NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) was launched in September, 2018. The satellite carries a single instrument, ATLAS (Advanced Topographic Laser Altimeter System), a green wavelength, photon-counting lidar, enabling global measurement and monitoring of elevation with a primary focus on the cryosphere. Although bathymetric mapping was not one of the design goals for ATLAS, pre-launch work by our research team showed the potential to map bathymetry with ICESat-2, using data from MABEL (Multiple Altimeter Beam Experimental Lidar), NASA’s high-altitude airborne ATLAS emulator, and adapting the laser-radar equation for ATLAS specific parameters. However, many of the sensor variables were only approximations, which limited a full assessment of the bathymetric mapping capabilities of ICESat-2 during pre-launch studies. Following the successful launch, preliminary analyses of the geolocated photon returns have been conducted for a number of coastal sites, revealing several salient examples of seafloor detection in water depths of up to ~40 m. The geolocated seafloor photon returns cannot be taken as bathymetric measurements, however, since the algorithm used to generate them is not designed to account for the refraction that occurs at the air–water interface or the corresponding change in the speed of light in the water column. This paper presents the first early on-orbit validation of ICESat-2 bathymetry and quantification of the bathymetric mapping performance of ATLAS using data acquired over St. Thomas, U.S. Virgin Islands. A refraction correction, developed and tested in this work, is applied, after which the ICESat-2 bathymetry is compared against high-accuracy airborne topo-bathymetric lidar reference data collected by the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA). The results show agreement to within 0.43—0.60 m root mean square error (RMSE) over 1 m grid resolution for these early on-orbit data. Refraction-corrected bottom return photons are then inspected for four coastal locations around the globe in relation to Visible Infrared Imaging Radiometer Suite (VIIRS) Kd(490) data to empirically determine the maximum depth mapping capability of ATLAS as a function of water clarity. It is demonstrated that ATLAS has a maximum depth mapping capability of nearly 1 Secchi in depth for water depths up to 38 m and Kd(490) in the range of 0.05–0.12 m−1. Collectively, these results indicate the great potential for bathymetric mapping with ICESat-2, offering a promising new tool to assist in filling the global void in nearshore bathymetry.
Abstract:In 2018, the National Aeronautics and Space Administration (NASA) is scheduled to launch the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2), with a new six-beam, green-wavelength, photon-counting lidar system, Advanced Topographic Laser Altimeter System (ATLAS). The primary objectives of the ICESat-2 mission are to measure ice-sheet elevations, sea-ice thickness, and global biomass. However, if bathymetry can be reliably retrieved from ATLAS data, this could assist in addressing a key data need in many coastal and inland water body areas, including areas that are poorly-mapped and/or difficult to access. Additionally, ATLAS-derived bathymetry could be used to constrain bathymetry derived from complementary data, such as passive, multispectral imagery and synthetic aperture radar (SAR). As an important first step in evaluating the ability to map bathymetry from ATLAS, this study involves a detailed assessment of bathymetry from the Multiple Altimeter Beam Experimental Lidar (MABEL), NASA's airborne ICESat-2 simulator, flown on the Earth Resources 2 (ER-2) high-altitude aircraft. An interactive, web interface, MABEL Viewer, was developed and used to identify bottom returns in Keweenaw Bay, Lake Superior. After applying corrections for refraction and channel-specific elevation biases, MABEL bathymetry was compared against National Oceanic and Atmospheric Administration (NOAA) data acquired two years earlier.The results indicate that MABEL reliably detected bathymetry in depths of up to 8 m, with a root mean square (RMS) difference of 0.7 m, with respect to the reference data. Additionally, a version of the lidar equation was developed for predicting bottom-return signal levels in MABEL and tested using the Keweenaw Bay data. Future work will entail extending these results to ATLAS, as the technical specifications of the sensor become available.
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