Integrating and Comparing two Remote Sensing Techniques to Quantify Organic Sediment Volume for a Dam Rehabilitation Project at a Pocono Mountain Lake in the Delaware State Forest, Pennsylvania

Authors: Chad Freed*, Widener University, Ahmed Lachhab, Susquehanna University, Taylor Mantey, University of Pennsylvania
Topics: Remote Sensing, UAS / UAV, Environmental Science
Keywords: Photogrammetry,GPR,sUAV,PIX4D,lake sediments,ArcMap,GIS
Session Type: Poster
Day: 4/4/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: Download


This study was completed on the southern 262 acres (62%) of Pecks Pond in the Delaware State Forest in the Pocono Mountains of Pennsylvania. The purpose of the study was to determine the sediment volume in the southern part of the lake to support a dam rehabilitation project. The sediment provides a depositional record since the 1930’s when Pecks Pond was created for ice production by damming a tributary to the Little Bushkill Creek. This study used a combination of georeferenced Ground Penetrating Radar (GPR) and photogrammetry using a small unmanned aerial vehicle (sUAV). GPR was used on the lake with a boat system to determine bathymetry and sub-lake stratigraphy to spatially locate the elevation of the lake bottom and the underlying bedrock. The difference in the two elevations is the thickness of the sediment layer. Pecks Pond was then drained by the Pennsylvania Department of Conservation and Natural Resources (PA-DCNR) and a photogrammetry survey using a sUAV was immediately completed to determine the elevation of the newly exposed lake bottom. The GPR data was processed by RADAN7 and imported into the ArcMap geographic information system (GIS). The photogrammetry data was processed by PIX4D and the results were also imported into ArcMap. The accuracy of the GPR derived lake bottom elevation and the sUAV derived lake bottom elevation are compared along with the two sediment volume calculations using just the GPR data and an integration of the GPR and sUAV photogrammetry remote sensing techniques.

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