An index to describe the earthquake effect on subsequent landslides in Central Taiwan

[[abstract]]Chelungpu fault reactivation produced the 1999 Chi-Chi earthquake in Central Taiwan in 1999, triggering many landslides over a broad area. The ground damage caused by the Chi-Chi earthquake still influences successive rainfall-triggered landslides. The landslide distribution triggered by heavy rainfall during typhoon Mindulle in 2004 has a high correlation to the landslide sites triggered by the previous Chi-Chi earthquake. This research calculated and ordered landslide data for both the area and distance from the Chelungpu fault. The rank correlation coefficient for measuring two covarying variables is employed to quantify the degree of correlation between the landslide distribution and the Chelungpu fault. A high rank correlation coefficient value demonstrates a highly correlated relationship between the subsequent landslides in 2004 and previous Chelungpu fault activity in 1999.[[notice]]補正完

Forest fire susceptibility mapping in the Minudasht forests, Golestan province, Iran

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Gis-Based Landslide Susceptibility Mapping With Probabilistic Likelihood Ratio And Spatial Multi-Criteria Evaluation Models (North Of Tehran, Iran)

The aim of this study is to produce landslide susceptibility mapping by probabilistic likelihood ratio (PLR) and spatial multi-criteria evaluation (SMCE) models based on geographic information system (GIS) in the north of Tehran metropolitan, Iran. The landslide locations in the study area were identified by interpretation of aerial photographs, satellite images, and field surveys. In order to generate the necessary factors for the SMCE approach, remote sensing and GIS integrated techniques were applied in the study area. Conditioning factors such as slope degree, slope aspect, altitude, plan curvature, profile curvature, surface area ratio, topographic position index, topographic wetness index, stream power index, slope length, lithology, land use, normalized difference vegetation index, distance from faults, distance from rivers, distance from roads, and drainage density are used for landslide susceptibility mapping. Of 528 landslide locations, 70 % were used in landslide susceptibility mapping, and the remaining 30 % were used for validation of the maps. Using the above conditioning factors, landslide susceptibility was calculated using SMCE and PLR models, and the results were plotted in ILWIS-GIS. Finally, the two landslide susceptibility maps were validated using receiver operating characteristic curves and seed cell area index methods. The validation results showed that area under the curve for SMCE and PLR models is 76.16 and 80.98 %, respectively. The results obtained in this study also showed that the probabilistic likelihood ratio model performed slightly better than the spatial multi-criteria evaluation. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.Wo