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Diffuse Attenuation Coefficient (Kd) from ICESat-2 ATLAS Spaceborne Lidar Using Random-Forest Regression
被引:11
|作者:
Corcoran, Forrest
[1
]
Parrish, Christopher E.
[1
]
机构:
[1] Oregon State Univ, Sch Civil & Construct Engn, Corvallis, OR 97331 USA
来源:
关键词:
OCEAN SUBSURFACE;
BATHYMETRY;
VEGETATION;
RETRIEVAL;
TURBIDITY;
DEPTH;
LIGHT;
COLOR;
D O I:
10.14358/PERS.21-00013R2
中图分类号:
P9 [自然地理学];
学科分类号:
0705 ;
070501 ;
摘要:
This study investigates a new method for measuring water turbidity-specifically, the diffuse attenuation coefficient of downwelling irradiance K-d-using data from a spaceborne, green-wavelength lidar aboard the National Aeronautics and Space Administration's ICESat-2 satellite. The method enables us to fill nearshore data voids in existing K-d data sets and provides a more direct measurement approach than methods based on passive multispectral satellite imagery. Furthermore, in contrast to other lidar-based methods, it does not rely on extensive signal processing or the availability of the system impulse response function, and it is designed to be applied globally rather than at a specific geographic location. The model was tested using K-d measurements from the National Oceanic and Atmospheric Administration's Visible Infrared Imaging Radiometer Suite sensor at 94 coastal sites spanning the globe, with K-d values ranging from 0.05 to 3.6 m(-1). The results demonstrate the efficacy of the approach and serve as a benchmark for future machine-learning regression studies of turbidity using ICESat-2.
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页码:831 / 840
页数:10
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