Topographic and multispectral reflectance products, aerial imagery, ground spectra, vegetation, and associated GPS data collected during uncrewed aircraft system operations - Dog Head Marsh at South Cape Beach, Mashpee, MA, October 7-8, 2021

The purpose of this field data collection was to test and compare the OceanInsight HDX Mini Spectrometer as an accessible alternative against the more expensive ASD Fieldspec for collecting ground-based hyperspectral reflectance profiles for landcover analysis.  The data collection took place in Dog Head Marsh and South Cape Beach within the Waquoit Bay National Estuarine Research Reserve (WBNERR).  The hyperspectral profiles were collected side-by-side with both field-spectrometers using comparable sensor collection settings for various ground cover samples.  The terrain and vegetation type of these sample were described as well as surveyed using Real Time Kinematic Global Positioning System.  This data was collected within a 4-hour window around solar noon on October 7th, 2021.  Low altitude (82 m above ground level) true-color and multispectral aerial images were collected over the marsh within the same 4-hour window surrounding solar noon to generate photogrammetric products (e.g. digital surface model (DSM), true-color and multispectral reflectance orthomosaics) for further comparison and application with the ground hyperspectral reflectance data, particularly for mapping the invasive marsh reed Phragmites australis. A 3DR SOLO uncrewed aircraft system was equipped in succession with a Ricoh GRII true-color RGB camera and a MicaSense Rededge-3 multispectral camera to collect images with sufficient overlap for photogrammetric processing. Ground control points (GCPs), black and white targets visible in the imagery, were deployed prior to imagery collection to improve the horizontal and vertical accuracy of the DEM, orthomosaic, and reflectance products. GCP locations are recorded using wifi-enabled or survey-collected RTK-GPS information. An additional landcover survey was conducted on October 8th, 2021 to record terrain and vegetation type and RTK-GPS position for randomly selected points throughout the field area to provide a ground-reference dataset for training and validation for machine learning imagery analysis. This data release includes the following data: (1) original images from the Ricoh GRII and MicaSense Rededge-3 cameras as well as (2) the GCPs needed to produce accurate photogrammetry products, (3) ground-reference data, (4) spectral reflectance profiles including GPS locations, and (5) topographic and reflectance products, including DSMs from both imagery datasets, a true-color orthomosaic and a multispectral reflectance orthomosaic.