Volume 2, Issue 4 (11-2021)
Degradation and Rehabilitation of Natural Land 2021, 2(4): 52-67 |
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saraei B, asghari saraskanrud S. Landslide Risk Zoning in the Nakarood Watershed using Fuzzy Logic and Remote Sensing. Degradation and Rehabilitation of Natural Land 2021; 2 (4) :52-67
URL: http://drnl.sanru.ac.ir/article-1-181-en.html
URL: http://drnl.sanru.ac.ir/article-1-181-en.html
Mohaghegh Ardabili University, Ardabil, Iran
Abstract: (779 Views)
Extended Abstract
Abstract: abstNatural crises such as landslides are capable of inflicting irreparable damage on humans and the environment. Therefore, risk assessment is critical in order to properly manage and reduce damage. Risk assessment is characterized by the process of estimating the probability of an event occurring and the significance or severity of its adverse effects. The aim of the present study is landslide risk zoning in Nekarud watershed using fuzzy logic and remote sensing.
Material and Methods: The most important indicators used in the research include: precipitation classes, altitude classes, geology, NDVI, distance from the river, distance from the fault, slope were identified after reviewing the research literature and expert opinions.
Results: In the AND operator fuzzy inference zoning maps, 1% are in the very low risk category, 2% in the low risk category, 3% in the medium risk zone, 18% in the high risk zone, and 76% in the very high risk zone. The logic of AND, because of the sharing between the criteria, has zoned many highly exposed areas and identified 80% of the basin as high risk. High-risk areas in this model are located in the whole basin. In the OR zoning model, 72, 12.4, 10, 2% are located in very low, low, medium, high and very high risk areas, respectively. Therefore, most of the area in this zoning model is in a very low class, and this logic considers many areas as safe due to the aggregation between criteria, which are located in the west and center of the basin, and only a very small part of the center of the study area is very risky. Highly detected in the eastern basin. Finally, the GAMA operator zoning model was 49%, 9%, 14%, 15%, 13%, respectively, in the very low, low, medium, high, very high risk classes, and the very low risk class covered most of the study area.
Conclusion: In this zoning, most of the vulnerable areas are located in the eastern part of the study basin and are more in line with reality. As the results of the present research showed, the use of RS and GIS technology is a useful and powerful tool in the filed of zoning and landslide risk assessment.
Abstract: abstNatural crises such as landslides are capable of inflicting irreparable damage on humans and the environment. Therefore, risk assessment is critical in order to properly manage and reduce damage. Risk assessment is characterized by the process of estimating the probability of an event occurring and the significance or severity of its adverse effects. The aim of the present study is landslide risk zoning in Nekarud watershed using fuzzy logic and remote sensing.
Material and Methods: The most important indicators used in the research include: precipitation classes, altitude classes, geology, NDVI, distance from the river, distance from the fault, slope were identified after reviewing the research literature and expert opinions.
Results: In the AND operator fuzzy inference zoning maps, 1% are in the very low risk category, 2% in the low risk category, 3% in the medium risk zone, 18% in the high risk zone, and 76% in the very high risk zone. The logic of AND, because of the sharing between the criteria, has zoned many highly exposed areas and identified 80% of the basin as high risk. High-risk areas in this model are located in the whole basin. In the OR zoning model, 72, 12.4, 10, 2% are located in very low, low, medium, high and very high risk areas, respectively. Therefore, most of the area in this zoning model is in a very low class, and this logic considers many areas as safe due to the aggregation between criteria, which are located in the west and center of the basin, and only a very small part of the center of the study area is very risky. Highly detected in the eastern basin. Finally, the GAMA operator zoning model was 49%, 9%, 14%, 15%, 13%, respectively, in the very low, low, medium, high, very high risk classes, and the very low risk class covered most of the study area.
Conclusion: In this zoning, most of the vulnerable areas are located in the eastern part of the study basin and are more in line with reality. As the results of the present research showed, the use of RS and GIS technology is a useful and powerful tool in the filed of zoning and landslide risk assessment.
Type of Study: Applicable |
Received: 2021/10/11 | Accepted: 2022/11/12 | Published: 2022/11/22
Received: 2021/10/11 | Accepted: 2022/11/12 | Published: 2022/11/22
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