modeling susceptibility to landslides using the weight of evidence approach western colorado usa abstract the paonia mcclure pass area of colorado is well known for active mass movements we examined 735 active shallow movement features including debris flows debris slides rock slides and soil slides in this area identification of the hazardous areas is a fundamental component of disaster management and an important basis for promoting safe human occupation and infrastructure development in landslide prone areas bayes theorem based on the weight of evidence woe was used to create a map of landslides that could be hazardous the modeling was accomplished by employing a geographical information system gis and a statistical package seventeen factors that cause landslides were measured and weighted using the woe method to create a map of areas susceptible to landslides the maps of weighted factors were summed on a pixel by pixel basis after performing chi square tests to determine factors that are conditionally independent of each other by combining factors that represent topography hydrology geology land cover and human influences six models were developed the performance of each model was evaluated by the distribution of the observed landslides the validity of the best map was checked against landslides which were not entered in the analysis the resulting map of areas susceptible to landslides has a prediction accuracy of 78

landslide characteristics and slope instability modeling using gis lantau island hong kong steep terrain and high a frequency of tropical rainstorms make landslide occurrence on natural terrain a common phenomenon in hong kong this paper reports on the use of a geographical information systems gis database compiled primarily from existing digital maps and aerial photographs to describe the physical characteristics of landslides and the statistical relations of landslide frequency with the physical parameters contributing to the initiation of landslides on lantau island in hong kong the horizontal travel length and the angle of reach defined as the angle of the line connecting the head of the landslide source to the distal margin of the displaced mass are used to describe runout behavior of landslide mass for all landslides studied the horizontal travel length of landslide mass ranges from 5 to 785 m with a mean value of 43 m and the average angle of reach is 27 7 this gis database is then used to obtain a logistic multiple regression model for predicting slope instability it is indicated that slope gradient lithology elevation slope aspect and land use are statistically significant in predicting slope instability while slope morphology and proximity to drainage lines are not important and thus excluded from the model this model is then imported back into the gis to produce a map of predicted slope instability the results of this study demonstrate that slope instability can be effectively modeled by using gis technology and logistic multiple regression analysis

a subjective and objective integrated weighting method for landslides susceptibility mapping based on gis the purpose of this study is to present a weighting method integrating subjective weight with objective weight for landslides susceptibility mapping based on geographical information system gis first the landslide inventory aspect slope proximity to streams of drainage network proximity to railway proximity to road topography elevation lithology tectonic activity and annual precipitation including their subclasses were taken as independent landslide causal factors second objective weights of the causal factors were calculated according to the landslide area density based on entropy weighting method and key factors were selected according to the rank of the objective weights third trapezoidal fuzzy number weighting approach was used to assess the sub classes of each key factor finally a case study was carried out in guizhou province china a landslide susceptibility map was created using weighted linear combination model based on gis using a predicted map of probability the study area was classified into four categories of landslide susceptibility low moderate moderate high and high

using multiple logistic regression and gis technology to predict landslide hazard in northeast kansas usa abstract landslides in the hilly terrain along the kansas and missouri rivers in northeastern kansas have caused millions of dollars in property damage during the last decade to address this problem a statistical method called multiple logistic regression has been used to create a landslide hazard map for atchison kansas and surrounding areas data included digitized geology slopes and landslides manipulated using arcview gis logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides given local slopes and geologic units results indicated that slope is the most important variable for estimating landslide hazard in the study area geologic units consisting mostly of shale siltstone and sandstone were most susceptible to landslides soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression soil types were highly correlated with the geologic units and no significant relationships existed between landslides and slope aspect

evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the turbolo river catchment northern calabria italy abstract landslides are one of the most widespread natural hazards that cause damage to both property and life every year and therefore the spatial distribution of the landslide susceptibility is necessary for planning future developmental activities in this paper the artificial neural network ann technique is tested for developing a landslide susceptibility map in turbolo river catchment north calabria south italy landslides were mapped through air photo interpretation and field surveys by identifying both the landslide depletion zones dzs and accumulation zones azs and relevant geo environmental thematic layers pertaining to landslide predisposing factors were generated using air photo interpretation field surveys and geographic information system gis tools ten predisposing factors were related to the occurrence of landslide lithology faults land use drainage network and a series of topographic factors elevation slope aspect plan curvature topographic wetness index twi and stream power index spi in order to evaluate and validate landslide susceptibility the dzs were divided in two groups using a random partition strategy the first group training set was used to prepare the susceptibility map employing a back propagation learning algorithm in the idrisi taiga software the second group testing set was used to validate the landslide susceptibility model using the confusion matrix and the receiver operating characteristic roc curve the susceptibility map was classified into five susceptibility classes very low low moderate high and very high about 46 of the study area falls in high to very high susceptible classes and most of the dzs mapped 87 3 occur in the same classes the validation results showed satisfactory agreement between the susceptibility map and the dzs locations over 85 of the dzs of the validation set are correctly classified falling in high and very high susceptibility areas also the roc curve had shown an area under curve auc value of 0 90 which demonstrates the robustness and good reliability of the landslide susceptibility model according to these results we conclude that the map produced by the artificial neural network is reliable and the methodology applied in the study produced high performance and satisfactory results which may be useful for land planning policy

autologistic modelling of susceptibility to landsliding in the central apennines italy in previous research a logistic regression of landslide occurrence on several explanatory variables was fitted and used to map landslide susceptibility for a small area in the central apennines italy here the spatial dependence or spatial correlation in the residuals from the fitted regression model was accounted for by inserting an autocovariate into the model the autocovariate was estimated by applying a gibbs sampler to the susceptibilities for neighbouring pixels as in any landslide susceptibility analysis accuracy was difficult to assess because of the requirement for data on future landslides however by comparing the ordinary logistic model to the autologistic model obtained on the same set of data it was possible to assess the influence of the autocovariate the autocovariate rendered the model simpler because several variables lost their significance and were therefore omitted from the model further areas of high landslide susceptibility estimated from the autologistic model were geographically clustered as one would expect and this may be advantageous in terms of i interpreting the model and ii displaying the results to non experts

lidar supported prediction of slope failures using an integrated ensemble weights of evidence and analytical hierarchy process the present study investigates a potential application of different resolution topographic data obtained from airborne lidar and an integrated ensemble weight of evidence and analytic hierarchy process woe ahp model to spatially predict slope failures previously failed slopes of the pellizzano italy were remotely mapped and divided into two subsets for training and testing purposes 1 2 5 10 15 and 20 m topographic data were processed to extract nine terrain attributes identified as conditioning factors for landslides slope degree aspect altitude plan curvature profile curvature stream power index topographic wetness index sediment transport index and topographic roughness index landslide slope failure susceptibility maps were produced using a single woe model 1 an ensemble woe ahp model that used all conditioning factors model 2 and an ensemble woe ahp model that only used highly nominated conditioning factors model 3 the validation results proved the efficiency of high resolution 5 m topographic data and the ensemble model particularly when all factors were used in the modeling process model 2 the average success rates and prediction rates for model 2 that used 5 m resolution datasets were 84 26 and 82 78 respectively the finding presented in this paper can aid in planning more efficient lidar surveys and the handling of large datasets and in gaining a better understanding of the nature of the predictive models

observations and modeling of alongshore variability in dune erosion at egmond aan zee the netherlands abstract dunes can erode within a few hours when exposed to high storm surge levels and large waves if the dunes are the primary defense such as in the netherlands this could result in flooding of the hinterland when dunes breach models are often used to analyze how dunes will respond to extreme conditions but they can also be applied to study milder events and with that gain more insight in the processes of dune erosion there is however growing demand for validating existing models under field conditions here we calibrate the xbeach dune erosion model with pre and post storm topography measurements of the dune erosion event in january 2012 at egmond aan zee the netherlands furthermore hydrodynamical data of the intertidal zone along a cross shore transect in the same area collected 3 months prior to the storm event are used to hydrodynamically calibrate and validate xbeach during the january 2012 storm the dune erosion was variable alongshore from the erosion of embryo dunes the forming of a dune scarp to considerable slumping of the entire dune face this caused the erosion volume v to range from 5 to 40 m3 m the calibrated model reproduces the alongshore variability in v with reasonable accuracy additional simulations show that the alongshore variation in v is due to variability on the initial dune topography primarily steepness and that variability in beach and nearshore bathymetry was of secondary importance

