This dataset documents the locations of ground control points associated with images obtained from unmanned aerial systems (UAS) flown in the Cape Cod National Seashore. Most of the ground control points were temporary targets placed by the U.S. Geological Survey field crew, but four were man-made features already in place, and two were points selected a posteriori from preliminary orthophotomosaics. Photographs of the four in-place features are included in this dataset, as are images showing the location of the two a posteriori points at two zoom levels. The locations of these ground control points can be used to constrain photogrammetric reconstructions based on the aerial imagery. The overall objective of the fieldwork was to evaluate the quality and cost of mapping from UAS images. Low-altitude (approximately 120 meters above ground level) digital images were obtained from cameras in a fixed-wing UAS flown from the lawn adjacent to the Coast Guard Beach parking lot on 1 March, 2016. All activities were conducted according to Federal Aviation Administration regulations and under a National Park Service Scientific Research and Collecting Permit, study number CACO-00285, permit number CACO-2016-SCI-003.

This dataset contains the locations of independent survey points acquired on the same day that images were obtained from unmanned aerial systems (UAS) flown in the Cape Cod National Seashore. The overall objective of the field work was to evaluate the quality and cost of mapping from UAS images. Low-altitude (approximately 120 meters above ground level) digital images were obtained from cameras in a fixed-wing unmanned aerial vehicle (UAV) flown from the lawn adjacent to the Coast Guard Beach parking lot on 1 March, 2016. U.S. Geological Survey technicians deployed and mapped 28 targets that appear in some of the images for use as ground control points. All activities were conducted according to Federal Aviation Administration regulations and under a National Park Service Scientific Research and Collecting Permit, study number CACO-00285, permit number CACO-2016-SCI-003. This dataset contains locations of both in place and placed targets that may be used as ground control to constrain photogrammetric reconstructions. One hundred and forty-four (144) points were measured along several cross-shore transects on the beach. These points were measured with real-time differential global positioning system (GPS) and have horizontal and vertical uncertainties of approximately +/ 0.03 m. These points were not used in photogrammetric processing, so they can be used for independent evaluation of photogrammetric products. The independent survey points are listed in file CACO_transect_Points_20160301.csv.

This dataset contains the locations of independent survey points acquired on the same day that images were obtained from unmanned aerial systems (UAS) flown in the Cape Cod National Seashore. The overall objective of the field work was to evaluate the quality and cost of mapping from UAS images. Low-altitude (approximately 120 meters above ground level) digital images were obtained from cameras in a fixed-wing unmanned aerial vehicle (UAV) flown from the lawn adjacent to the Coast Guard Beach parking lot on 1 March, 2016. U.S. Geological Survey technicians deployed and mapped 28 targets that appear in some of the images for use as ground control points. All activities were conducted according to Federal Aviation Administration regulations and under a National Park Service Scientific Research and Collecting Permit, study number CACO-00285, permit number CACO-2016-SCI-003. This dataset contains locations of both in place and placed targets that may be used as ground control to constrain photogrammetric reconstructions. One hundred and forty-four (144) points were measured along several cross-shore transects on the beach. These points were measured with real-time differential global positioning system (GPS) and have horizontal and vertical uncertainties of approximately +/ 0.03 m. These points were not used in photogrammetric processing, so they can be used for independent evaluation of photogrammetric products. The independent survey points are listed in file CACO_transect_Points_20160301.csv.

Low-altitude (30-120 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained with a series of cameras mounted on small unmanned aerial systems (UAS, also known as a drone). Imagery was collected at close to low tide on five days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which were located by using a real-time kinematic global navigation satellite system (RTK-GNSS) base station and rovers. The GCPs can be used as constraints during photogrammetric processing. Transect points were collected by using the same RTK-GNSS system; these can be used to evaluate photogrammetric products. This data release includes georeferenced images, image-location files, GCPs, and transect points. Collection of these data was supported by the U.S. Geological Survey Coastal/Marine Hazards and Resources Program and conducted under U.S. Geological Survey field activity numbers 2016-013-FA, 2016-043-FA, 2016-053-FA, 2016-054-FA and 2016-055-FA.

