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Towards the Use of Land Use Legacies in Landslide Modeling: Current Challenges and Future Perspectives in an Austrian Case Study
Land ( IF 3.905 ) Pub Date : 2021-09-08 , DOI: 10.3390/land10090954
Raphael Knevels , Alexander Brenning , Simone Gingrich , Gerhard Heiss , Theresia Lechner , Philip Leopold , Christoph Plutzar , Herwig Proske , Helene Petschko

Land use/land cover (LULC) changes may alter the risk of landslide occurrence. While LULC has often been considered as a static factor representing present-day LULC, historical LULC dynamics have recently begun to attract more attention. The study objective was to assess the effect of LULC legacies of nearly 200 years on landslide susceptibility models in two Austrian municipalities (Waidhofen an der Ybbs and Paldau). We mapped three cuts of LULC patterns from historical cartographic documents in addition to remote-sensing products. Agricultural archival sources were explored to provide also a predictor on cumulative biomass extraction as an indicator of historical land use intensity. We use historical landslide inventories derived from high-resolution digital terrain models (HRDTM) generated using airborne light detection and ranging (LiDAR), which are reported to have a biased landslide distribution on present-day forested areas and agricultural land. We asked (i) if long-term LULC legacies are important and reliable predictors and (ii) if possible inventory biases may be mitigated by LULC legacies. For the assessment of the LULC legacy effect on landslide occurrences, we used generalized additive models (GAM) within a suitable modeling framework considering various settings of LULC as predictor, and evaluated the effect with well-established diagnostic tools. For both municipalities, we identified a high density of landslides on present-day forested areas, confirming the reported drawbacks. With the use of LULC legacy as an additional predictor, it was not only possible to account for this bias, but also to improve model performances.

中文翻译:

在滑坡建模中利用土地利用遗产:奥地利案例研究中的当前挑战和未来展望

土地利用/土地覆盖 (LULC) 的变化可能会改变滑坡发生的风险。虽然 LULC 通常被认为是代表当今 LULC 的静态因素,但历史 LULC 动态最近开始引起更多关注。研究目的是评估近 200 年的 LULC 遗产对奥地利两个城市(Waidhofen an der Ybbs 和 Paldau)的滑坡敏感性模型的影响。除了遥感产品外,我们还从历史制图文件中绘制了三个 LULC 模式。探索了农业档案资源,以提供累积生物量提取的预测因子,作为历史土地利用强度的指标。我们使用源自使用机载光探测和测距 (LiDAR) 生成的高分辨率数字地形模型 (HRDTM) 的历史滑坡清单,据报道,它们在当今的森林地区和农田上有偏向的滑坡分布。我们询问 (i) 长期 LULC 遗产是否是重要且可靠的预测因素,以及 (ii) LULC 遗产是否可以减轻库存偏差。为了评估 LULC 遗留对滑坡发生的影响,我们在合适的建模框架内使用广义加性模型 (GAM),考虑到 LULC 的各种设置作为预测变量,并使用完善的诊断工具评估影响。对于这两个城市,我们在当今的森林地区发现了高密度的山体滑坡,证实了报告的缺陷。使用 LULC 传统作为额外的预测器,不仅可以解决这种偏差,还可以提高模型性能。
更新日期:2021-09-08
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