debris flow susceptibility mapping using frequency ratio and seed cells in a portion of a mountain international route dry central andes of argentina abstract debris flow and floods represent one of the main natural hazards that impact transport infrastructure causing serious damage economic losses and hinder regional economic development these processes are eventually associated with massive traffic cuts and direct damage to road structures to enable the prevention of such consequences this paper employs statistical modeling techniques various instability factors and geomorphological mapping to generate debris flow susceptibility maps in a portion of an important route on the dry andes of san juan in the agua negra river basin argentina a debris flows inventory map was prepared using satellite images and field checks the debris flows inventory was randomly divided into a model dataset 80 47 debris flows and remaining 20 12 debris flows data was used for validation purpose the instability factors chosen that influence debris flows occurrence were elevation slope angle slope aspect solar radiation topographic wetness index stream power index topographic position index melton ruggedness number terrain ruggedness index sediment transport capacity index plan curvature profile curvature lithology distance to road and proximity to stream using these factors six different models of debris flow susceptibility were calculated by frequency ratio fr lithology igneous complex was found to be important debris flows related factor in the study area the precision of the results was evaluated by receiver operating characteristic roc analysis according to the area under the curve auc the models of all flow track and natural breaks and all flow track and geometrical interval were 0 83 and 0 84 respectively showing a practically identical predictive capacity

comparison of the implementation of rock engineering system and analytic hierarchy process methods upon landslide susceptibility mapping using gis a case study from the eastern achaia county of peloponnesus greece as landslides are very common in greece causing serious problems to the social and economic welfare of many communities the implementation of a proper hazard analysis system will help the creation of a reliable susceptibility map his will help local communities to define a safe land use and urban development the purpose of this study is to compare the implementation of two semi quantitative landslide assessment approaches using landslide susceptibility maps compiled in a gis environment the compared methods are rock engineering system res and the analytic hierarchy process ahp for the landslide susceptibility analysis the northeastern part of the achaia county was examined this area suffers from many landslides because of its neighborhood with the tectonically active corinthian gulf and its geological setting neogene sediments flysch and other bedrock formations with local overthrusts ten parameters were used in both methodologies and each one was separated into five categories ranging from 0 to 4 representing their specific conditions derived from the investigation of the landslides in the western part of the study area ranking area a layer map was generated for each parameter using gis while the weighting coefficients of each methodology were used for the compilation of res and ahp final maps of the eastern part of the study area validating area by examining these two maps it is revealed that even though both correctly show the landslide status of the second site the res map reveals a better behavior in the spatial distribution of the various landslide susceptibility zones

gis based assessment of risk due to salt mining activities at tuzla bosnia and herzegovina ground subsidence triggered by salt mining from deposits located beneath the city of tuzla bosnia and herzegovina is one of the major dangers acting on a very densely urbanized area since 1950 when the salt deposit exploitation by means of boreholes began as demonstrated in this paper subsidence induced several hazard factors such as severe ground deformations the arising of deep and superficial fractures and a very fast water table rise connected with the brine extraction now affecting several districts the above mentioned factors have been quantified by the use of geomatic methodologies including field surveys and analysis of geographical data in order to estimate the historical sinking rates authors processed the large and never before processed amount of topographical data collected during two periods from 1956 to 1991 and from 1992 to 2003 with only poor data collected afterward traditional surveys were completely and definitively stopped the analysis reveals a cumulative subsidence as high as 12 m during the whole period causing damage to buildings and infrastructures within an area that includes a large portion of the historical town at present almost entirely destroyed modern sinking rates have been monitored with static gps whereas the presence of superficial fractures monitored with kinematic gps factors related to the presence of deep fractures and water table rise have been evaluated by curvature analysis techniques and piezometric data respectively finally hazard factors have been combined in a risk map using the gis geographical information system map algebra capabilities and a simple multicriteria decision analysis mda in order to do that a vulnerability map has been derived on the basis of information reported on a couple of recently sensed high resolution satellite imageries the final risk arisen from the combination of single hazard factors and vulnerability map highlights critical scenarios and unsuspected threatening that are under consideration by the local decision makers and urban planners in particular as highlighted in the final risk map the present day water table rise triggered by the decrease in brine pumping is seriously posing a threat to a portion of the city which is not the most involved in ground deformations

