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• W3036331608 abstract "Drought has become a more frequent phenomenon under changing climatic conditions, particularly in Sub Saharan Africa. This study tested the utility of a newly proposed Temperature-Vegetation Water Stress Index (T-VWSI) in detecting drought severity using Landsat data for the years 2008, 2012, 2016 and 2018. This index was created using both NDVI and LST to detect drought severity within the region. The results show that the year 2016 experienced the most severe levels of drought, with the northern areas of the uMsinga region being most severely affected. SPI was used to corroborate the findings of the T-VWSI index and also established that the year 2016 was the year of severe drought in uMsinga. The results of this study have illustrated the potential of the T-VWSI index in effectively mapping and detecting drought over large spatial areas." @default.
• W3036331608 created "2020-06-25" @default.
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• W3036331608 date "2020-07-08" @default.
• W3036331608 modified "2023-09-24" @default.
• W3036331608 title "Detecting and mapping drought severity using multi-temporal Landsat data in the uMsinga region of KwaZulu-Natal, South Africa" @default.
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• W3036331608 doi "https://doi.org/10.1080/10106049.2020.1783580" @default.
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