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.
RS
mehdi feyzolahpour
Abstract
Spatial and temporal changes of surface water affect the structure and functioning of the ecosystems of the Teham Dam region as well as the agricultural, economic and social development in this region. In this research, MNDWI, AWEI and NDWI indices and SVM support vector machine model was used to detect ...
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Spatial and temporal changes of surface water affect the structure and functioning of the ecosystems of the Teham Dam region as well as the agricultural, economic and social development in this region. In this research, MNDWI, AWEI and NDWI indices and SVM support vector machine model was used to detect the long-term changes of Teham Dam in the period from 2002 to 2023. The results of the AWEI index showed that the area of the dam was about 2.4 square kilometers in 2007, which decreased to 1.15 square kilometers in 2023. In the MNDWI index, in 2007 and 2023, the area of water was equal to 2.6 and 1.17 square kilometers, respectively. The NDWI map shows a 46.38% decrease in the area of the water zone from 2007 to 2023. But in the AWEI index, this decrease was equal to 47.9. AWEI index with kappa values equal to 0.94 has correctly recognized the boundaries of water areas. According to the SVM model, in this period of time, the amount of vegetation has decreased from 0.8 square kilometers in 2002 to 0.07 square kilometers in 2023. The amount of barren land has decreased almost in this period of time and was equal to 4.57 square kilometers in 2023. The maximum temperature of the earth's surface in July 2002 was equal to 38.3 degrees Celsius and in July 2023 it reached 28.4 degrees Celsius.