landslide susceptibility assessment using a novel hybrid model of statistical bivariate methods fr and woe and adaptive neuro fuzzy inference system anfis at southern zagros mountains in iran the aim of landslide susceptibility mapping lsm is to produce the most important and basic information required for overall landslide disaster planning and mitigation different statistical bivariate methods such as frequency ratio fr and weights of evidence woe have been widely used for lsm although results of these aforementioned statistical methods are generally acceptable however they can be improved further by fine tuning the conditioning factor s classes the purpose of this paper is to overcome some drawbacks of the bivariate models by developing a novel hybrid method using adaptive neuro fuzzy inference system anfis and statistical bivariate methods fr and woe in geographical information system the provinces of southern zagros mountains iran are chosen as a case study to implement the proposed method first landslide inventory map was produced using various data source such as historical landslides locations remote sensing images and land surveying techniques second the inventory data were divided into a ratio 70 30 for training and testing the models third twelve landslide conditioning and triggering factors such as altitude slope aspect plan and profile curvatures distance to roads distance to streams distance to faults rainfall seismicity land use and lithology were selected and categorized in two groups consisting of numerical and nominal values then each conditioning factor was classified and the weight of each class was determined by using fr and woe models the outputs of individual statistical and hybrid methods were applied to determine nominal and continuous numerical data respectively in the hybrid approach the calculated weights of each class were allocated to the center of each class and the rest of the weights were determined by anfis landslide locations which were not used in training the models were used for validation the produced susceptibility maps were validated and compared using area under the curve auc results indicated that predictive performances of hybrid models fr anfis and woe anfis have better performance than the statistical models fr and woe the aucs of success rates are 85 86 87 and 87 and the aucs of predicted rates are 82 82 85 and 84 for fr woe fr anfis and woe anfis respectively additionally frequency ratio plots frp and seed cells area index scai methods were also employed for a second round of validation the frp and scai graphs illustrated higher performance for the hybrid lsm models the proposed approach can be applied in other types of natural hazard modeling such as flood land subsidence and gully erosion

glacier fluctuations of jostedalsbreen western norway during the past 20 years the sensitive response of maritime mountain glaciers the steep outlet glaciers of jostedalsbreen western norway are good examples of sensitively reacting maritime mountain glaciers their changes in length frontal position and lower tongue s morphology during the past 20 years have been well documented at first they experienced a strong frontal advance after ad 2000 glacier behaviour was dominated by a strong frontal retreat in some cases causing a separation of the lowermost glacier tongue in this paper the glacier length changes are presented both visually and numerically supplemented by mass balance and meteorological data the glacier behaviour is interpreted and its causes are discussed whereas the factors controlling the advance during the 1990s seem clear the interpretation of the most recent retreat still leaves some uncertainties the actual glacier front behaviour cannot fully be related to the mass balance data terminus response times and relations between individual mass balance and meteorological parameters have changed some hypoth

frequency ratio model based landslide susceptibility mapping in lower mae chaem watershed northern thailand the purpose of this study is to produce a landslide susceptibility map for the lower mae chaem watershed northern thailand using a geographic information system gis and remotely sensed images for this purpose past landslide locations were identified from satellite images and aerial photographs accompanied by the field surveys to create a landslide inventory map ten landslide inducing factors were used in the susceptibility analysis elevation slope angle slope aspect lithology distance from lineament distance from drainage precipitation soil texture land use land cover lulc and ndvi the first eight factors were prepared from their associated database while lulc and ndvi maps were generated from landsat 5 tm images landslide susceptibility was analyzed and mapped using the frequency ratio fr model that determines the level of correlation between locations of past landslides and the chosen factors and describes it in terms of frequency ratio index finally the output map was validated using the area under the curve auc method where the success rate of 80 06 and the prediction rate of 84 82 were achieved the obtained map can be used to reduce landslide hazard and assist with proper planning of lulc in the future

