Investigation of agricultural drought time series in Darab city using remote sensing and Google Earth engine system

Drought Hazard is one of the natural features of the planet that can occur in all climatic zones. This study aimed to analyze the time series of agricultural drought in Darab city over 20 years (2000 – 2020) using remote sensing and satellite images in the Google Earth engine system. Satellite imagery includes 460 images of land surface temperature (LST) and vegetation (NDVI) MODIS satellites are Terra which are used to calculate the temperature condition index (TCI) and vegetation condition index (VCI) was used. Also, using the recorded rainfall data of the Darab synoptic station, the SPI index was calculated by MATLAB software in different time intervals. The results show that according to the Extreme dryness class and based on the TCI index of the 2000 year with an area of 225.46 square kilometers and also according to the VCI index of the 2013 year with an area of 280.80 square kilometers, They had the most land area in Darab city. As a result, comparing the numerical value of SPI index for each of the years of the period under study with the amount of non-drought areas obtained from TCI and VCI indices obtained from satellite images, The highest correlation coefficient of 0.76 was observed between the 12-month SPI and the VCI index, which indicates the VCI satellite index as the optimal index indicating the drought situation in Darab city. Another outstanding result of the present study is that the use of remote sensing data and Google Earth Engine system to monitor and investigate drought in areas that do not have observational data from land surveys is very useful.