Low-altitude (30-120 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained with a series of cameras mounted on small unmanned aerial systems (UAS, also known as a drone). Imagery was collected at close to low tide on five days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which were located by using a real-time kinematic global navigation satellite system (RTK-GNSS) base station and rovers. The GCPs can be used as constraints during photogrammetric processing. Transect points were collected by using the same RTK-GNSS system; these can be used to evaluate photogrammetric products. This data release includes georeferenced images, image-location files, GCPs, and transect points. Collection of these data was supported by the U.S. Geological Survey Coastal/Marine Hazards and Resources Program and conducted under U.S. Geological Survey field activity numbers 2016-013-FA, 2016-043-FA, 2016-053-FA, 2016-054-FA and 2016-055-FA.

Low-altitude (80-100 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts were obtained from a camera mounted on a small unmanned aerial system (UAS; also known as a drone). Imagery was collected at close to low tide on seven days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which were located by using a real-time kinematic global navigation satellite system (RTK-GNSS) base station and rovers. The GCPs can be used as constraints during photogrammetric processing. Transect points were collected by using the same RTK-GNSS system; these can be used to evaluate photogrammetric products. This data release includes georeferenced images, image-location files, GCPs, and transect points. Collection of these data was supported by the U.S. Geological Survey Coastal and Marine Geology Program and were conducted under USGS field activity numbers 2017-005-FA, 2017-008-FA, 2017-010-FA, 2017-014-FA, 2017-027-FA, 2017-029-FA, and 2017-050-FA.

Low-altitude (80-100 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts were obtained from a camera mounted on a small unmanned aerial system (UAS; also known as a drone). Imagery was collected at close to low tide on seven days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which were located by using a real-time kinematic global navigation satellite system (RTK-GNSS) base station and rovers. The GCPs can be used as constraints during photogrammetric processing. Transect points were collected by using the same RTK-GNSS system; these can be used to evaluate photogrammetric products. This data release includes georeferenced images, image-location files, GCPs, and transect points. Collection of these data was supported by the U.S. Geological Survey Coastal and Marine Geology Program and were conducted under USGS field activity numbers 2017-005-FA, 2017-008-FA, 2017-010-FA, 2017-014-FA, 2017-027-FA, 2017-029-FA, and 2017-050-FA.

Imagery acquired with unmanned aerial systems (UAS) and coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. These new techniques are particularly useful for data collection of coastal systems, which requires high temporal and spatial resolution datasets. The U.S. Geological Survey worked in collaboration with members of the Marine Biological Laboratory and Woods Hole Analytics at Black Beach, in Falmouth, Massachusetts to explore scientific research demands on UAS technology for topographic and habitat mapping applications. This project explored the application of consumer-grade UAS platforms as a cost-effective alternative to lidar and aerial/satellite imagery to support coastal studies requiring high-resolution elevation or remote sensing data. A small UAS was used to capture low-altitude photographs and GPS devices were used to survey reference points. These data were processed in an SfM workflow to create an elevation point cloud, an orthomosaic image, and a digital elevation model.

Imagery acquired with unmanned aerial systems (UAS) and coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. These new techniques are particularly useful for data collection of coastal systems, which requires high temporal and spatial resolution datasets. The U.S. Geological Survey worked in collaboration with members of the Marine Biological Laboratory and Woods Hole Analytics at Black Beach, in Falmouth, Massachusetts to explore scientific research demands on UAS technology for topographic and habitat mapping applications. This project explored the application of consumer-grade UAS platforms as a cost-effective alternative to lidar and aerial/satellite imagery to support coastal studies requiring high-resolution elevation or remote sensing data. A small UAS was used to capture low-altitude photographs and GPS devices were used to survey reference points. These data were processed in an SfM workflow to create an elevation point cloud, an orthomosaic image, and a digital elevation model.

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated estimates of camera positions and attitudes based on the photogrammetric reconstruction; tables listing locations of the base stations, ground control points, and transect points; geolocated, RGB-colored point clouds; orthomosaic images; and digital elevation models for each of the survey regions. Collection of these data was supported by the Federal Emergency Management Agency, the State of New York Departments of State and Environmental Conservation, and the USGS Coastal and Marine Geology Program and was conducted under USGS field activity number 2017-042-FA.