR) data were collected using a FLIR Vue Pro R 640 camera with an uncooled vanadium oxide microbolometer and a 13-mm lens. Images were collected at 2-second intervals, with a flight speed of 9 meters per second (m/s), 7 m/s, or 5 m/s (visible, multispectral, thermal, respectively) with approximately 75% overlap between sequential images and 70% sidelap between adjacent flight lines. Cameras used local time for visible and thermal imagery collection but Coordinated Universal Time (UTC) for multispectral imagery collection. Photogrammetry to integrate the individual images into an orthophoto and digital surface model (for visible imagery) was done using Agisoft Metashape.

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 and projected to a local coordinate system for each site. Visible color (Vis-C) imagery was collected with a Ricoh GRII as a single band. Multispectral (MS) imagery was collected with a MicaSense RedEdge 3 as five co-located bands: blue (B; approximately 475-500 nanometers [nm]), green (G; 550-560 nm), red (R; 660-670 nm), red-edge (710-720 nm), and near infrared (NIR; 820-860 nm). Thermal-infrared (TIR) data were collected using a FLIR Vue Pro R 640 camera with an uncooled vanadium oxide microbolometer and a 13-mm lens. Images were collected at 2-second intervals, with a flight speed of 9 meters per second (m/s), 7 m/s, or 5 m/s (visible, multispectral, thermal, respectively) with approximately 75% overlap between sequential images and 70% sidelap between adjacent flight lines. Cameras used local time for visible and thermal imagery collection but Coordinated Universal Time (UTC) for multispectral imagery collection. Photogrammetry to integrate the individual images into an orthophoto and digital surface model (for visible imagery) was done using Agisoft Metashape.

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 and projected to a local coordinate system for each site. Visible color (Vis-C) imagery was collected with a Ricoh GRII as a single band. Multispectral (MS) imagery was collected with a MicaSense RedEdge 3 as five co-located bands: blue (B; approximately 475-500 nanometers [nm]), green (G; 550-560 nm), red (R; 660-670 nm), red-edge (710-720 nm), and near infrared (NIR; 820-860 nm). Images were collected at 2-second intervals, with a flight speed of 9 meters per second (m/s) or 7 m/s (visible and multispectral, respectively) with approximately 75% overlap between sequential images and 70% sidelap between adjacent flight lines. Cameras used local time for visible and thermal imagery collection but Coordinated Universal Time (UTC) for multispectral imagery collection. Photogrammetry to integrate the individual images into an orthophoto and digital surface model (for visible imagery) was done using Agisoft Metashape.

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 and projected to a local coordinate system for each site. Visible color (Vis-C) imagery was collected with a Ricoh GRII as a single band. Images were collected at 2-second intervals, with a flight speed of 9 meters per second (m/s) and with approximately 75% overlap between sequential images and 70% sidelap between adjacent flight lines. Cameras used local time for visible and thermal imagery collection but Coordinated Universal Time (UTC) for multispectral imagery collection. Photogrammetry to integrate the individual images into an orthophoto and digital surface model (for visible imagery) was done using Agisoft Metashape.

The University of Connecticut and the U.S. Geological Survey (USGS) collected low-altitude (30-50 m above ground level) airborne visible-light imagery data via a quadcopter, small unoccupied aircraft system (UAS or ‘drone’) deployed along two tributary confluence locations within the Housatonic River: Mill Brook (latitude: 42°52’18” N, longitude: 73°21’48” W) and Furnace Brook (latitude: 41°49’16” N, longitude: 73°22’17” W). Both tributary confluence sites serve as critical summer thermal refuge for cold water-adapted poikilotherms. The objectives for this data collection included the creation of high-resolution orthomosaic images of the two tributary confluences to infer bank and instream structures and mixing processes at the tributary confluences. Detailed site-scale maps such as these are important tools for managers and researchers aiming to protect and conserve populations at risk. The UAS (Mavic 2 Zoom, DJI Enterprises) was flown several times per day, at wind speeds below 10 mph, capturing RGB imagery from March 24-25, 2021. The UAV flights collected single RGB JPG images at 30-50m above ground level using the double-grid flight pattern on the third-party app Pix4D Capture (https://www.pix4d.com/product/pix4dcapture). The images were stitched automatically into several orthomosaic images using Agisoft Metashape (Agisoft LLC, St. Petersburg, Russia) software as described in the ‘processed_data’ subfolders of this data release. Structure from Motion techniques were also applied to the visual imagery to derive time-specific, digital surface models (DSM) of the exposed banks and some subsurface features.

This dataset provides NASA AirSWOT Ka-band (35.75 GHz) radar interferometry data products for water surface elevation (WSE), a derived color-infrared (CIR) digital image orthomosaic, and derived lake/wetland and river channel water masks at 3.6 x 3.6 m resolution for a study area of ~3,300 km2 in the Yukon Flats Basin (YFB) in eastern interior Alaska. The data were collected during a flight over the region on June 15, 2015.These data were collected to validate AirSWOT WSE mappings and to improve the understanding of surface water flow through complex Arctic-Boreal wetland systems.

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 (41°54'17.6"N 70°34'17.4"W), where a comprehensive stream and wetland restoration was performed. Wetland restoration actions at Tidmarsh Farms were made possible by a landowner decision to enroll in the U.S. Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) Wetland Reserve Easement Program. The Massachusetts Department of Fish and Game’s Division of Ecological Restoration (MDER) later became the lead manager for the design, permitting, and implementation of stream and wetland restoration actions on the site. In 2017, after the completion of the largest freshwater wetland restoration in Massachusetts to date, the property was purchased by the Massachusetts Audubon Society who in 2018 opened the Tidmarsh Wildlife Sanctuary to the public.

This data set contains ortho-rectified mosaic tiles, created as a product from the NOAA Integrated Ocean and Coastal Mapping (IOCM) initiative. The source imagery was acquired from 20160911 - 20160924 with an Applanix Digital Sensor System (DSS). The original images were acquired at a higher resolution to support the final ortho-rectified mosaic.