Evaluation of spatial probability of landslides using bivariate and multivariate approaches in the Goriganga valley,Kumaun Himalaya,India

Natural Hazards - In this study, new hybrid artificial neural network (ANN) models were used for predicting the groundwater resource index. The salp swarm algorithm (SSA), particle swarm...     

aiNet- and GIS-based regional prediction system for the spatial and temporal probability of rainfall-triggered landslides

We developed a real-time forecasting system, aiNet-GISPSRIL, for evaluating the spatiotemporal probability of occurrence of rainfall-triggered landslides. In this system, the aiNet (a kind of artificial neutral network based on a self-organizing system) and GIS are merged for integrating the rainfall conditions into various environmental factors that influence the landslide occurrence and for simulating the complex non-linear relationships between landslide occurrence and its related conditions. Zhejiang Province (101,800 km² in area), located in the southeast coastal region of China, is highly prone to the occurrence of landslides during intensive rainfall. Since 2003, the aiNet-GISPSRIL has been used to predict landslides during the rainy seasons in the region. The aiNet-GISPSRIL uses the regional 24-h forecast rainfall information and the real-time rainfall monitoring data from the rain-gauge network as its inputs, and then provides 24-h forecast of the landslide probability for every 1 × 1-km grid cell within the region. Verification studies on the performance of the aiNet-GISPSRIL show that the system has successfully predicted the dates and localities of 304 landslides (accounting for 66.2% of reported landslides during the period). During the period from 2003 to 2007, because the system provided the probability levels of landslide occurrences up to 24-h in advance, gave locations of potential landslides, and timely warned those individuals at high-risk areas, more than 1700 persons living in the risk sites had been evacuated to safe ground before the landslides occurred and thus casualty was avoided. This highly computerized, easy-operating system can be used as a prototype for developing forecasting systems in other regions that are prone to rainfall-triggered landslides.     

Spatial prediction of wildfire probability in the Hyrcanian ecoregion using evidential belief function model and GIS

Accurate estimates of wildfire probability and production of distribution maps are the first important steps in wildfire management and risk assessment. In this study, geographical information system (GIS)-automated techniques were integrated with the quantitative data-driven evidential belief function (EBF) model to predict spatial pattern of wildfire probability in a part of the Hyrcanian ecoregion, northern Iran. The historical fire events were identified using earlier reports and MODIS hot spot product as well as by carrying out multiple field surveys. Using the GIS-based EBF model, the relationships among existing fire events and various predictor variables predisposing fire ignition were analyzed. Model results were used to produce a distribution map of wildfire probability. The derived probability map revealed that zones of moderate, high, and very high probability covered nearly 60% of the landscape. Further, the probability map clearly demonstrated that the probability of a fire was strongly dependent upon human infrastructure and associated activities. By comparing the probability map and the historical fire events, a satisfactory spatial agreement between the five probability levels and fire density was observed. The probability map was further validated by receiver operating characteristic using both success rate and prediction rate curves. The validation results confirmed the effectiveness of the GIS-based EBF model that achieved AUC values of 84.14 and 81.03% for success and prediction rates, respectively.     

Assessing flood inundation mapping through estimated discharge using GIS and HEC-RAS model

Water discharge is the main parameter in hydraulic modeling for flood hazard assessment. However, the unavailability of data on discharge and observed river morphologies resulted in erroneous calculations and irregularities in flood inundation mapping. The objectives of this study are (i) to investigate uncertainties of hydraulic parameters (width, cross-sectional depth, and channel slope) used in discharge equation and (ii) to examine the influence of estimate discharge on water extent and flood depth with different boundary conditions on interferometric synthetic aperture radar (IFSAR) and modified IFSAR DEMs. Sensitivity analysis was conducted with the Monte Carlo simulation method to generate random data combinations. Bjerklie’s equation was used to calculate discharge based on the three variables, and Manning’s n was substituted into the Hydrologic Engineering Center River Analysis System (HEC-RAS) model. TerraSAR-X was used to distinguish existing flood water bodies and normal water extent. The uncertainty of the combined variables was assessed with the likelihood measures such as F-statistic, mean absolute error, root mean square error, and Nash–Sutcliffe efficiency which compares observed and predicted inundated area as well as flood water depth simulated using the HEC-RAS model.     

