ANALYSIS OF DROUGHT DYNAMICS BASED ON MODIS DATA AND THE HURST INDEX
DOI:
https://doi.org/10.47390/TS3030-3702V3I1Y2025N01Keywords:
drought forecasting, MODIS, Hurst index, NDVI, LST, Vegetation Health Index (VHI), R/S analysisAbstract
Monitoring and forecasting droughts are crucial for mitigating the impacts of climate change on water resources and agriculture. This review summarizes modern methods for analyzing and predicting drought dynamics using MODIS (Moderate Resolution Imaging Spectroradiometer) data and the Hurst index. The advantages and limitations of MODIS-based indices (NDVI, LST, VHI) and the application of the rescaled range (R/S) method for assessing drought persistence are discussed. Special attention is given to the combination of remote sensing and statistical analysis techniques to improve early warning systems. Challenges such as data heterogeneity and regional variations are also addressed, along with future directions, including the use of machine learning and high-resolution data.
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