Spatial–temporal variations of vegetation and drought severity across Tharparkar, Pakistan, using remote sensing-derived indices

Abstract

Tharparkar is an arid region in the southeastern province of Sindh, Pakistan, and experienced drought as a regular phenomenon in the past. The complex nature of drought and sparsely located network of met stations handicapped reliable spatial and temporal analysis of drought severity across Tharparkar. Freely available tropical rainfall measuring mission rainfall satellite data and moderate-resolution imaging spectroradiometer normalized difference vegetation index (NDVI) satellite data fulfilled this gap and were used to generate drought indices. Commonly used NDVI and NDVI anomalies pose problems when compared with standardized meteorological drought indices such as standardized precipitation index (SPI) and standardized precipitation and evapotranspiration index (SPEI) for drought characterization. This study compared standardized vegetation index (SVI) with traditionally used, i.e., SPI and SPEI, for modeling drought severity in the arid and fragile agro-ecosystem of Tharparkar. SVI significantly correlated with standardized meteorological drought indices (SPI and SPEI) and revealed vegetation dynamics under rainfall and temperature variations. Weighted overlay analysis in geographical information systems depicted an accurate onset of the 2014 drought. This study provides useful information for drought characterization that can be used for drought monitoring and early warning systems in data scarce, arid, and semiarid regions.