School of Civil and Environmental Engineering, The University of New South Wales, Sydney, Australia.
Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Via Madonna Alta 126, 06128, Perugia, Italy.
Sci Rep. 2021 Oct 29;11(1):21333. doi: 10.1038/s41598-021-00780-y.
Inventories of seismically induced landslides provide essential information about the extent and severity of ground effects after an earthquake. Rigorous assessment of the completeness of a landslide inventory and the quality of a landslide susceptibility map derived from the inventory is of paramount importance for disaster management applications. Methods and materials applied while preparing inventories influence their quality, but the criteria for generating an inventory are not standardized. This study considered five landslide inventories prepared by different authors after the 2015 Gorkha earthquake, to assess their differences, understand the implications of their use in producing landslide susceptibility maps in conjunction with standard landslide predisposing factors and logistic regression. We adopted three assessment criteria: (1) an error index to identify the mutual mismatches between the inventories; (2) statistical analysis, to study the inconsistency in predisposing factors and performance of susceptibility maps; and (3) geospatial analysis, to assess differences between the inventories and the corresponding susceptibility maps. Results show that substantial discrepancies exist among the mapped landslides. Although there is no distinct variation in the significance of landslide causative factors and the performance of susceptibility maps, a hot spot analysis and cluster/outlier analysis of the maps revealed notable differences in spatial patterns. The percentages of landslide-prone hot spots and clustered areas are directly proportional to the size of the landslide inventory. The proposed geospatial approaches provide a new perspective to the investigators for the quantitative analysis of earthquake-triggered landslide inventories and susceptibility maps.
地震诱发滑坡清单提供了地震后地面效应的范围和严重程度的重要信息。严格评估滑坡清单的完整性和从清单中得出的滑坡易发性图的质量，对于灾害管理应用至关重要。在编制清单时应用的方法和材料会影响其质量，但生成清单的标准尚未标准化。本研究考虑了 2015 年廓尔喀地震后由不同作者编制的五个滑坡清单，以评估它们之间的差异，了解在结合标准滑坡诱发因素和逻辑回归生成滑坡易发性图时使用它们的影响。我们采用了三个评估标准：（1）错误指数，用于识别清单之间的相互不匹配；（2）统计分析，用于研究诱发因素和易发性图的不一致性；（3）地理空间分析，用于评估清单之间和相应易发性图之间的差异。结果表明，绘制的滑坡之间存在明显差异。尽管滑坡诱发因素的重要性和易发性图的性能没有明显变化，但对地图的热点分析和聚类/异常值分析显示出空间模式的显著差异。易发生滑坡的热点和聚类区域的百分比与滑坡清单的大小成正比。提出的地理空间方法为研究人员提供了一种新的视角，用于对地震触发的滑坡清单和易发性图进行定量分析。
