@Article{ZhangFuQuChLuLiKo:2022:LaSuMa,
               author = "Zhang, Tingyu and Fu, Quan and Quevedo, Renata Pacheco and Chen, 
                         Tianqing and Luo, Dan and Liu, Fangfang and Kong, Hui",
          affiliation = "{Shaanxi Provincial Key Laboratory of Land Rehabilitation} and 
                         {Shaanxi Provincial Land Engineering Construction Group Land 
                         Survey Planning and Design Institute} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Shaanxi Provincial Key Laboratory 
                         of Land Rehabilitation} and {Shaanxi Provincial Land Engineering 
                         Construction Group Land Survey Planning and Design Institute} and 
                         {Shaanxi Provincial Land Engineering Construction Group Land 
                         Survey Planning and Design Institute} and {Shaanxi Provincial Key 
                         Laboratory of Land Rehabilitation}",
                title = "Landslide Susceptibility Mapping Using Novel Hybrid Model Based on 
                         Different Mapping Units",
              journal = "KSCE Journal of Civil Engineering",
                 year = "2022",
               volume = "11",
                pages = "1--13",
             keywords = "Geology, Systematically developed fores of multiple trees, 
                         Entropy, Hybrid models, Spatial analysis.",
             abstract = "Landslide is a most widespread geohazards around the world. 
                         Reasonable landslide susceptibility mapping can aid 
                         decision-makers in landslide prevention. Therefore, drawing 
                         regional landslide susceptibility map is of great significance to 
                         landslide prevention. This research mainly aims to explore a new 
                         method and carry out the landslide susceptibility mapping based on 
                         terrain mapping unit (TMU) and grid cells mapping unit (GCMU) in 
                         Wuqi County, Yanan City, China. Firstly, the landslide inventory 
                         map was prepared based on 717 landslides that were extracted. 
                         Secondly, the index of entropy model (IOE) was applied to quantify 
                         landslide predisposing factors based on TMU and GCMU, 
                         respectively. Finally, the systematically developed forest of 
                         multiple trees (SysFor) was integrated with IOE to construct a 
                         novel hybrid model (IOE-SysFor) and the landslide susceptibility 
                         maps based on TMU and GCMU were obtained. Statistical indices and 
                         receiver operating characteristic curve (ROC) were applied to 
                         evaluate the results and compare the approaches. From the results, 
                         it indicated that the accuracy of landslide susceptibility maps 
                         generated by the IOE-SysFor based on TMU and GCMU was 
                         satisfactory, furthermore, the performance of IOE-SysFor model 
                         running on the TMU was better than GCMU. Therefore, the TMU was 
                         considered as a more suitable landslide mapping unit for similar 
                         regions and the approach developed by this study can provide a 
                         reference for future researches.",
                  doi = "10.1007/s12205-022-1471-9",
                  url = "http://dx.doi.org/10.1007/s12205-022-1471-9",
                 issn = "1226-7988",
                label = "lattes: 5290642954663700 3 ZhangFuQuChLuLiKo:2022:LaSuMa",
             language = "en",
           targetfile = "Zhang2022_Article_LandslideSusceptibilityMapping.pdf",
        urlaccessdate = "06 jun. 2024"
}