The NASA Ames Stereo Pipeline (ASP) is an open source software of automated geodesy and photogrammetry tools to process satellite, aerial camera, and historical imagery with and without accurate camera pose information using a structure-from-motion (SfM) methodology. ASP is designed to generate topographic digital surface models (DSM). We added to the ASP topographic module a bathymetric module to derive near shore bathymetry using satellite panchromatic bands (PAN), and multispectral bands. The process is semiautomatic and can generate either topographic, bathymetric or topo-bathymetric (TB) seamless 3D point clouds and DSM in the same vertical and horizontal coordinate systems. The bathymetric results depend heavily on the water surface elevation and while previous methods considered the water surface horizontal, our bathymetric module takes into consideration the earth curvature for the considered satellite imagery. A land / water mask can be automatically derived using NIR bands or can be user defined. The new ASP bathymetry module was tested using WorldView-2 panchromatic and green band stereo imagery in Florida Keys (Key West) FL from May 2015. The nearshore PAN and GRN bathymetric results around Key West, FL were validated against bathymetric lidar collected in 2017. The validation errors improve with adding camera calibration and finally alignment to prior topographic lidar data (no bathymetry data used) from 1.0778 m root mean square error (RMSE) to 0.4052 m RMSE to 0.2480 m RMSE, respectively. For PAN bands the depth penetration around Key West was around 4 m with a TB DSM resolution of 1 m. For the same area, using the green (GRN) band the bathymetric validation RMSE in absence of camera adjustment or alignment was 1.1040 m, with camera adjustment RMSE improves to 0.6846 m, and with topographic alignment RMSE is 0.5854. For the green bands the depth penetration in Key West was approximately 7 m with a TB DSM resolution of 2 m.

Recent advances in the quality and availability of lidar permit high spatial resolution in digital elevation models (DEMs). However, large-scale lidar acquisitions may be flown during high tides, storm events, and irregular tidal regimes leading to temporal change differences, but ultimately the uneven penetration through dense vegetation impacts the reality of ground surface positions. For the low-gradient coastal land margin of the northern Gulf of Mexico, even a small elevation bias (on the order of 0.1 m) can adversely affect surface hydrodynamic model accuracy. Therefore, ground-truthing with a vertical elevation adjustment is essential for robust biogeophysical modeling. This study assessed measurement errors of lidar-derived DEM datasets (1 m DEMs), developed in 2021. The DEM was evaluated for distinct coastal wetlands, especially coastal marshes of Louisiana, Mississippi, and Alabama. Error analysis was conducted using Real-Time Kinematic (RTK) GPS to assess how well the lidar-derived elevations represent the actual marsh surface (ground surface). The performance of the temporally and spatially distinct lidar-derived elevation datasets was evaluated over 7,000 elevation points measured between 2011-2021. We also examined the relationship between measurement errors and vegetation characteristics (marsh type, height, and percent cover). This presentation will demonstrate our ongoing efforts to assess the high-resolution lidar-derived elevations in coastal wetlands and discuss the measurement errors.