Faming HuangYu CaoWenbin LiFilippo CataniGuquan SongJinsong HuangChangshi Yu
School of Civil Engineering and Architecture, Nanchang UniversityHebei International Joint Research Center for Remote Sensing of Agricultural Drought Monitoring/School of Land Science and Space Planning, Hebei GEO UniversityDepartment of Geosciences, University of PadovaDiscipline of Civil, Surveying and Environmental Engineering, Priority Research Centre for Geotechnical Science and Engineering, University of NewcastleSchool of Information Engineering, Nanchang University
This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction (LSP). To illustrate various study area scales, Ganzhou City in China, its eastern region (Ganzhou East), and Ruijin County in Ganzhou East were chosen. Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m, as well as slope units that were extracted by multi-scale segmentation method. The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs. Then, landslide susceptibility maps (LSMs) of Ganzhou City, Ganzhou East and Ruijin County are produced using a support vector machine (SVM) and random forest (RF), respectively. The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City, along with the LSMs of Ruijin County from Ganzhou East. Additionally, LSMs of Ruijin at various mapping unit scales are generated in accordance. Accuracy and landslide susceptibility indexes (LSIs) distribution are used to express LSP uncertainties. The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City, Ganzhou East to Ruijin County, whereas those under slope units are less affected by study area scales. Of course, attentions should also be paid to the broader representativeness of large study areas. The LSP accuracy of slope units increases by about 6%–10% compared with those under grid units with 30 m and 60 m resolution in the same study area's scale. The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large. The importance of environmental factors varies greatly with the 60 m grid unit, but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.
Landslide susceptibility predictionUncertainty analysisStudy areas scalesMapping unit scalesSlope unitsRandom forest
主办单位:煤炭科学研究总院有限公司 中国煤炭学会学术期刊工作委员会