Zoning of Drought by Integrating Satellite Imagery and Ground–Based Climate Data (Case study: Malayer Plain)

One of the most important consequences of drought is reducing the amount of vegetation. Reducing vegetation and environmental conditions lead various problems such as soil erosion, increased runoff levels and flood risk. Accordingly, evaluation of the effects of drought on vegetation has a great importance. The purpose of this study is to use the Drought Effect Index (IDI), remotely sensed data and terrestrial data in the study area.

The IDI index indicates the long-term effects of climate conditions in the study area on the vegetation cover in area. In this study, the IDI index combines data of the meteorological stations of Malayer Plain to prepare rainfall and temperature maps (information from 5 synoptic stations inside and outside of study area with a 19-years scale) and a series of Landsat TM satellites and ETM + were calculated for the NDVI vegetation mapping (including 6 images in May and 2000, 2002, 2007, 2009, 2013 and 2015). The zonation map was prepared based on this information. This investigation has been done in May 2019.

The results showed that there is a meaningful correlation between aggregate data (IDI) and SPI index, indicates the efficiency of combined data. Results of Pearson correlation showed that there is a significant correlation between the mean SPI and IDI of 0.963 at a significant level of P<0.01.

So far, land and satellite data have been widely used for the study of droughts, but the index derived from the integration of these data has received little attention from researchers, so the aim and innovation of this research is to make it possible to use drought impact index (IDI). Combine terrestrial and satellite data in the study area.