A new radar vegetation index for research in the dry areas

Wenjing Li; Weicheng Wu; Zhenhao Xu; Sicheng Li; Aohui Li; Xiaoping Song; Lihua Gong; Yaoyao Zhu

doi:10.1117/12.3032225

3 June 2024 A new radar vegetation index for research in the dry areas

Wenjing Li, Weicheng Wu, Zhenhao Xu, Sicheng Li, Aohui Li, Xiaoping Song, Lihua Gong, Yaoyao Zhu

Proceedings Volume 13170, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024); 131700H (2024) https://doi.org/10.1117/12.3032225
Event: Third International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024), 2024, Wuhan, China

Abstract

In view of the insensitivity of the available radar vegetation indices to dryland ecosystems, it is the purpose of this paper to develop a more pertinent new radar vegetation index, i.e., dryland radar vegetation index (DRVI), for land characterization using Sentinel 1 data based on the scattering entropy, scattering angle and cross polarization. After a comparison with the available radar indices and sensitivity analysis versus (vs) the optical remote sensing indices, the new index, DRVI, was found to have a stronger correlation with the optical vegetation indices such as the normalized difference vegetation index (NDVI), generalized difference vegetation index (GDVI), and mining and restoration assessment indices (MRAIs) and a higher sensitivity to dryland biomes than other radar vegetation indices. It is hence concluded that this DRVI has high potential of application in characterizing the dryland ecosystems despite it is derived from the Mu Us Sandy Land, China.

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

Citation Download Citation

Wenjing Li, Weicheng Wu, Zhenhao Xu, Sicheng Li, Aohui Li, Xiaoping Song, Lihua Gong, and Yaoyao Zhu "A new radar vegetation index for research in the dry areas", Proc. SPIE 13170, International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024), 131700H (3 June 2024); https://doi.org/10.1117/12.3032225

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KEYWORDS

Vegetation

Radar

Land cover

Scattering

Synthetic aperture radar

Remote sensing

Biological research

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