Capability of VCADI, TSDI and TVDI Indices in Estimating the Drought of Agricultural Land in Hesar Village, Mahenshan City
Subject Areas : Application of computer in water and soil issues
1 - Assistant Professor, Department of Geography, University of Zanjan, Zanjan, Iran.
Keywords: Dryness index, TVDI, TSDI, VCADI, Hesar Mahneshan,
Abstract :
Background and Aim: Today, many drought indices have been presented based on the regression relationships of vegetation indices and surface temperature. The purpose of this research is to evaluate the capability of each of the vegetation temperature aridity index (TVDI), vegetation albedo aridity index (VCADI) and modified vegetation soil aridity index (TSDI) in estimating the aridity condition in the Hesar of Mahneshan in the shore of the river Qezelozan.
Method: In this research, the differences and capabilities of 3 aridity indicators on the shore of Qezelozan River in Hesar Mahneshan section were investigated. For this purpose, Landsat 5 and 8 images were used in 1990 and 2023. These indices are based on the regression relations between vegetation, surface temperature and albedo, and a regression relation was established between NDVI, LST, albedo and MSAVI indices, and TVDI, TSDI and VCADI indices were created. Each of these indicators used certain bands and band 6 of Landsat 5 satellite and band 10 of Landsat 8 satellite were used to estimate the earth's surface temperature. Origin 8 software was used to draw the scatter diagram and the corresponding regression equation was obtained. The values of slope and intercept were used to draw the index map. The accuracy of each of these indicators was checked using the Kappa coefficient.
Results: In order to check the drought condition, the studied area is divided into five classess with very low, low, medium, high and very high dryness and it was observed that the area with high dryness in the VCADI index increased from 0.65 km2 in 1990 to 53. 1 square kilometer has increased in 2023 and has reached 23.6% from 10% of the area of the region. This amount has increased from 0.47 and 0.65 km2 to 18.7 and 23.64 percent in the very large area for TSDI and TVDI indicators, respectively.
Conclusion: The results showed that the highest Pearson correlation coefficient of -0.55 was established between LST index and NDVI and occurred in 2023. Based on the drought indices, it was observed that in the VCADI index, the areas with very dry areas increased from 0.65 square kilometers to 1.53 square kilometers and reached 23.6% from 10%. In TSDI and TVDI indices, similar results have been obtained and have reached 23.64 and 18.7 percent in 2023 from 10 and 7.26 percent in 1990, respectively. Based on Pearson's correlation and Kappa coefficient, it was observed that the TVDI index has a better ability to assess drought compared to other indices, and the TSDI index with a correlation coefficient of -0.54% is in the second place in 2023.
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