Spatial probabilistic modeling of slope failure using an integrated GIS Monte Carlo simulation approach

Spatial probabilistic modeling of slope failure using a combined Geographic Information System (GIS), infinite-slope stability model and Monte Carlo simulation approach is proposed and applied in the landslide-prone area of Sasebo city, southern Japan. A digital elevation model (DEM) for the study area has been created at a scale of 1/2500. Calculated results of slope angle and slope aspect derived from the DEM are discussed. Through the spatial interpolation of the identified stream network, the thickness distribution of the colluvium above Tertiary strata is determined with precision. Finally, by integrating an infinite-slope stability model and Monte Carlo simulation with GIS, and applying spatial processing, a slope failure probability distribution map is obtained for the case of both low and high water levels.     

Validation of Landslide Susceptibility Maps; Examples and Applications from a Case Study in Northern Spain

A procedure for validating landslide susceptibility maps wasapplied in a study area in northern Spain and the results obtained compared. Validationwas used to carry out sensitivity analysis for individual variables and combinationsof variables. The validity of different map-making methods was tested, as well as theutility of different types of Favourability Functions. The results obtained show thatvalidation is essential to determine the predictive value of susceptibility maps. Italso helps to better select the most suitable function and significant variables, thus improving the efficiency of the mapping process. Validation based on a temporal strategy makes it possible to derive hazard maps from susceptibility maps.     

斜向坡变形破坏机制的数值模拟研究

本文讨论了斜向坡的旋转式变形和破坏机制，用有限元法计算了此种斜坡中的剩余下滑力的分布方式，并以此来解释在滑动过程中发生一定旋转的原因；论文还运用离散元法，模拟了此种滑坡的滑动过程。     

某滑坡区滑带土工程地质特性研究

本文论述了某滑坡滑带土的工程地质特性及其滑坡稳定性的影响，为滑坡的合理整治提供了依据。     

露天矿边坡实用型专家系统PESOPS V1.0的设计与应用

结合边坡工程和岩质边坡普遍存在的问题，建造了一个露天矿边坡实用型专家系统ＰＥＳＯＰＳ Ｖ１．０。介绍了滑坡预报子系统的原理和方法，通过应用实例表明该子系统适用性强，预报可靠、使用方便。     

Data driven bivariate landslide susceptibility assessment using geographical information systems: a method and application to Asarsuyu catchment, Turkey

In the last decades, landslide hazard assessment has attracted many researchers' attention. A number of parameters are suggested to be responsible to quantitatively explain the mechanism of landslides; many of these parameters are very important and factual. However, some data types and models are site-specific and could not be applied to different locations. Furthermore, the data stored in continuous parameter maps are divided into a number of classes arbitrarily, depending on the vision of the expert. Basically, this division controls the result of bivariate analysis. Besides, the responsible portion of the parameter map controlling the mechanism is also weighted arbitrarily. Based on these two facts, the class boundaries put a prejudice on the produced susceptibility/hazard maps, which result in dependence on the knowledge of the user rather than being dependent on the data and the fact itself. The aim of this study is to refine the previously defined methods in a more data-dependent trend. To achieve this goal, two new concepts: seed cells and percentile maps are introduced. Seed cells are the zones that are considered to represent the best undisturbed morphological decision rules (conditions before landslide occurs) and would be achieved by adding a buffer zone to the crown and flank areas of the landslide. To quantitatively classify the input parameter maps, the data distributions of seed cells in the parameter maps are divided into a number of classes on the basis of their distribution's percentile break-points upon which the parameter maps are directly dependent on the seed cell distributions, hence to the data itself.     

Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.     

Doing groups: Situating knowledge and creating stories

This paper presents group research as a potentially powerful research tool for cultural geographers interested in the ways knowledge is produced at the interpersonal level. I argue that groups can create unique research spaces that incorporate 'sociality', the everyday social norms, logics and languages that guide ordinary conversations, into the research agenda. By concentrating on these discursive norms, insights can be obtained into the ways that knowledge is negotiated, produced and constrained in different places. To demonstrate the value of group research, a case study involving Australian environmentalists is analysed, to show how forests are constructed, contested and naturalised within this particular subculture. The article concludes by emphasising the importance of group research to critical geographers interested in social empowerment and change.     

Geographical knowledge and policy: the positive contribution of discourse studies

The 'discursive turn' has been blamed for a lack of engagement between geographers and policymakers. This paper argues that such a view is fundamentally flawed. It ignores the positive contribution that discourse analysis has made to policy studies and the particular role that geographers have played in developing such analyses. It is based on a misconceived view of the policy process and how knowledge can contribute to policy outcomes. A closer attention to policy discourses reveals exactly how knowledge is constructed within the policy process and can help identify how policy may be improved through discursive means.