Geographically adaptive multispectral remote sensing water depth inversion based on BP neural network

Guohua Li; Liyuan Hou; Nan Li; Jiafen Xie; Ruyao Sun; Xintian Wang

doi:10.1117/12.3035538

10 July 2024 Geographically adaptive multispectral remote sensing water depth inversion based on BP neural network

Guohua Li, Liyuan Hou, Nan Li, Jiafen Xie, Ruyao Sun, Xintian Wang

Proceedings Volume 13223, Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024); 132232B (2024) https://doi.org/10.1117/12.3035538
Event: 2024 5th International Conference on Geology, Mapping and Remote Sensing (ICGMRS 2024), 2024, Wuhan, China

Abstract

Remote sensing water depth inversion has the advantages of large-scale comprehensive coverage, based on pixel scale, and uniform spatial distribution. It overcomes the shortcomings of traditional depth measurement methods and compensates for the disadvantages of traditional measurements in terms of uncontinuous, multi-point, and real-time measurement of vast water areas. This paper proposes a technique for geographically adaptive multispectral remote sensing water depth inversion based on BP neural networks, and tests it using data from Resource 1 satellite (02E) to Gaoya Reservoir in Shandong Province. The results show that the error in elevation is ±1.04m, and the error distribution shows randomness.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Guohua Li, Liyuan Hou, Nan Li, Jiafen Xie, Ruyao Sun, and Xintian Wang "Geographically adaptive multispectral remote sensing water depth inversion based on BP neural network", Proc. SPIE 13223, Fifth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2024), 132232B (10 July 2024); https://doi.org/10.1117/12.3035538

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