Improving the drought monitoring capability of VHI at the global scale via ensemble indices for various vegetation types from 2001 to 2018

Drought is one of the most complex and harmful natural disasters. A study on the temporal and spatial patterns and the evolution of drought can provide a scientific basis for predicting drought occurrences. Based on a multi-source dataset, we select a suitable control drought indicator for improving...

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Veröffentlicht in:Weather and climate extremes Jg. 35; S. 100412
Hauptverfasser: Zeng, Jingyu, Zhang, Rongrong, Qu, Yanping, Bento, Virgílio A., Zhou, Tao, Lin, Yuehuan, Wu, Xiaoping, Qi, Junyu, Shui, Wei, Wang, Qianfeng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.03.2022
Elsevier
Schlagworte:
Algorithm optimization
Global
Temporal and spatial characteristics
Vegetation drought
Vegetation health index
Vegetation types
Temporal and spatial characteristics
Vegetation types
Vegetation drought
Global
Algorithm optimization
Vegetation health index
ISSN:2212-0947, 2212-0947
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Zusammenfassung:Drought is one of the most complex and harmful natural disasters. A study on the temporal and spatial patterns and the evolution of drought can provide a scientific basis for predicting drought occurrences. Based on a multi-source dataset, we select a suitable control drought indicator for improving the vegetation health index (VHI), optimize its algorithm through Pearson correlation analysis, and compare the VHI performance before and after the improvement for various vegetation types. Results show that (1) the self-calibrated Palmer drought severity index is more suitable than the standardized precipitation evapotranspiration index for improving the VHI; (2) the contribution of the thermal condition index to the VHI in most parts of the world is higher than that of the vegetation condition index; (3) the enhanced VHI significantly improves the detection of vegetation drought; and (4) vegetation drought events occurring in high latitudes tend to worsen, and the response of different vegetation types to drought is significantly different. Our research presents a step forward in improving the effectiveness of the VHI in detecting vegetation drought and thus its application prospects. Furthermore, the response characteristics of various vegetation types to drought are identified, deepening our understanding of vegetation drought, which may help decision-makers and authorities to develop better mitigation and adaptation strategies to reduce losses caused by these events. In most areas of the world, the contribution of TCI to VHI is larger than that of VCI. The newly developed VHIopt presents a significantly improved ability to detect vegetation drought when compared to the standard VHI. Furthermore, its performance in various vegetation types around the world is better than the VHIori. The new enhanced VHIopt is a step forward towards a better applicability prospect and reliability of VHI in drought detection. [Display omitted] •sc-PDSI is more suitable for optimizing VHI on a global scale than SPEI.•VHIopt significantly improves the ability of vegetation drought detection.•There are obvious differences in the response of various types of vegetation to drought.•The contribution of TCI to VHI in most parts of the world is higher than that of VCI.•Our research improves the application prospect of VHI in vegetation drought detection.
ISSN:2212-0947
2212-0947
DOI:10.1016/j.wace.2022.100412