magnitude frequency characteristics and preparatory factors for spatial debris slide distribution in the northern faroe islands abstract the faroe islands in the north atlantic ocean are highly susceptible to debris avalanches and debris flows originating from debris slide activity in shallow colluvial soils to provide data for hazard and risk assessment of debris avalanches and debris flows this study aims at quantifying the magnitude and frequency of their debris slide origins as well as identifying which preparatory factors are responsible for the spatial debris slide distribution in the landscape for that purpose a debris slide inventory was generated from aerial photo interpretation api fieldwork and anecdotal sources covering a 159 km2 study area in the northern faroe islands a magnitude cumulative frequency mcf curve was derived to predict magnitude dependant debris slide frequencies while preparatory factors responsible for spatial debris slide distribution were quantified through gis supported discriminant function analysis dfa nine factors containing geological lithology dip geomorphological slope angle altitude aspect plan and profile curvature and land use infield outfield sheep density information were included in the multivariate analysis debris slides larger than 100 m2 with magnitude expressed as topographic scar area can be predicted from the power law function y 936 26x 1 277 r2 0 98 while a physical explanation is preferred for the roll over pattern of smaller slope failures the dfa is able to correctly classify app 70 of the modeled terrain units into their pre determined stable unstable groups preparatory factors responsible for the spatial debris slide distribution are aspect slope angle sheep density plan curvature and altitude while influence of the remaining factors is negligible

gis techniques and statistical models in evaluating landslide hazard geographical information systems gis and numerical cartography may greatly facilitate the development and use of statistical models for the assessment of regional landslide hazard from a small drainage basin located in central italy relevant geological and geomorphological factors were collected and processed by applying gis technology in particular modules were used which both generate high fidelity digital terrain models and automatically partition the terrain into main slope units the resulting information was then analysed by discriminant analysis which enabled landslide hazard and risk to be evaluated in each slope unit although not lacking drawbacks the method proved to be a feasible and cost effective approach to landslide susceptibility assessment and mapping

statistical models for slope instability classification abstract statistical models for reliable hazard assessment of landslides in a given area are presented the models are based on information theory and regression analysis information theory is a branch of probability in which the most significant feature is unpredictability and regression analysis is based on simple statistical theory both methods of statistical prediction have been applied to slope instability to provide cross validation of the results a fortran 77 program for computer aided assessment of the landslide hazard has been developed the program considers the factors affecting the slope instability and history of past landslides of the area as its input the program also calculates the information and regression value in a given area and classifies the area into different grades of instability a case study of landslide hazard assessment of a 66 km2 area in parts of the alkananda valley the gharwal himalaya is presented the factors considered in the analysis are angle and height of the slope rock type and geological structures such as faults and thrusts the results obtained are illustrated in the form of landslide hazard maps the predicted results are compared by the above methods

landslide spatial susceptibility mapping by using gis and remote sensing techniques a case study in zigui county the three georges reservoir china landslides are one of the most destructive phenomena in nature and damage both property and lives every year in this paper a logistic regression model with datasets developed via a geographic information system and remotely sensed data was used to create a landslide spatial susceptibility map for the three gorges project reservoir region on the yangtze river in zigui county the five causative factors used in the logistic regression model were evaluated in different ways topographic slope and topographic aspect were derived from a topographical map at 1 50 000 scale bed rock slope relationship and lithology were obtained from a geological map at 1 50 000 scale and fractional vegetation cover fvc which represents the reduced frequency of landslides due to the vegetation canopy and ground cover and is also one of the most difficult parameters to estimate over broad geographic areas was generated using a back propagation neural network bpnn method based on cbers china brazil earth resources satellite data the results of which were compared with values measured in the field the obtained pearson correlation coefficient r was 0 899 then the fvc factor and the other four factors were used as the input to a logistic regression model by integrating the five factor maps in the geographical information system gis via pixel based computing the landslide spatial susceptibility map was obtained the study area was reclassified into four categories of landslide susceptibility severe moderate low and very low approximately 15 0 of the study area was identified as severe susceptibility and very low low and moderate susceptibility zones covered 21 8 41 7 and 21 5 of the area respectively these results have an accuracy of 78 90 thus by using a logistic regression model in a gis environment a spatial susceptibility map of landslides can be obtained and the regions in zigui county that are susceptible to landslides and need immediate protective and mitigation measures can be identified

