A Scalable, Cloud‐Based Workflow for Spectrally‐Attributed ICESat‐2 Bathymetry With Application to Benthic Habitat Mapping Using Deep Learning

Abstract Since the 2018 launch of NASA's ICESat‐2 satellite, numerous studies have documented the bathymetric measurement capabilities of the space‐based laser altimeter. However, a commonly identified limitation of ICESat‐2 bathymetric point clouds is that they lack accompanying spectral reflectanc...

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Bibliografske podrobnosti

Principais autores:	Forrest Corcoran, Christopher E. Parrish, Lori A. Magruder, J. P. Swinski
Format:	Artigo
Jezik:	Inglês
Izdano:	American Geophysical Union (AGU) 2024-11-01
Serija:	Earth and Space Science
Teme:	ICESat‐2 cloud computing bathymetry benthic habitats data fusion deep learning
Online dostop:	https://doi.org/10.1029/2024EA003735
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