Risk assessment of snowmelt-induced landslides based on GIS and an effective snowmelt model

Natural Hazards - In early 2008, southern China experienced a severe freezing snow event, causing many geological disasters (such as landslides). Based on combining the infinite slope model and the...     

Groundwater study using remote sensing and geographic information systems (GIS) in the central highlands of Eritrea

Remote sensing, evaluation of digital elevation models (DEM), geographic information systems (GIS) and fieldwork techniques were combined to study the groundwater conditions in Eritrea. Remote sensing data were interpreted to produce lithological and lineament maps. DEM was used for lineament and geomorphologic mapping. Field studies permitted the study of structures and correlated them with lineament interpretations. Hydrogeological setting of springs and wells were investigated in the field, from well logs and pumping test data. All thematic layers were integrated and analysed in a GIS. Results show that groundwater occurrence is controlled by lithology, structures and landforms. Highest yields occur in basaltic rocks and are due to primary and secondary porosities. High yielding wells and springs are often related to large lineaments, lineament intersections and corresponding structural features. In metamorphic and igneous intrusive rocks with rugged landforms, groundwater occurs mainly in drainage channels with valley fill deposits. Zones of very good groundwater potential are characteristic for basaltic layers overlying lateritized crystalline rocks, flat topography with dense lineaments and structurally controlled drainage channels with valley fill deposits. The overall results demonstrate that the use of remote sensing and GIS provide potentially powerful tools to study groundwater resources and design a suitable exploration plan.The online version of the original article can be found at     

Groundwater study using remote sensing and geographic information systems (GIS) in the central highlands of Eritrea

Remote sensing, evaluation of digital elevation models (DEM), geographic information systems (GIS) and fieldwork techniques were combined to study the groundwater conditions in Eritrea. Remote sensing data were interpreted to produce lithological and lineament maps. DEM was used for lineament and geomorphologic mapping. Field studies permitted the study of structures and correlated them with lineament interpretations. Hydrogeological setting of springs and wells were investigated in the field, from well logs and pumping test data. All thematic layers were integrated and analysed in a GIS. Results show that groundwater occurrence is controlled by lithology, structures and landforms. Highest yields occur in basaltic rocks and are due to primary and secondary porosities. High yielding wells and springs are often related to large lineaments, lineament intersections and corresponding structural features. In metamorphic and igneous intrusive rocks with rugged landforms, groundwater occurs mainly in drainage channels with valley fill deposits. Zones of very good groundwater potential are characteristic for basaltic layers overlying lateritized crystalline rocks, flat topography with dense lineaments and structurally controlled drainage channels with valley fill deposits. The overall results demonstrate that the use of remote sensing and GIS provide potentially powerful tools to study groundwater resources and design a suitable exploration plan.An erratum to this article can be found at     

Acquiring high-resolution topography and performing spatial analysis of loess landslides by using low-cost UAVs

The Loess Plateau is a region in China prone to frequent geological disasters, where thousands of loess landslides can be found. Conventional field survey methods are inadequate for the requirements of fine spatial analysis of landslides. Due to its numerous advantages (fast, efficient, low cost, safe, and able to acquire high-resolution data), structure from motion (SfM) technique to photogrammetric orientation of flights and modeling applied to photographs taken by unmanned aerial vehicles (UAVs) equipped with a camera has become a powerful new tool for the generation of high-resolution topography that has emerged in recent years, which has become a powerful new technique for acquiring high-resolution topographic data. In this study, we conducted nearly two months of field UAV surveys of loess landslides on the Loess Plateau, eventually established 3D digital models for 11 loess landslides, and produced high-resolution digital orthophoto maps (DOMs) and digital elevation models (DEMs). High-resolution spatial analysis of the loess landslides (mainly including characteristic parameter extraction, topography profile analysis, surface feature analysis, and hydrologic analysis) was performed using Agisoft PhotoScan, ArcGIS 10.2, Global Mapper 17, and Origin Pro 9.0. The UAV technique allows us to further understand the micro-level internal spatial and structural characteristics of loess landslides. Moreover, not only does it allow us to accurately measure the characteristic geometric parameters but also enables us to detect the surface details of loess landslides (e.g., textures, fissures, and micro-landforms). Manifestly, we can also deduce the original structural characteristics and possible inducement mechanism of landslides based on a combination of high-resolution data acquired by UAVs, proper ground surveys, and theoretical knowledge. In summary, the low-cost UAVs are highly and especially suitable for surveys and digital terrain analysis of landslides on the Loess Plateau with sparse vegetation.     

