{"title":"A GIS-based landslide susceptibility assessment and mapping around the Aba Libanos area, Northwestern Ethiopia","authors":"Dawit Asmare, Chalachew Tesfa, Mulusew Minuyelet Zewdie","doi":"10.1007/s12518-023-00499-7","DOIUrl":null,"url":null,"abstract":"<div><p>The geological hazards caused by natural and manmade activities pose serious property damage, loss of life, and changes in the earth’s features. In this work, GIS-based landslide susceptibility mapping was carried out using the Analytical Hierarchy Process (AHP) and Frequency Ratio (FR) methods for the Chemoga River Sub-Basin (CRSB), in the Aba Libanos area in Northwestern Ethiopia. To produce a susceptibility map, eight influencing factors were selected. They are elevation, slope, aspect, Lithology, land use land cover, curvature, distance to drainage, and distance lineaments. All those influencing factors were statistically analyzed to decide their relationship to past landslides. The relationships between the observed landslide areas and these eight related factors were identified using GIS-based statistical models including AHP and FR. Detailed fieldwork (lithological description and mapping, geological structural measurements, and taking considerations for the impact of each influencing factor on the occurrence of landslides in the area) was conducted to interpret and produce the various maps of the study area. The AHP modeling susceptibility map of the study area was 9.6%, 15.4%, 29.7%, 27.8%, and 17.5% very low, low, moderate, high, and very high respectively. Similarly, based on the value of FR, the study area was classified into five susceptibility zones, 20.7%, 14.6%, 13.0%, 18.6%, and 33.0% very low, low, moderate, high, and very high respectively. Both results showed that steep side slopes and lineaments are very high landslide susceptibility zones. Lastly, the landslide susceptibility maps produced from the two models were validated with detailed fieldwork measurements and observation. Prediction accuracy of these maps that the landslide inventory map was overlaid on the AHP and FR maps. Both susceptibility maps show almost similar results and mainly, introduced some parts of the study areas of the Chemoga river sub-basin (CRSB) as landslide-prone areas.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s12518-023-00499-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
The geological hazards caused by natural and manmade activities pose serious property damage, loss of life, and changes in the earth’s features. In this work, GIS-based landslide susceptibility mapping was carried out using the Analytical Hierarchy Process (AHP) and Frequency Ratio (FR) methods for the Chemoga River Sub-Basin (CRSB), in the Aba Libanos area in Northwestern Ethiopia. To produce a susceptibility map, eight influencing factors were selected. They are elevation, slope, aspect, Lithology, land use land cover, curvature, distance to drainage, and distance lineaments. All those influencing factors were statistically analyzed to decide their relationship to past landslides. The relationships between the observed landslide areas and these eight related factors were identified using GIS-based statistical models including AHP and FR. Detailed fieldwork (lithological description and mapping, geological structural measurements, and taking considerations for the impact of each influencing factor on the occurrence of landslides in the area) was conducted to interpret and produce the various maps of the study area. The AHP modeling susceptibility map of the study area was 9.6%, 15.4%, 29.7%, 27.8%, and 17.5% very low, low, moderate, high, and very high respectively. Similarly, based on the value of FR, the study area was classified into five susceptibility zones, 20.7%, 14.6%, 13.0%, 18.6%, and 33.0% very low, low, moderate, high, and very high respectively. Both results showed that steep side slopes and lineaments are very high landslide susceptibility zones. Lastly, the landslide susceptibility maps produced from the two models were validated with detailed fieldwork measurements and observation. Prediction accuracy of these maps that the landslide inventory map was overlaid on the AHP and FR maps. Both susceptibility maps show almost similar results and mainly, introduced some parts of the study areas of the Chemoga river sub-basin (CRSB) as landslide-prone areas.
期刊介绍:
Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences.
The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology.
Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements