Evaluation of the applicability of multiple remote sensing drought indices for monitoring of dry and wet in southwest China

Xiehui Li; Hejia Jia; Chu Meng; Huashu Liu; Ying Yao; Boer Xia

doi:10.1117/12.3007538

30 August 2023 Evaluation of the applicability of multiple remote sensing drought indices for monitoring of dry and wet in southwest China

Xiehui Li, Hejia Jia, Chu Meng, Huashu Liu, Ying Yao, Boer Xia

Author Affiliations +

Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 1279726 (2023) https://doi.org/10.1117/12.3007538
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China

Abstract

In this paper, four historical cases of severe drought in different seasons were chosen based on multi-source remote sensing data. Several remote sensing-based drought indices were calculated, and the conditions were uniformly divided into dry and wet based on the drought indices by using ArcGIS technology. The monitoring results using several remote sensing-based drought indices for the four cases were compared against those using SPEI and MCI that were calculated based on measurements at meteorological stations. In this way, the suitability of several remote sensing-based drought indices was assessed for drought monitoring in Southwest China. The results show that no single remote sensing-based drought index can accurately monitor the dry and wet characteristics of the Southwest China with complex topography and diverse climate types, and all of them have certain shortcomings and need to be further improved subsequently.

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

Citation Download Citation

Xiehui Li, Hejia Jia, Chu Meng, Huashu Liu, Ying Yao, and Boer Xia "Evaluation of the applicability of multiple remote sensing drought indices for monitoring of dry and wet in southwest China", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 1279726 (30 August 2023); https://doi.org/10.1117/12.3007538

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