Detecting And Mapping Drought Severity Using Multitemporal Landsat Data In The Umsinga Region Of Kwazulunatal South Africa Shenelle Lottering Paramu Mafongoya Romano Lottering by Shenelle Lottering & Paramu Mafongoya & Romano Lottering instant download after payment.

Geocarto International, 2020. doi: 10.1080/10106049.2020.1783580
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.