{"title":"Landslide susceptibility mapping using frequency ratio and analytical hierarchy process method in Awabel Woreda, Ethiopia","authors":"Engdaw Gulbet, Belete Getahun","doi":"10.1016/j.qsa.2024.100246","DOIUrl":null,"url":null,"abstract":"<div><div>A landslide is a serious geo-environmental problem that results in the death of life and the devastation of infrastructure, properties, and agricultural lands. This research aimed to identify landslide susceptibility zones in selected Kebels of Awabel Woreda, central Ethiopia. Frequency ratio (FR) and analytical hierarchy process (AHP) methods were used. 175 landslide inventory data collected from Google Earth and field data were collected for testing and training data sets. Using the analytical hierarchy process, all the thematic layers (stream distance, slope, aspect, rainfall, lineament density, elevation, lithology, soil, land use/land cover, and curvature) were reclassified and weighted based on their relative contribution to landslide occurrence with the help of experts’ knowledge. The results show that 11.85% and 20.52 % of the study fall under the very high and high susceptible zones, respectively, while the low susceptible zones cover 26.3% and 14.74% of the area. The landslide susceptibility zone identified by the frequency ratio model shows that (6.09%) and (16.9%) of the area covered very high and high susceptible zones, respectively, while 30.4% and 23.4% of the area covered low and very susceptible zones, respectively. The predicted landslide-susceptible areas were validated using existing landslide points with the help of the ROC tool in ArcGIS. Area under the curve (AUC) results were 84.5% for the AHP model and 73% for the frequency ratio model. The find of this study will provide an input for decision makers and land use planners in the future.</div></div>","PeriodicalId":34142,"journal":{"name":"Quaternary Science Advances","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quaternary Science Advances","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666033424000844","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
A landslide is a serious geo-environmental problem that results in the death of life and the devastation of infrastructure, properties, and agricultural lands. This research aimed to identify landslide susceptibility zones in selected Kebels of Awabel Woreda, central Ethiopia. Frequency ratio (FR) and analytical hierarchy process (AHP) methods were used. 175 landslide inventory data collected from Google Earth and field data were collected for testing and training data sets. Using the analytical hierarchy process, all the thematic layers (stream distance, slope, aspect, rainfall, lineament density, elevation, lithology, soil, land use/land cover, and curvature) were reclassified and weighted based on their relative contribution to landslide occurrence with the help of experts’ knowledge. The results show that 11.85% and 20.52 % of the study fall under the very high and high susceptible zones, respectively, while the low susceptible zones cover 26.3% and 14.74% of the area. The landslide susceptibility zone identified by the frequency ratio model shows that (6.09%) and (16.9%) of the area covered very high and high susceptible zones, respectively, while 30.4% and 23.4% of the area covered low and very susceptible zones, respectively. The predicted landslide-susceptible areas were validated using existing landslide points with the help of the ROC tool in ArcGIS. Area under the curve (AUC) results were 84.5% for the AHP model and 73% for the frequency ratio model. The find of this study will provide an input for decision makers and land use planners in the future.