RS
mehdi feyzolahpour
Abstract
Drought is the most expensive weather event in the world after hurricanes. Early detection of drought and prediction of its occurrence will reduce costs and save human lives. In this research, in order to evaluate the best index in estimating moisture stress and drought, 8 indices NDVI, NDWI, VCI, SR, ...
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Drought is the most expensive weather event in the world after hurricanes. Early detection of drought and prediction of its occurrence will reduce costs and save human lives. In this research, in order to evaluate the best index in estimating moisture stress and drought, 8 indices NDVI, NDWI, VCI, SR, MSI, SIWSI, NDII and NMI were used and Shadgan Wetland was investigated in the period of 2018 to 2023. LST index was also used to check temperature changes. In order to determine the most suitable index, the Pearson correlation coefficient was estimated between the indices and the effectiveness of each index was shown on the Chadwick scale. Based on this, NDWI, MSI, NMI and LST indices have the highest correlation and based on Chadwick's scale in 5 cases, NDWI and MSI indices have a strong and very strong correlation and there is a strong correlation between these two indices at around 0.99 - It has been established. The correlation between LST and NDWI indices was also negative and was estimated at -0.73. Due to the dominance of semi-arid conditions in the region, vegetation-based indices have a very weak capability in drought estimation, and the correlation between NDVI and NDWI was around 0.05. Therefore, based on this, it can be concluded that in Shadgan wetland, indicators based on humidity and temperature stress have better capabilities in drought estimation than vegetation indicators.
