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Deriving High-Resolution Reservoir Bathymetry from ICESat-2 Prototype Photon-Counting Lidar and Landsat ImageryKnowledge of reservoir bathymetry is essential for many studies on terrestrial hydrological and biogeochemical processes. However, there are currently no cost-effective approaches to derive reservoir bathymetry at the global scale. This study explores the potential of generating high-resolution global bathymetry using elevation data collected by the 532-nm Advanced Topographic Laser Altimeter System (ATLAS) onboard the Ice, Cloud, and Land Elevation Satellite (ICESat-2). The novel algorithm was developed and tested using the ICESat-2 airborne prototype, the Multiple Altimeter Beam Experimental Lidar (MABEL), with Landsat-based water classifications (from 1982 to 2017). MABEL photon elevations were paired with Landsat water occurrence percentiles to establish the elevation-area (E-A) relationship, which in turn was applied to the percentile image to obtain partial bathymetry over the historic dynamic range of reservoir area. The bathymetry for the central area was projected to achieve the full bathymetry. The bathymetry image was then embedded onto the digital elevation model (DEM). Results were validated over Lake Mead against survey data. Results over four transects show coefficient of determination (R²) values from 0.82 to 0.99 and root-mean-square error (RMSE) values from 1.18 to 2.36 m. In addition, the E-A and elevation-storage (E-S) curves have RMSEs of 1.56 m and 0.08 km³, respectively. Over the entire dynamic reservoir area, the derived bathymetry agrees very well with independent survey data, except for within the highest and lowest percentile bands. With abundant overpassing tracks and high spatial resolution, the newly launched ICESat-2 should enable the derivation of bathymetry over an unprecedented number of reservoirs.
Document ID
20190027119
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
External Source(s)
Authors
Yao Li ORCID
(Texas A&M University College Station, TX, United States)
Huilin Gao ORCID
(Texas A&M University College Station, TX, United States)
Michael F Jasinski
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Shuai Zhang
(University of North Carolina System Chapel Hill, North Carolina, United States)
Jeremy D Stoll
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Date Acquired
July 9, 2019
Publication Date
June 18, 2019
Publication Information
Publication: IEEE Transactions on Geoscience and Remote Sensing
Publisher: Institute of Electrical and Electronics Engineers
Volume: 57
Issue: 10
Issue Publication Date: October 1, 2019
ISSN: 0196-2892
e-ISSN: 1558-0644
URL: https://ieeexplore.ieee.org/document/8738833
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN70381
ISSN: 0196-2892
Report Number: GSFC-E-DAA-TN70381
E-ISSN: 1558-0644
Funding Number(s)
CONTRACT_GRANT: NNG15HQ01C
Distribution Limits
Public
Copyright
Other
Technical Review
Professional Review
Document Inquiry

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