Future research and potential measurement of flood risk in Tehran using SVM vector support machine algorithm

Subject Areas : Climatology

pooya Amiri ¹ (PhD Student in Geography, Urban Planning, Larestan University, Iran, Shiraz)
Mohammad ibrahi Afifi ² (Assistant Professor of Geography, Larestan Branch, Islamic Azad University, Larestan Iran)
marzieh Mogholi ³ (Associate Professor, Department of Geography, Larestan Branch, Islamic Azad University, Larestan, Iran)

Received: 2020-09-17 Accepted : 2021-07-19 Published : 2022-03-21

Keywords: Flood, Tehran, Futurology, Vector Support Machine Algorithm,

Abstract :

Future research involves a set of endeavors that visualize potential futures and plan for them by searching for resources, patterns, and factors of change or stability. Future research reflects how the reality of "tomorrow" is born from the change (or stability) of "today." The increasing trend of floods in recent years indicates that most parts of the country are exposed to destructive floods and the extent of flood damage and loss of life and property has increased. The purpose of this study was to predict the future of floods in Tehran using the svm vector support machine algorithm. The research method is spatial analysis. The data used were prepared in the form of information layers. The criteria used were altitude, slope, direction of slope, land use, distance from the road, distance from the waterway, geology. The IGR index was obtained for 7 effective factors selected for the occurrence of surface floods in the study area to evaluate the predictive ability of the model. The results showed that the weight of geological factors, altitude, land use, slope, slope direction, distance from the road, distance from the river were 0.029, 0.026, 0.025, 0.019, 0.015, 0.009, 0.008, respectively, with the highest values. 0.029 was assigned to the geological factor and 0.008 to the distance from the river. The final zoning map showed that the high susceptibility class to flooding was in the range of 40.63% and the very low sensitivity class was 3.55% in the lowest area.

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