Detecting and mapping drought severity using multi-temporal Landsat data in the uMsinga region of KwaZulu-Natal, South Africa

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.

Keywords:

• Drought
• T-VWSI
• SPI
• Landsat

Acknowledgements

The authors would like to thank the South African Weather Service for providing the meteorological data and the US Geological Survey (USGS) for providing the imagery.

Additional information

Funding

The authors would also like to thank The National Research Foundation for providing funding for the research study. [Grant numbers: 86893 & 127354].