Agricultural Drought in the Vietnamese Central Highlands at 1-km Resolution: Monthly and Annual Datasets

The iMDI synthesizes the moisture deficits, soil thermal stress, and vegetation growth status in drought processes and makes it favorable for comprehensive agricultural drought monitoring. The combination of three proposed indices (i.e., VCI, TCI, and ESI) provides more accurate and comprehensive information on drought severity in connection to local conditions. The feasibility of the iMDI is also proved in the correlation with ground-based drought data in the study area. At present, the products include monthly and annual per-pixel drought with 1 km spatial resolution, covering the period of 2001–2020. The data are provided as a global mosaic in geographic lat/long projection in GeoTIFF file format. There are two types of data, such as raw files and legend files, that users can use for their studies. The raw data showed the original values for each pixel, which can be used with different models or algorithms. The legend files showed the different types of drought classification that can be used for attribute analysis: 1-extreme drought, 2-severe drought, 3-moderate drought, 4-near drought, and 5-no drought. Also, the VCI, TCI, and ESI datasets are included so that users can use them for their own needs, even though these datasets can be obtained directly from GEE or other sources.
For more details on the computation and application of the iMDI, please see: Tran, T. V., Bruce, D., Huang, C. Y., Tran, D. X., Myint, S. W., & Nguyen, D. B. (2023). Decadal assessment of agricultural drought in the context of land use land cover change using MODIS multivariate spectral index time-series data. GIScience & Remote Sensing, 60(1), 2163070. https://doi.org/10.1080/15481603.2022.2163070.

综合多变量干旱指数（iMDI）可综合干旱过程中的水分亏缺、土壤热胁迫与植被生长状况，为全面开展农业干旱监测提供有力支撑。所提出的三类指数（即植被状况指数（Vegetation Condition Index, VCI）、温度状况指数（Temperature Condition Index, TCI）与环境胁迫指数（Environmental Stress Index, ESI））相结合，能够结合局地实际情况，提供更为精准且全面的干旱严重程度信息。本研究通过与研究区内地面干旱观测数据的相关性分析，验证了iMDI的可行性。

目前该数据集产品包含空间分辨率为1千米的逐像素月度与年度干旱数据，时间覆盖范围为2001年至2020年。数据采用地理经纬度投影，以全球镶嵌GeoTIFF文件格式进行存储与分发。该数据集包含两类文件，即原始数据文件与分类说明文件，可供用户开展相关科研工作使用。原始数据文件存储了各像素的原始数值，可适配各类模型与算法的调用需求。分类说明文件包含不同等级的干旱分类结果，可用于属性分析：1为极端干旱、2为重度干旱、3为中度干旱、4为近旱、5为无干旱。

此外，数据集还包含VCI、TCI与ESI三类指数数据，可供用户根据自身需求使用——尽管此类数据也可直接从谷歌地球引擎（Google Earth Engine, GEE）或其他数据源获取。

若需了解iMDI的计算方法与应用细节，请参阅以下文献：Tran, T. V., Bruce, D., Huang, C. Y., Tran, D. X., Myint, S. W., & Nguyen, D. B. (2023). Decadal assessment of agricultural drought in the context of land use land cover change using MODIS multivariate spectral index time-series data. GIScience & Remote Sensing, 60(1), 2163070. https://doi.org/10.1080/15481603.2022.2163070.