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GLDD Coastal & Dredging Laboratory

Texas A&M University College of Engineering

Detecting Changes of Wetland Boundaries by Applying Particle Image Velocimetry to UAS Orthoimagery in Galveston Bay, Texas

Soo Bum Bae, Jin Young Kim, ChiHsiang Huang, Yao Li, Fangzhou Tong, Shuai Zhang, Kuang-An Chang, Jens Figlus, Huilin Gao, James Michael Kaihatu, Scott A Socolofsky

Detecting Changes of Wetland Boundaries by Applying Particle Image Velocimetry to UAS Orthoimagery in Galveston Bay, Texas

December 2022

Unmanned Aerial System (UAS) orthoimagery based on Structure-from-Motion (SfM) has recently gained popular demand in environmental and agricultural studies for its high-spatial resolution and cost-effectiveness. The accuracy of the UAS terrestrial surveys is achieved by direct georeferencing with GPS correction technology (e.g., Post-Processed Kinematic, PPK) and further improved when coupled with ground control points (GCPs). However, the installation of GCPs on-site limits the effectiveness in both time and human resources. This study proposes a new positional correction method that overlays multiple surveys of UAS orthomaps to estimate temporal shoreline changes of wetlands using image cross-correlation, as implemented in common Particle Image Velocimetry (PIV) software. PIV provides spatially variable imaged displacement information needed to optimally match image regions between two subsequent surveys.

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