Predictive landslide susceptibility mapping using spatial information in the Pechabun area of Thailand

For predictive landslide susceptibility mapping, this study applied and verified probability model, the frequency ratio and statistical model, logistic regression at Pechabun, Thailand, using a geographic information system (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and field surveys, and maps of the topography, geology and land cover were constructed to spatial database. The factors that influence landslide occurrence, such as slope gradient, slope aspect and curvature of topography and distance from drainage were calculated from the topographic database. Lithology and distance from fault were extracted and calculated from the geology database. Land cover was classified from Landsat TM satellite image. The frequency ratio and logistic regression coefficient were overlaid for landslide susceptibility mapping as each factor’s ratings. Then the landslide susceptibility map was verified and compared using the existing landslide location. As the verification results, the frequency ratio model showed 76.39% and logistic regression model showed 70.42% in prediction accuracy. The method can be used to reduce hazards associated with landslides and to plan land cover.     

Landslide hazard mapping using logistic regression model in Mackenzie Valley,Canada

A logistic regression model is developed within the framework of a Geographic Information System (GIS) to map landslide hazards in a mountainous environment. A case study is conducted in the mountainous southern Mackenzie Valley, Northwest Territories, Canada. To determine the factors influencing landslides, data layers of geology, surface materials, land cover, and topography were analyzed by logistic regression analysis, and the results are used for landslide hazard mapping. In this study, bedrock, surface materials, slope, and difference between surface aspect and dip direction of the sedimentary rock were found to be the most important factors affecting landslide occurrence. The influence on landslides by interactions among geologic and geomorphic conditions is also analyzed, and used to develop a logistic regression model for landslide hazard mapping. The comparison of the results from the model including the interaction terms and the model not including the interaction terms indicate that interactions among the variables were found to be significant for predicting future landslide probability and locating high hazard areas. The results from this study demonstrate that the use of a logistic regression model within a GIS framework is useful and suitable for landslide hazard mapping in large mountainous geographic areas such as the southern Mackenzie Valley.     

Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models

This study applied, tested and compared a probability model, a frequency ratio and statistical model, a logistic regression to Damre Romel area, Cambodia, using a geographic information system. For landslide susceptibility mapping, landslide locations were identified in the study area from interpretation of aerial photographs and field surveys, and a spatial database was constructed from topographic maps, geology and land cover. The factors that influence landslide occurrence, such as slope, aspect, curvature and distance from drainage were calculated from the topographic database. Lithology and distance from lineament were extracted and calculated from the geology database. Land cover was classified from Landsat TM satellite imagery. The relationship between the factors and the landslides was calculated using frequency ratio and logistic regression models. The relationships, frequency ratio and logistic regression coefficient were overlaid to make landslide susceptibility map. Then the landslide susceptibility map was compared with known landslide locations and tested. As the result, the frequency ratio model (86.97%) and the logistic regression (86.37%) had high and similar prediction accuracy. The landslide susceptibility map can be used to reduce hazards associated with landslides and to land cover planning.     

北京山区突发性地质灾害易发性评价

北京山区地质环境条件复杂,发育大量突发地质灾害隐患,既直接威胁山区村庄、道路、景区的人员及设施的安全,又会对城镇的规划建设构成威胁。通过开展地质灾害易发性评价工作,划分出地质灾害易发区,以评价结果指导城镇建设规划,减轻地质灾害的威胁,这是一项十分重要的工作。文章在阐述北京山区崩塌、滑坡及泥石流突发地质灾害发育情况的基础上,选取了坡度、起伏度、工程地质岩组、地质构造、地貌类型及降水等6个影响因子,采用综合信息量模型方法,分别对北京山区斜坡类灾害（崩塌、滑坡）和泥石流灾害的易发性进行评价,并根据“就高不就低”的原则,叠加各灾种的易发性评价结果划分出北京山区突发地质灾害易发性分区图,为城镇建设适宜性评价、编制国土空间规划及完善空间治理提供科学的依据。     

长江三峡工程库区巴东新城址环境工程地质预测

巴东县城新址是长江三峡工程库区移民城镇环境工程地质问题较突出的场址之一, 主要环境工程地质问题是古滑坡的失稳和库岸再造。在查清地质环境条件的基础上, 本文着重进行了黄土坡古滑坡、赵树岭古滑坡等古滑坡的稳定性预测, 并根据实测的有关参数, 采用图解法预测库岸再造宽度。在此基础上, 根据影响该区城市开发建设的主要的地质环境要素, 建立隶属函数, 采用模糊综合评判模型及算法, 给出巴东县城新址区的城市开发建设的环境地质分区评价。     

