Abstract

Intense rainfall events often produce a great number of shallow landslides events, which in many cases can hits large areas or an entire regional territory. These slope instabilities cause damage to many roads, buildings, and infrastructures and often human loss. In these conditions, it is useful to refine shallow landslides susceptibility maps at regional scale progressively more reliable and efficacy. To take the highlighted goal it is opportune to promote the use of a circular approach that can considers knowledge (data, methods, models, solutions, etc.) constantly upgraded. To achieve this aims we propose a method that introduces structurally in a possible circular approach (progressive better results with constantly upgraded knowledge) the use of a comprehensive geo-database of shallow landslide events and related implemented through a collection and analysis of numerous sources, including published inventory maps, scientific literature, technical reports and newspapers, integrated by a multi-temporal interpretation of remote sensing images and several field surveys. The method is applied referring to the Calabria region, which is largely affected by this landslide category. The refined geo-database realized includes 22,028 shallow landslides, occurred between 1951 and 2017. The relationship between spatial pattern of the shallow landslides and the analyzed predisposing factors (lithological units, fault density, land use, drainage density, slope gradient, TWI, SPI and LS) showed that the high values of slope gradient, LS factor and drainage density, coupled to low values of TWI, displayed a strong control on the shallow landslide occurrence. The efficacy of the geo-database realization proves their usefulness in order to estimate and validate shallow landslide susceptibility map, which was optimally obtained applied a simple bivariate statistical method. The susceptibility map was classified into five classes and about 26% of the study area falls in high and very high susceptible classes and most of the shallow landslides mapped (76%) occur in the same classes. The AUC value of the prediction rate curve was 0.81, indicating a good prediction capability of the susceptibility map. The interaction between shallow landslide susceptibility map and road network map highlighted that the 20% of the roadways of the region area falls in high and very high susceptible areas, whereas was observed that the high (58.4%) and very high (65.6%) susceptibility classes are mainly distributed within cover materials from weathered crystalline rocks. The results obtained in this study indicate that the proposed method can concur to promote a circular approach and support with efficacy a progressive refinement of regional shallow landslide susceptibility map, from 2008 to now, that may be useful tool for national and/or local authorities to manage land use and civil protection planning, and for hazard and risk assessment from regional to slope scale.

摘要

强降雨事件通常会产生大量浅层滑坡事件，在许多情况下，这些事件可能会袭击大片地区或整个区域。这些斜坡不稳定性对许多道路、建筑物和基础设施造成破坏，并经常造成人员伤亡。在这些条件下，在区域尺度上逐步改进浅层滑坡敏感性图是有用的，该图更加可靠和有效。为了实现突出的目标，推广使用循环方法是合适的，该方法可以考虑不断升级的知识（数据、方法、模型、解决方案等）。为了实现这一目标，我们提出了一种方法，该方法以一种可能的循环方法（通过不断更新的知识逐步获得更好的结果）在结构上引入浅层滑坡事件的综合地理数据库的使用，并通过收集和分析众多来源，包括出版的库存地图、科学文献、技术报告和报纸，通过对遥感图像的多时间解释和几次实地调查进行整合。该方法适用于受此类滑坡影响较大的卡拉布里亚地区。实现的精细化地理数据库包括 1951 年至 2017 年间发生的 22,028 个浅层滑坡。浅层滑坡的空间格局与分析的诱发因素（岩性单元、断层密度、土地利用、排水密度、坡度坡度、TWI、SPI 和 LS）表明坡度、LS 因子和排水密度的高值，加上 TWI 的低值，对浅层滑坡的发生表现出强烈的控制。地理数据库实现的有效性证明了它们在估计和验证浅层滑坡敏感性图方面的有用性，该图是应用简单的双变量统计方法优化获得的。敏感性图被分为五个等级，大约26%的研究区域属于高和非常高的敏感等级，大多数浅层滑坡（76%）发生在同一等级。预测率曲线的AUC值为0.81，表明药敏图具有良好的预测能力。浅层滑坡敏感性图和路网图的交互作用突出显示，该区域20%的道路属于高敏感性和极高敏感性区域，而观察到高敏感性（58.4%）和极高敏感性（65.6%）类主要分布在风化结晶岩的覆盖材料中。本研究中获得的结果表明，所提出的方法可以促进循环方法并有效支持区域浅层滑坡敏感性图的逐步细化，从 2008 年到现在，这可能是国家和/或地方当局的有用工具管理土地使用和民防规划，以及从区域到斜坡规模的灾害和风险评估。