An improved global vegetation health index dataset in detecting vegetation drought

• Published in: Scientific data Vol. 10; no. 1; p. 338
• Main Authors: Zeng, Jingyu, Zhou, Tao, Qu, Yanping, Bento, Virgílio A, Qi, Junyu, Xu, Yixin, Li, Ying, Wang, Qianfeng
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 31.05.2023; Nature Publishing Group UK; Nature Portfolio
• Subjects: Agricultural production; Data Descriptor; Datasets; Drought; Global warming; Soil moisture; Vegetation; Wildfires
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-023-02255-3

Due to global warming, drought events have become more frequent, which resulted in aggravated crop failures, food shortage, larger and more energetic wildfires, and have seriously affected socio-economic development and agricultural production. In this study, a global long-term (1981-2021), high-resolution (4 km) improved vegetation health index (VHI) dataset integrating climate, vegetation and soil moisture was developed. Based on drought records from the Emergency Event Database, we compared the detection efficiency of the VHI before and after its improvement in the occurrence and scope of observed drought events. The global drought detection efficiency of the improved high-resolution VHI dataset reached values as high as 85%, which is 14% higher than the original VHI dataset. The improved VHI dataset was also more sensitive to mild droughts and more accurate regarding the extent of droughts. This improved dataset can play an important role in long-term drought monitoring but also has the potential to assess the impact of drought on the agricultural, forestry, ecological and environmental sectors.