Grassland vegetation parameters estimation using UAV hyperspectral data

Xiaohua Zhu; Xinyu Chen; Lingling Ma; Guangzhou Ouyang

doi:10.1117/12.2679246

17 October 2023 Grassland vegetation parameters estimation using UAV hyperspectral data

Xiaohua Zhu, Xinyu Chen, Lingling Ma, Guangzhou Ouyang

Author Affiliations +

Proceedings Volume 12727, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV; 1272715 (2023) https://doi.org/10.1117/12.2679246
Event: SPIE Remote Sensing, 2023, Amsterdam, Netherlands

Abstract

In this paper, an approach for joint estimation of grassland LAI and Cab from unmanned aerial vehicle (UAV) hyperspectral data was proposed. Firstly, based on PROSAIL (PROSPECT+SAIL) model, 15 typical hyperspectral VIs were simulated and analyzed to identify optimal VIs for LAI and Cab estimation. Secondly, three different combinations of VIs were tested in the construction of LAI and Cab inversion matrices. Thirdly, 3-layer 2-dimension VIs matrix was generated to determine the relationship between VIs and LAI values and Cab values. Finally, LAI and Cab were joint retrieved according to the cells of VIs matrix.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaohua Zhu, Xinyu Chen, Lingling Ma, and Guangzhou Ouyang "Grassland vegetation parameters estimation using UAV hyperspectral data", Proc. SPIE 12727, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV, 1272715 (17 October 2023); https://doi.org/10.1117/12.2679246

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