Drought detection in semi-arid regions using remote sensing of vegetation indices and drought indices

Abstract

Drought is a serious climatic condition that affects nearly all climatic zones worldwide, with semi-arid regions being especially susceptible to drought conditions because of their low annual precipitation and sensitivity to climate changes. Drought indices such as the Standardized Precipitation Index (SPI) have been developed for quantifying drought conditions. Usually, calculation of drought indices requires a long record of climatic data, which may not be available because of the inaccessibility of a region and a lack of human activity. Remote sensing of semi-arid vegetation can provide vegetation indices which can be used to link drought conditions when correlated with various drought indices. Spectral reflectance measurements of creosote and black gramma grass were taken between January and November 2003 in the Sevilleta National Wildlife Refuge of New Mexico and various vegetation indices were derived. Each vegetation index was correlated with the SPI of various weekly timescales at varying time-lag intervals calculated from 1999 to seek the best vegetation index that can be used as the best indicator of SPI conditions. The results show a strong linear correlation between the vegetation indices NDVI, Greenness Index, ARVI and drought index SPI at various SPI measurements with various lag times