Assessing soil erosion in Mediterranean karst landscapes of Lebanon using remote sensing and GIS

Maps showing the potential for soil erosion at 1:100,000 scale are produced in a study area within Lebanon that can be used for evaluating erosion of Mediterranean karstic terrain with two different sets of impact factors built into an erosion model. The first set of factors is: soil erodibility, morphology, land cover/use and rainfall erosivity. The second is obtained by the first adding a fifth factor, rock infiltration. High infiltration can reflect high recharge, therefore decreasing the potential of surface runoff and hence the quantity of transported materials. Infiltration is derived as a function of lithology, lineament density, karstification and drainage density, all of which can be easily extracted from satellite imagery. The influence of these factors is assessed by a weight/rate approach sharing similarities between quantitative and qualitative methods and depending on pair-wise comparison matrix.The main outcome was the production of factorial maps and erosion susceptibility maps (scale 1:100,000). Spatial and attribute comparison of erosion maps indicates that the model that includes a measure of rock infiltration better represents erosion potential. Field investigation of rills and gullies shows 87.5% precision of the model with rock infiltration. This is 17.5% greater than the precision of the model without rock infiltration. These results indicate the necessity and importance of integrating information on infiltration of rock outcrops to assess soil erosion in Mediterranean karst landscapes.     

Doline probability map using logistic regression and GIS technology in the central Ebro Basin (Spain)

In the surroundings of Zaragoza, karstification processes are especially intense in covered karst areas where fluvial terraces lie directly on Tertiary evaporites. Since the beginning of Quaternary, these processes have lead to the development of collapse and subsidence dolines with a wide range of sizes, which have significant economic impacts. To reduce economic impact and increase safety, a regional analysis of this phenomenon is needed for spatial management. Therefore, a probability map of dolines was developed using logistic regression and geographic information system (GIS) techniques. This paper covers the selection of input data, manipulation of data using the GIS technology, and the use of logistic regression to generate a doline probability map. The primary variable in the doline development in this area is geomorphology, represented by the location of endorheic areas and different terrace levels. Secondary variables are the presence of irrigation and the water table gradient.     

基于GIS技术的甘肃省区位优势度分析

区位优势度是反映区域经济、社会发展的重要指标。基于网格评分的思想,建立区位优势度模型,利用GIS技术对甘肃全省范围进行无缝网格的定量分析。确立交通网络密度、交通干线影响度和城镇影响度三个评价指标,分析甘肃省境内综合区位优势状况。结果表明：省内大部分区域区位优势度处于较低水平,占省域面积的86.88%。只有极少数地区较高,占省域面积的0.5%,中等区位优势度地区占面积12.62%,甘肃省综合优势度区域差异显著,兰州区位优势度最高,为0.86,阿克塞哈萨克族自治县区位优势度最低,接近0。综合区位优势度较高区域依然沿陇海-兰新线和主要交通干线分布,中东部地区优势度明显高于西部廊道区域。中东部主要以兰州为中心,在陇海-兰新线东西方向上的区位优势逐渐延伸并减弱,向西途经武威、金昌、张掖等城镇,向东经定西市和天水市,以及向东北方向的白银市;西部主要以酒嘉地区为核心,向东延伸至张掖、金昌等城镇,向西至瓜州县,并向敦煌南向延伸。     

基于真三维GIS的地质构造模型与空间分析

带有断层的地质体建模难于层状地层,是当前研究的难点,模型完成后的三维空间分析功能目前也处于研究阶段,是当前研究的热点.以某石膏矿为例,介绍了利用存在地层倒转、地层缺失等复杂钻孔数据进行三维建模的流程以及模型建立后的三维空间分析方法和地学应用,尝试了三维GIS空间-属性查询、空间裁剪、纵剖面横切面的自动生成方法和实例研究.结果表明,地质体和构造的特征的三维建模和空间分析有利于地质演化的理解和开采设计的优化.     