An Overview of Measurement and Calculation Methods on the Land Surface Temperature on Alpine Mountainous Cold Regions

Land surface temperature on alpine mountainous cold regions, which is one of basic parameters of the regional hydrological and meteorological conditions, directly affects glacial recession, snow melt, distribution and freezing thawing process of permafrost, evapotranspiration, vegetation growth, and various underlying surface change process, and then changes the regional hydrological and ecological environment, becomes the important parameter of the research on land surface process and the study of eco-hydrological process. This paper tried to provide an overview of research on land surface temperature, and to introduce its influence factors and the ways to obtain land surface temperature data in high mountainous cold region. Relative to low elevation plain, the land surface temperature was significantly affected by local altitude, terrain and plant cover. There were some methods to obtain land surface temperature, such as measurement in situ, retrieval based on remote sensing and calculation by land surface process models, but there were some limitations while used on alpine mountainous cold regions. Land surface temperature data from meteorological stations were only about level bare ground, and the influence of terrain or vegetable cover was not considered. Therefore, the data could not represent the information of region scale on mountainous area. Land surface temperature retrieval from remote sensing data, because of calculation theory, ground observation verification and spatiotemporal resolution, made it difficult to fulfill research on hydrology, land surface process and eco-hydrological process in alpine mountainous area. Land surface process models estimated land surface temperature in the experimental sites with high accuracy, but reduced the accuracy while upscale to the region scale on the mountainous cold area, because of the error from input control meteorological, soil and plant variables, and the error of ground observation site verification. The future research on land surface temperature on alpine mountainous cold regions should strengthen field observations and improve data accuracy, to build a physical land surface temperature estimation method with topographic and vegetation parameters, and to contribute to research on land-atmosphere-water process in alpine mountainous regions.     

The application of GIS-based bivariate statistical methods for landslide hazards assessment in the upper Tons river valley,Western Himalaya,India

Landslides are one of the most frequent and common natural hazards in many parts of Himalaya. To reduce the potential risk, the landslide susceptibility maps are one of the first and most important steps in the landslide hazard mitigation. Earth observation satellite and geographical information system-based techniques have been used to derive and analyse various geo-environmental parameters significant to landslide hazards. In this study, a bivariate statistics method was used for spatial modelling of landslide susceptibility zones. For this purpose, thematic layers including landslide inventory, geology, slope angle, slope aspect, geomorphology, slope morphology, drainage density, lineament and land use/land cover were used. A large number of landslide occurrences have been observed in the upper Tons river valley area of Western Himalaya. The result has been used to spatially classify the study area into zones of very high, high, moderate, low and very low landslide susceptibility zones. About 72% of active landslides have been observed to occur in very high and high hazard zones. The result of the analysis was verified using the landslide location data. The validation result shows significant agreement between the susceptibility map and landslide location. The result can be used to reduce landslide hazards by proper planning.     

Estimating potential landslide sites of an upland sub-watershed in Western Ghat’s of Kerala (India) through frequency ratio and GIS

The purpose of this study is to assess the susceptibility of landslides in parts of Western Ghats, Kerala, India, using a geographical information system (GIS). Landslide inventory of the area was made by detailed field surveys and the analysis of the topographical maps. The landslide triggering factors are considered to be slope angle, slope aspect, slope curvature, slope length, distance from drainage, distance from lineaments, lithology, land use and geomorphology. ArcGIS version 8.3 was used to manipulate and analyse all the collected data. Probabilistic-likelihood ratio was used to create a landslide susceptibility map for the study area. The result was validated using the Area under Curve (AUC) method and temporal data of landslide occurrences. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations. As the result, the success rate of the model was (84.46%) and the prediction rate of the model was (82.38%) shows high prediction accuracy. In the reclassified final landslide susceptibility zone map, 5.68% of the total area is classified as critical in nature. The landslide susceptibility map thus produced can be used to reduce hazards associated with landslides and to land cover planning.     

