A monthly 250 m Vegetation Drought Resistance Index (VDRI) dataset for China from 2000 to 2022
Jinyang Wang, Zhenfeng Shao, Peng Fu, Jiahui Chang, Menghao Du, Shuzhe Huang, Zhuohong Li, Fei Yang 等 9 位
Wuhan University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Louisiana State University Louisiana State University Agricultural Center
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Global warming is increasing the frequency and intensity of extreme droughts, threatening terrestrial ecosystem structure and function. However, existing indices often fail to provide a comprehensive representation of the water cycle, and high-resolution datasets for characterizing vegetation responses to drought remain limited. To address this gap, we first developed a monthly Vertical Composite Drought Index (VCDI) by integrating precipitation, surface runoff, soil moisture, and groundwater storage anomalies. This index summarizes multidimensional water constraints across the “atmosphere-surface-subsurface” continuum and captures cumulative effects of drought across multiple timescales. Furthermore, VCDI, land surface temperature, and vegetation greenness were combined to produce a monthly Vegetation Drought Resistance Index (VDRI) dataset for China at 250 m resolution from 2000 to 2022. Multi-source evaluations indicate that VDRI provides spatially detailed and temporally consistent information on vegetation conditions under concurrent hydroclimatic and thermal stress. The datasets support ecosystem assessment, ecological drought monitoring, wildfire risk analysis, and benchmarking for drought-impact studies and related ecological models.
逐年被引趋势
暂无年度引用数据
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
物理Hydrology and Drought Analysis
Plant Water Relations and Carbon Dynamics · Remote Sensing in Agriculture