Landslide Susceptibility Map of the Northwestern Gerecse Hills (Hungary)

Supplementary material for Gerzsenyi and Albert (in press).<br>We created the Landslide Susceptibility of the Northern Gerecse Hills using Chung's (2006) likelihood ratio function model. The input datasets were the TanDEM-X DEM (12 m), the Hungarian National Landslides Cadastre landslide inventory and the Geological Map of Hungary (1 : 100 000). The model partitions the study area into a landslide and non-landslide part, then computes the distributions of the analysed variables for both the landslide and non-landslide area. By comparing the distributions of the analysed variables in the landslide and non-landslide area with grid computation methods, the model yields landslide susceptibility estimates for the study area. The estimations show to what extent a certain area is similar to the sample areas, therefore, its likelihood to be affected by landslides in the future. The estimated landslide susceptibility is given in a percentile form in this raster.Value X means that X% of the total cells has lower susceptibility than the cell with value X. Areas with higher susceptibility values are relatively more prone to landsliding than areas with lower susceptibility values. Susceptibility values range from 1 to 100.<br>Contents:1. Susceptibility raster:GD-AG_TGSI-2018-0047_susceptibility_map_percentiles_12m.tif<br>Resolution: 12 mCRS: EPSG: 23700 - HD72 / EOVWest: 593870.3272East: 608714.3272South: 259582.8811North: 269278.8811<br><br>2. Metadata (QGIS 3):GD-AG_TGSI-2018-0047_susceptibility_map_percentiles_12m.qmd<br><br>Acknowledgement:The TanDEM-X data was provided by the German Aerospace Center (DLR). © DLR – 2017. The study was supported by the ÚNKP-17-2 New National Excellence Program of the Ministry of Human Capacities, Hungary. This research was partly supported by the Thematic Excellence Programme, Industry and Digitization Subprogramme, NRDI Office, 2019 – Project no. ED_18-1-2019-0030.<br>References:Chung, C. 2006. “Using Likelihood Ratio Functions for Modeling the Conditional Probability of Occurrence of Future Landslides for Risk Assessment.” <i>Computers &amp; Geosciences</i> 32: 1052–1068. doi:10.1016/j.cageo.2006.02.003<br> Gerzsenyi, D. and Albert, G. (in press) "Landslide inventory validation and susceptibility mapping in the Gerecse Hills, Hungary." <i>Geo-spatial Information Science</i>.

本数据集为Gerzsenyi与Albert（已录用待刊）研究的配套补充材料。

我们采用Chung（2006）提出的似然比函数模型，构建了匈牙利北部盖雷采山的滑坡敏感性（Landslide Susceptibility）数据集。本次研究的输入数据集包括TanDEM-X数字高程模型（DEM，12 m分辨率）、匈牙利国家滑坡登记册滑坡编目数据，以及1:10万比例尺的匈牙利地质图。

该模型将研究区划分为滑坡区与非滑坡区，分别计算分析变量在两类区域中的分布特征；通过网格计算方法对比分析变量在滑坡区与非滑坡区的分布差异，最终为研究区生成滑坡敏感性评估结果。该评估结果可反映某一区域与样本区域的相似程度，进而表征该区域未来发生滑坡的可能性。本数据集以栅格形式存储滑坡敏感性评估结果，采用百分位值进行表征：栅格值为X时，代表研究区内总栅格单元中有X%的单元敏感性低于该栅格单元。敏感性值越高的区域，相较于敏感性值较低的区域，发生滑坡的相对概率更高。该数据集的敏感性值取值范围为1至100。

数据集内容：
1. 敏感性栅格文件：GD-AG_TGSI-2018-0047_susceptibility_map_percentiles_12m.tif
分辨率：12 m
坐标系（CRS）：EPSG: 23700 - HD72 / EOV
西边界：593870.3272
东边界：608714.3272
南边界：259582.8811
北边界：269278.8811

2. 元数据文件（适配QGIS 3）：GD-AG_TGSI-2018-0047_susceptibility_map_percentiles_12m.qmd

致谢：
TanDEM-X数据由德国航空航天中心（DLR）提供，© DLR – 2017。本研究得到匈牙利人力资源部新国家卓越计划ÚNKP-17-2项目的资助。本研究部分得到匈牙利国家研究、发展和创新办公室（NRDI Office）主题卓越计划产业与数字化子项目2019年度项目ED_18-1-2019-0030的支持。

参考文献：
1. Chung, C. 2006. 《用于风险评估的未来滑坡发生条件概率建模：似然比函数的应用》，《计算机与地球科学》，第32卷，第1052–1068页，DOI: 10.1016/j.cageo.2006.02.003
2. Gerzsenyi, D. 与 Albert, G.（已录用待刊），《匈牙利盖雷采山区滑坡编目验证与敏感性制图》，《地理空间信息科学》。