Remote sensing-based monitoring of the spatiotemporal characteristics of drought using hydro-meteorological indices

Abstract

Due to climate change, drought events will probably occur more frequently and be more intense. Therefore, effective drought monitoring and assessment is vital in developing knowledge of drought, drought adaptation, and mitigatory actions. Remote sensing has been widely used for monitoring drought in recent years. In the current research, three groups of remote sensing indices, i.e. vegetation, thermal and moisture indices, were applied to determine the correlation between them and the standardized precipitation index (SPI) as drought index for the growing season (April to September) from 1999 to 2005 for rangeland areas in the Alborz province of Iran. The results indicated that normalized difference vegetation index (NDVI) (with a correlation coefficient of 0.74) and land surface temperature (LST) (with a correlation coefficient of 0.67) had the highest correlations with rainfall. Therefore, it concluded that the assumed indices are suitable for drought monitoring for this land use. Temporal analysis of the results showed that the best correlations of remote sensing indices belonged to the 6- and 9-month SPI and indicated the effect of long-term rainfall on plant growth.

Keywords

• correlation analysis
• spi
• ndvi
• lst