Overview Landslide Hazard Assessment of China

In recent years, China has suffered serious geological disasters, most of slope movements due to complex geology, geomorphology, unusual weather conditions, and large-scale land explorations during high speed economic development. According to geological hazard investigations organized by the Ministry of Land and Resources of China, there are 400 towns and more than 10000 villages under the threatening of those landslide hazards. This paper presents the overview landslide hazard assessment in terms of GIS, which aims to evaluate the overview geohazard potentials, vulnerabilities of lives and land resources, and risks in conterminous China on the scale of 1 : 6 000 000. This is the first overview landslide hazard potential map of China.     

Detection and accuracy of landslide movement by InSAR analysis using PALSAR-2 data

Interferometric synthetic aperture radar (InSAR) analysis is a radar technique for generating large-area maps of ground deformation using differences in the phase of microwaves returning to a satellite. In recent years, high-resolution SAR sensors have been developed that enable small-scale slope deformation to be detected, such as the partial block movement of a landslide. The L-band SAR (PALSAR-2) is mounted on Advanced Land Observing Satellite-2 (ALOS-2), which was launched on 24 Mar. 2014. Its main improvements compared with ALOS are enhanced resolution of as high as 3 m with a high-frequency recurrence period (14 days). Owing to its high resolution and the use of the L-band, PALSAR-2 can obtain reflective data passing through a tree canopy surface, unlike the other synthetic aperture radars. Therefore, the coherence of InSAR in mountainous forest areas is less likely to decrease, making it advantageous for the extraction of slope movement. In this study, to verify the accuracy of InSAR analysis using PALSAR-2 data, we compared the results of InSAR analysis and the measurement of the displacement in a landslide by global navigation satellite system (GNSS) observation. It was found that the average difference between the displacements obtained by InSAR analysis and the field measurements by GNSS was only 15.1 mm in the slant range direction, indicating the high accuracy of InSAR analysis. Many of the areas detected by InSAR analysis corresponded to the locations of surface changes due to landslide activity. Additionally, in the areas detected by InSAR analysis using multiple datasets, the ground changes due to landslide movement were confirmed by site investigation.     

Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China

There is no doubt that land cover and climate changes have consequences on landslide activity, but it is still an open issue to assess and quantify their impacts. Wanzhou County in southwest China was selected as the test area to study rainfall-induced shallow landslide susceptibility under the future changes of land use and land cover (LULC) and climate. We used a high-resolution meteorological precipitation dataset and frequency distribution model to analyse the present extreme and antecedent rainfall conditions related to landslide activity. The future climate change factors were obtained from a 4-member multi-model ensemble that was derived from statistically downscaled regional climate simulations. The future LULC maps were simulated by the land change modeller (LCM) integrated into IDRISI Selva software. A total of six scenarios were defined by considering the rainfall (antecedent conditions and extreme events) and LULC changes towards two time periods (mid and late XXI century). A physically-based model was used to assess landslide susceptibility under these different scenarios. The results showed that the magnitude of both antecedent effective recharge and event rainfall in the region will evidently increase in the future. Under the scenario with a return period of 100 years, the antecedent rainfall in summer will increase by up to 63% whereas the event rainfall will increase by up to 54% for the late 21st century. The most considerable changes of LULC will be the increase of forest cover and the decrease of farming land. The magnitude of this change can reach + 22.1% (forest) and –9.2% (farmland) from 2010 until 2100, respectively. We found that the negative impact of climate change on landslide susceptibility is greater than the stabilizing effect of LULC change, leading to an over decrease in stability over the study area. This is one of the first studies across Asia to assess and quantify changes of regional landslide susceptibility under scenarios driven by LULC and climate change. Our results aim to guide land use planning and climate change mitigation considerations to reduce landslide risk.     

山区公路地质灾害减灾决策支持系统——以西藏古乡沟泥石流为例

由于复杂地形条件和地质条件以及降雨、地下水等因素的影响,山区公路易受到泥石流、滑坡、崩塌、溜砂坡等地质灾害的危害。文章在对山区公路地质灾害模型研究和分析的基础上,建立了滑坡稳定性分析、泥石流活动性分析、泥石流危险范围预测与危险性分区、滑坡区公路整治方案优选、拦砂坝优化设计等灾害分析模型和减灾决策模型,通过数据库、分析模型和决策模型的集成,建立了基于组件式GIS的山区公路地质灾害减灾决策支持系统。作为系统应用的实例,文章最后讨论了系统在古乡沟泥石流危险范围预测的应用,预测了一定条件下泥石流堆积扇上的泥深,泥石流运动过程中出现的最大泥深、最大速率、最大动量和最大动能,为古乡沟泥石流的预防和治理提供了科学依据。     

