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

Published: 7 March 2023| Version 3 | DOI: 10.17632/w2dzy4r6vb.3
Thuong Tran,


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.



Thu Dau Mot University


Remote Sensing, Agriculture Land Use, Drought


This research is funded by Thu Dau Mot University, Binh Duong Province, Vietnam under grant number DT.21.2-063.