Elevation models, aerial imagery, LiDAR point clouds (LPCs), vegetation survey, and GPS data collected during uncrewed aircraft systems (UAS) operations at Lower Darby Creek, Darby Township, Pennsylvania, August 28 to September 1, 2023

Two DJI M600 small Uncrewed Aircraft Systems (sUAS) were used to collect aerial remote sensing data over various locations within the Lower Darby Creek Superfund Site and the adjacent John Heinz National Wildlife Refuge (NWR). Datasets included natural (RGB) color images, multispectral images, and LiDAR Point Clouds (LPCs). These data were processed to produce high resolution digital elevation models (DEM) and natural-color and multispectral reflectance image mosaics. Black and white cross-coded ground control points (GCPs) were sureveyed using RTK-GPS and RTK-GPS enabled Aeropoints to georeference the model and orthomosaics during post-processing. The elevation and imagery products were produced to help partners at the EPA and U.S. Fish and Wildlife Service evaluate the baseline conditions of the target sites, with future data collections planned to monitor landscape change from remediation efforts and potential storm impacts. Data was collected over two sites under the Superfund site designation, the Clearview Landfill and the Folcroft Annex. The Folcroft Annex lies within the boundary of the NWR. UAS LiDAR data was collected for these two sites and additional areas of the NWR using a Yellowscan Mapper+ mounted to a DJI Matrice 600 sUAS to generate high density LPCs, which were then processed to create high resolution (5-50 cm) DEMs. Aerial images were collected over the Clearview Landfill and another site within the NWR using both a natural-color RGB Ricoh GRII camera and a 7-band multispectral Micasense Altum-PT camera attached to the second DJI Matrice 600 sUAS. This aerial imagery was flown to achieve sufficient overlap in images for photogrammetric processing using structure-from-motion techniques to generate high resolution (5cm) DEM as well as natural-color and multispectral reflectance orthomosaics.