Landslides in the Tandayapa Valley, northern Andes, Ecuador: implications for landform development in humid and tectonically active mountain ranges

Landslides are common throughout the Ecuadorian Andes, but their causal and controlling factors and their roles in landform development have not yet been systematically investigated. This paper reports observations and hypotheses arising from a reconnaissance study of the Tandayapa Valley in the Cordillera Occidental, approximately 30 km west of Quito. This study area is characterised by high local relief (ca. 800 m) associated with dissected mountainous terrain, high annual rainfall (>2,000 mm), and secondary-succession wet montane ‘cloud forest’. Regolith cover is extremely thin on the very steep (45 to >60°) upper main valley slopes, but there are thick accumulations of tephra on the slope crests and ridgetops. These deposits show periods of soil development separated by deposition events. Natural landslides in this environment comprise rare large deep-seated bedrock failures and occasional shallow failures on the steep upper slopes where potentially unstable thicknesses of tephra have accumulated. Landslides associated with construction of roads and forest trails are more common. Back-analysis of one road-cut landslide, using field and laboratory data to characterise the in situ weathered material where possible, indicated that natural shallow failures are unlikely in the absence of a surficial cover of tephra. By analogy with another mountainous tropical landscape, it is suggested that long-term landform development can be explained in terms of channel incision, driven by uplift, producing steep lower valley slopes that eventually exceed bedrock failure thresholds. Therefore, large deep-seated landslides appear to control valley slope form development, whilst the shallow landslides contribute to general denudation.     

Statistical analysis of landslide susceptibility at Yongin, Korea

The aim of this study is to evaluate the susceptibility of landslides at Yongin, Korea, using a geographic information system (GIS). Landslide locations were identified in the Yongin area from interpretation of aerial photographs, field surveys, and maps of the topography, soil type, timber cover, and geology. These data were collected and constructed into a spatial database using GIS. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, age, diameter, and density of timber were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM satellite image. Landslide susceptibility was analyzed using the landslide occurrence factors by probability and logistic regression methods. The results of the analysis were verified using the landslide location data. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide location. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy. The results can be used to reduce associated hazards, and to plan land use and construction.     

A time-space based approach for mapping rainfall-induced shallow landslide hazard

A rainfall-induced shallow landslide is a major hazard in mountainous terrain, but a time-space based approach is still an unsettled issue for mapping rainfall-induced shallow landslide hazards. Rain induces a rise of the groundwater level and an increase in pore water pressure that results in slope failures. In this study, an integrated infinite slope analysis model has been developed to evaluate the influence of infiltration on surficial stability of slopes by the limit equilibrium method. Based on this new integrated infinite slope analysis model, a time-space based approach has been implemented to map the distributed landslide hazard in a GIS (Geographic Information Systems) and to evaluate the shallow slope failure induced by a particular rainfall event that accounts for the rainfall intensity and duration. The case study results in a comprehensive time-space landslide hazard map that illustrates the change of the safety factor and the depth of the wetting front over time.     

岩溶山区崩滑灾害变形破坏地质模式分类

岩溶山区特殊的地质结构导致崩塌、滑坡等地质灾害时常发生,带来了严重的人员伤亡和经济社会损失。研究岩溶山区崩滑灾害特征,建立相应的变形破坏地质模式,对于岩溶山区崩滑灾害风险防控与治理工程具有重要理论意义与指导价值。文章以典型地质灾害形成演化过程为例,在系统地分析研究区典型崩滑灾害地质背景、影响因素、动力学与运动学特征的基础上,提出了岩溶山区崩滑灾害变形破坏地质模式,得出以下主要结论:（1）影响崩滑成灾基本因素（崩滑灾害体势能、岩溶结构面、岩组结构、斜坡地貌和斜坡结构）、影响因素（水文地质条件、工程活动、地震、降雨）和变形运动特征（运动形式和变形机制）三个方面,据此建立了岩溶山区崩滑灾害地质分类指标体系。（2）结合研究区特征对模型体系里面的每个要素进行系统分析,崩滑灾害的发生是各个要素相互组合、相互作用的结果。（3）总结了研究区内5种典型崩滑地质模式:高势能反倾降雨型高速远程滑坡—碎屑流模型、高势能斜倾视向采矿型高速远程崩滑灾害模型、超高势能横向陡倾地震型高速远程滑坡、高势能采矿型高速崩塌—碎屑流模型、低势能差异风化崩塌模型。为后续开展物理模拟、数值模拟、稳定性计算和变形破坏预测等工作奠定基础。下一步将更加深入全面地建立研究区的崩滑灾害模式,并进行崩滑灾害的危险性分级工作。      

