Assessment of Agricultural Drought Monitoring Using Various Indices based on Ground-based and Remote Sensing Data (Case Study:Lake Urima Basin)

Drought is a natural phenomenon that occurs in almost all parts of the world. The effects of this crawling phenomenon are more pronounced in arid and semi-arid areas due to their annual rainfall. In contrast to traditional methods based on meteorological stations observations that focus more on weather drought, the use of remote sensing and satellite imagery as a useful tool for monitoring agricultural drought has been considered. In the present study, the aim of comparing and assessing agricultural drought monitoring in Urmia Lake basin using VCI, VHI, TCI vegetation cover indices during the years 2000 to 2011 is using Madison. For this purpose, the NDVI index was first calculated from the images of Madis during June, July, August and September. Then, by comparing the mean of this index during these months, Shahrivar was selected with the maximum value as the month of the indicator. With regard to the minimum and maximum NDVI index in the months of September 2003 and 2008, VCI, VHI, TCI dash mapping maps were prepared. In order to evaluate the performance of agricultural drought indices, correlation coefficients were calculated for VCI, VHI and TCI profiles with SPI Meteorological Index. The results showed that the remote sensing index had a good accuracy in estimating the spatial and temporal dispersion of agricultural drought, so that the correlation coefficient between the VHI and SPI index was 0.86, which indicates that the index is consistent with the SPI meteorological index.