三峡库区泄滩滑坡渗流场与应力场耦合分析

随着大规模梯级水电工程的不断发展,库岸滑坡的稳定性及潜在的涌浪灾害将是影响水电工程(群)全生命周期安全运行的关键因素。本文分别从库岸边坡稳定性及滑坡涌浪研究两个方面,对目前国内外的相关研究成果进行了系统总结和分析。在库岸边坡稳定性研究方面,越来越多的研究集中于降雨、库水位变动等水动力环境下的库岸边坡的水-岩耦合作用及稳定性演化的分析方法方面。通过对滑坡涌浪的物理模型试验法、解析法及数值模拟法3大类方法的优缺点分析,随着数值计算技术的飞速发展其在滑坡涌浪链生灾害动力学分析方面体现出其强大的生命力。库岸滑坡从渐进破坏→启动→高速运动、涌浪→堆积、涌浪传播与爬坡等构成了滑坡涌浪灾害链的不同阶段,也是一个连续的灾害过程,而不同阶段灾害特点又有很大的差异。然而,目前通常将库岸滑坡稳定性分析和涌浪分析分割开来,从而不能很好地反应这一灾害链过程。基于高性能数值计算技术,从全过程的物理力学机制出发构建灾害链的模拟和分析方法,将是目前的发展趋势,也是从解决库岸滑坡涌浪链生灾害动力学分析的关键。     

Scenario-based quantitative human vulnerability assessment of site-specific landslides using a probabilistic model

Landslides - Ensuring the safety of personnel and providing practical escape routes for potential victims play essential roles in reducing the human vulnerability to site-specific landslides....     

基于GIS的广东省滑坡灾害区划研究

以广东省小流域分布图为底图,在详细收集全省历史滑坡及现代滑坡资料的基础上,编制了全省滑坡灾害分布图,在ArcGIS8 3平台上,首先将两图进行空间叠加,生成了全省滑坡灾害易发程度分区图,以此分区图与广东省地形坡度、地层岩性、地貌分布、降雨分布图叠加分析,结果表明:广东省滑坡灾害易发区主要发生在地形坡度在10°～45°之间,地貌分布多为中、小起伏山地以及丘陵地区,地层岩性多为极硬、次硬及软硬相间岩层,以及高降雨区。     

Assessing spatial uncertainty in mapping soil erodibility factor using geostatistical stochastic simulation

Soil erosion is one of most widespread process of degradation. The erodibility of a soil is a measure of its susceptibility to erosion and depends on many soil properties. Soil erodibility factor varies greatly over space and is commonly estimated using the revised universal soil loss equation. Neglecting information about estimation uncertainty may lead to improper decision-making. One geostatistical approach to spatial analysis is sequential Gaussian simulation, which draws alternative, equally probable, joint realizations of a regionalised variable. Differences between the realizations provide a measure of spatial uncertainty and allow us to carry out an error analysis. The objective of this paper was to assess the model output error of soil erodibility resulting from the uncertainties in the input attributes (texture and organic matter). The study area covers about 30 km² (Calabria, southern Italy). Topsoil samples were collected at 175 locations within the study area in 2006 and the main chemical and physical soil properties were determined. As soil textural size fractions are compositional data, the additive-logratio (alr) transformation was used to remove the non-negativity and constant-sum constraints on compositional variables. A Monte Carlo analysis was performed, which consisted of drawing a large number (500) of identically distributed input attributes from the multivariable joint probability distribution function. We incorporated spatial cross-correlation information through joint sequential Gaussian simulation, because model inputs were spatially correlated. The erodibility model was then estimated for each set of the 500 joint realisations of the input variables and the ensemble of the model outputs was used to infer the erodibility probability distribution function. This approach has also allowed for delineating the areas characterised by greater uncertainty and then to suggest efficient supplementary sampling strategies for further improving the precision of K value predictions.