{"title":"利用激光雷达数据绘制滑坡易发性图:以泰国考艾国家公园为例","authors":"","doi":"10.52939/ijg.v19i3.2597","DOIUrl":null,"url":null,"abstract":"Landslide is the natural problem occur worldwide due to its geological features, climatic characteristics and human activities. With the help of a geographic information system (GIS) and the Analytic Hierarchical Process (AHP) method, this research attempts to develop a map of landslide susceptibility. During the present investigation, a total of ten landslide influencing factors including elevation, slope, curvature, aspect, topographic wetness index (TWI), land cover, lithology, precipitation, distance to the road and drainage, were examined for the present analysis. Using AHP, weights were applied to each factor. The weight over lay approach was used to create the landslide susceptibility map, which was then divided into five classes. According to the research findings of the susceptibility classes, 19.97% of the research 's area was highly susceptible, followed by 61.65% of low susceptible, 17.33% of moderate susceptible, 0.94% of high susceptible, and 0.12% of very high susceptible. The areas with extremely high landslide susceptibility are adjacent to a road system and have a steep slope. The amount of mean annual rainfall is high and lithology belonging to the Jurassic metasediments. The findings for this map showing the research area's vulnerability to landslides in Khao Yai National Park are useful for planners and decision-makers for slope management and future development projects in the area.","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Landslide Susceptibility Mapping Using LiDAR Data: A Case Study of Khao Yai National Park, Thailand\",\"authors\":\"\",\"doi\":\"10.52939/ijg.v19i3.2597\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Landslide is the natural problem occur worldwide due to its geological features, climatic characteristics and human activities. With the help of a geographic information system (GIS) and the Analytic Hierarchical Process (AHP) method, this research attempts to develop a map of landslide susceptibility. During the present investigation, a total of ten landslide influencing factors including elevation, slope, curvature, aspect, topographic wetness index (TWI), land cover, lithology, precipitation, distance to the road and drainage, were examined for the present analysis. Using AHP, weights were applied to each factor. The weight over lay approach was used to create the landslide susceptibility map, which was then divided into five classes. According to the research findings of the susceptibility classes, 19.97% of the research 's area was highly susceptible, followed by 61.65% of low susceptible, 17.33% of moderate susceptible, 0.94% of high susceptible, and 0.12% of very high susceptible. The areas with extremely high landslide susceptibility are adjacent to a road system and have a steep slope. The amount of mean annual rainfall is high and lithology belonging to the Jurassic metasediments. The findings for this map showing the research area's vulnerability to landslides in Khao Yai National Park are useful for planners and decision-makers for slope management and future development projects in the area.\",\"PeriodicalId\":38707,\"journal\":{\"name\":\"International Journal of Geoinformatics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Geoinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52939/ijg.v19i3.2597\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52939/ijg.v19i3.2597","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Social Sciences","Score":null,"Total":0}
Landslide Susceptibility Mapping Using LiDAR Data: A Case Study of Khao Yai National Park, Thailand
Landslide is the natural problem occur worldwide due to its geological features, climatic characteristics and human activities. With the help of a geographic information system (GIS) and the Analytic Hierarchical Process (AHP) method, this research attempts to develop a map of landslide susceptibility. During the present investigation, a total of ten landslide influencing factors including elevation, slope, curvature, aspect, topographic wetness index (TWI), land cover, lithology, precipitation, distance to the road and drainage, were examined for the present analysis. Using AHP, weights were applied to each factor. The weight over lay approach was used to create the landslide susceptibility map, which was then divided into five classes. According to the research findings of the susceptibility classes, 19.97% of the research 's area was highly susceptible, followed by 61.65% of low susceptible, 17.33% of moderate susceptible, 0.94% of high susceptible, and 0.12% of very high susceptible. The areas with extremely high landslide susceptibility are adjacent to a road system and have a steep slope. The amount of mean annual rainfall is high and lithology belonging to the Jurassic metasediments. The findings for this map showing the research area's vulnerability to landslides in Khao Yai National Park are useful for planners and decision-makers for slope management and future development projects in the area.