国道213汶川—松潘段滑坡隐患遥感识别与易发性评价

国道213汶川—松潘段位于强震山区,滑坡灾害频发,每年都会因滑坡灾害导致交通中断,迫切需要查明沿线滑坡隐患的空间分布,并对其易发性进行评价。利用光学遥感和InSAR综合遥感技术对沿线滑坡隐患进行识别,共识别滑坡隐患288处,其中InSAR探测出有形变的滑坡隐患点27处。以识别出的滑坡隐患为评价样本,选取高程、坡度、坡向、地表曲率、工程地质岩组、归一化植被指数(normalizied difference vegetation index,NDVI)、距道路距离、距河流距离、距断层距离等9个影响因素作为评价因子,采用Logistic回归模型评价该沿线滑坡隐患易发性,评价结果可为国道213汶川—松潘段滑坡灾害防治提供参考。     

The use of predictive modeling techniques for optimal exploitation of spatial databases: a case study in landslide hazard mapping with expert system-like methods

. A case study is presented in which different probabilistic prediction models (Bayesian probability, fuzzy logic "and", "or", "sum", "product", "gamma" operations, and certainty factors) are used to produce landslide hazard maps for a hilly and mountainous region in the northern Apennines, Italy. Seven data layers are exploited to detect most vulnerable areas: lithology, distance from the geological lineaments, annual rainfall amount, land cover type, topographic slope and aspect, and the distance from hydrographic network segments. The results of the different predictions are compared using the prediction rate index and critically discussed, to evaluate the possibility of using readily available databases for land planning.     

Land use/cover change and driving force analyses in parts of northern Iran using RS and GIS techniques

To accomplish integrated watershed management and land use planning, it is necessary to study the dynamic spatial pattern of land use and cover change related to socioeconomical and physical parameters. In this study, land use and cover change detection was applied to the Lajimrood Drainage Basin in northern parts of Iran, an area characterized by rich and diversified agricultural and forest mosaic. The main of changes in the study area were forest–arable land transformation, which was only considered in this study. In order to detect these changes, at first, based on 1:25,000 digital topographic maps dated 1967 and 1994 and ETM⁺ satellite image dated 2002, land use map in these three dates were prepared. The results showed that the area with forest land use decreased about 3.2% in transition 1967–2002. Also, arable land increased about 36.9%. We suggested a method to analyze the driving forces and the spatial distribution of land use change. The maps of elevation, slope, and aspect were derived and classified by using digital elevation model (DEM). Also, the maps of distance from road, drainage network, and building area were selected as socioeconomical factors. These maps were overlaid and crossed with land use change map and land use change area ratio was computed. The results showed that the elevation, slope, and aspect were physical effective factors in land use changing. Also, by increasing the distance from building area and roads, deforestation rate was reduced.     

基于确定性系数的降雨型滑坡影响因子敏感性分析

本文选择东南沿海地区具有典型降雨型滑坡的淳安县作为研究区,在完成全县地质灾害详细调查的基础上,选取高程、坡度、坡向、曲率、工程地质岩组、距断层距离、距道路距离、土地利用和植被等9个滑坡影响因子,利用GIS技术与确定性系数分析方法,对这9个影响因子开展敏感性分析。研究结果表明:(1) 寒武、震旦、石炭和白垩系是滑坡易发地层,侵入岩组、紫红色砂岩、碳酸盐岩夹碎屑岩、碳酸盐岩为主的岩组是滑坡高敏感性岩组;滑坡受断层影响总体上随着距离断层由近及远逐渐降低;(2) 坡度范围10°~35°是滑坡的易发坡度,30°~35°滑坡数量达到峰值;SE和S等朝南坡向是滑坡最易发坡向;高程范围为100~200m是滑坡最易发区间;凹坡最易发生滑坡,而凸坡则滑坡敏感性最差;非林地、茶叶、竹林和经济林等是滑坡高敏感植被类型;(3) 住宅用地、耕地、园地等与人类活动密切相关的用地类型是滑坡易发地类;距道路距离因子对滑坡敏感性低,相关性不明显。上述各滑坡影响因子最利于滑坡发生的数值区间确定,将为研究区进一步开展降雨型滑坡区域易发性评价及预测奠定基础。