A method for detecting drought utilizing time series of MODIS surface reflectance imagery
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Author |
Jumpol Itsarawisut, Mehsa Singharath, Tanutdech Rotjanakusol, Natcha Laosuwan and Teerawong Laosuwan
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e-ISSN |
1819-6608 |
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On Pages
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898-903
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Volume No. |
20
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Issue No. |
13
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Issue Date |
October 15, 2025
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DOI |
https://doi.org/10.59018/0725106
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Keywords |
drought, normalized difference vegetation index, vegetation condition index, terra/modis.
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Abstract
Drought monitoring and assessment present significant challenges due to their gradual onset and varying severity, often resulting from regional rainfall imbalances. This research focuses on detecting drought conditions in the Mun River Basin by utilizing a decade-long time series of Terra/MODIS satellite surface reflectance imagery. Specifically, the study employed data from the MOD09A1 product of Terra/MODIS to analyze the Normalized Difference Vegetation Index (NDVI) and the Vegetation Condition Index (VCI). These indices served as key indicators for assessing vegetation health, which reflects drought conditions in the study area. The analysis revealed that the year 2020 experienced the most severe drought, affecting 71.15% of the total area, equivalent to 46,080.679 km². Statistical evaluations of drought and rainfall data over the ten years showed a strong correlation, with a coefficient of determination (R² = 0.8498). These results underscore the effectiveness of VCI as a reliable indicator for identifying and assessing drought across both spatial and temporal dimensions in the Mun River Basin.
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