This dataset is a time-series of high-resolution visible imagery orthomosaics of the Gothic Townsite area surrounding Rocky Mountain Biological Laboratory, collected by an Uncrewed Aircraft System (UAS, e.g. "drone"). Image data was captured by a 40-megapixel red-green-blue (RGB) camera attached to a quadcopter aircraft flying at 100m above the ground surface. Data has a nominal ground sample distance (pixel resolution) of approximately 1 cm, but has not been resampled from its original resolution to preserve data quality. Image data are stored as JPEG-compressed 8-bit integers in the YCBCR colorspace, so they are most useful in visual interpretation. A high-quality radiometrically calibrated 5-band reflectance dataset including red edge and near-infrared information is also available. Flights were conducted approximately weekly within 3 hours of solar noon, in full-sun conditions where possible. The flights typically take approximately 75 minutes to complete, and flightlines were oriented NNW-SSE at a 28m spacing, starting in the western proportion of the imaging area and progressing east. This means that western parts of the imaging area were typically imaged approximately 1-hour beore the eastern edges. Raw images were captured as 8-bit JPEG files approximately once every 0.6 seconds, providing approximately 85 percent forward overlap and 70 percent side overlap between adjacent images. For densely forested parts of the landscape, the forward speed of the aircraft was reduced to 8 m/sec to increase the forward overlap to 90%, improving orthomosaic performance for complex vegetation. Raw image data was georeferenced and orthorectified in Agisoft Metashape software (version 1.7), using information from the UAS system's Real-time Kinematic (RTK) global satellite navigation system as well as 8-15 ground-control points geolocated to within 2 cm. Independent assessment indicates a geographic precision of approximately 5 cm (Mean Absolute Error).
Items connected by shared entities, co-authorship, citations, or semantic similarity.