assessment of shallow landslide susceptibility by means of multivariate statistical techniques several multivariate statistical analyses have been performed to identify the most influential geological and geomorphological parameters on shallow landsliding and to quantify their relative contribution a data set was first prepared including more than 30 attributes of 230 failed and unfailed slopes the performance of principal component analysis t test and one way test allowed a preliminary selection of the most significant variables which were used as input variables for the discriminant analysis the function obtained has classified successfully 88 5 per cent of the overall slope population and 95 6 per cent of the failed slopes slope gradient watershed area and land use appeared as the most powerful discriminant factors a landslide susceptibility map based on the scores of the discriminant function has been prepared for ensija range in the eastern pyrenees an index of relative landslide density shows that the results of the map are consistent copyright 2001 john wiley sons ltd language en

digital terrain modelling a review of hydrological geomorphological and biological applications the topography of a catchment has a major impact on the hydrological geomorphological and biological processes active in the landscape the spatial distribution of topographic attributes can often be used as an indirect measure of the spatial variability of these processes and allows them to be mapped using relatively simple techniques many geographic information systems are being developed that store topographic information as the primary data for analysing water resource and biological problems furthermore topography can be used to develop more physically realistic structures for hydrologic and water quality models that directly account for the impact of topography on the hydrology digital elevation models are the primary data used in the analysis of catchment topography we describe elevation data sources digital elevation model structures and the analysis of digital elevation data for hydrological geomorphological and biological applications some hydrologic models that make use of digital representations of topography are also considered

a gis based landslide susceptibility evaluation using bivariate and multivariate statistical analyses bivariate and multivariate statistical analyses were used to predict the spatial distribution of landslides in the cuyahoga river watershed northeastern ohio u s a the relationship between landslides and various instability factors contributing to their occurrence was evaluated using a geographic information system gis based investigation a landslide inventory map was prepared using landslide locations identified from aerial photographs field checks and existing literature instability factors such as slope angle soil type soil erodibility soil liquidity index landcover pattern precipitation and proximity to stream responsible for the occurrence of landslides were imported as raster data layers in arcgis and ranked using a numerical scale corresponding to the physical conditions of the region in order to investigate the role of each instability factor in controlling the spatial distribution of landslides both bivariate and multivariate models were used to analyze the digital dataset the logistic regression approach was used in the multivariate model analysis both models helped produce landslide susceptibility maps and the suitability of each model was evaluated by the area under the curve method and by comparing the maps with the known landslide locations the multivariate logistic regression model was found to be the better model in predicting landslide susceptibility of this area the logistic regression model produced a landslide susceptibility map at a scale of 1 24 000 that classified susceptibility into four categories low moderate high and very high the results also indicated that slope angle proximity to stream soil erodibility and soil type were statistically significant in controlling the slope movement

how wide is a road the association of roads and mass wasting in a forested montane environment a spatial data base of 1609 landslides was analysed using a geographic information system to determine landslide frequency in relation to highways a 126 km long transportation network in a 201km 2 area of humid tropical mountainous forested terrain in puerto rico was used in conjunction with a series of 20 buffer disturbance zones varying from 5 to 400 m in length measured perpendicular to the highways average landslide frequency in the study area at distances greater than 85 m from roads was about six landslides per square kilometre at distances of 85 m or less on either side of a highway landslide frequency was about 30 landslides per square kilometre on average this elevated disturbance rate affected 330 m 2 km 2 a 1 within the 170 m swath the mass wasting rate outside of the disturbance zone affected 40 m 2 km 2 a 1 these results indicate that the rate of mass wasting disturbance is increased from five to eight times in a 170 m wide swath along road corridors the lateral extent of the environmental impact of roads in the study area is greater than is commonly perceived the approach described herein demonstrates a simple method to assess the spatial association of mass wasting with highways 1997 by john wiley sons ltd

extraction of potential debris source areas by logistic regression technique a case study from barla besparmak and kapi mountains nw taurids turkey debris flow is one of the most destructive mass movements sometimes regional debris flow susceptibility or hazard assessments can be more difficult than the other mass movements determination of debris accumulation zones and debris source areas which is one of the most crucial stages in debris flow investigations can be too difficult because of morphological restrictions the main goal of the present study is to extract debris source areas by logistic regression analyses based on the data from the slopes of the barla besparmak and kapi mountains in the sw part of the taurids mountain belt of turkey where formation of debris material are clearly evident and common in this study in order to achieve this goal extensive field observations to identify the areal extent of debris source areas and debris material air photo studies to determine the debris source areas and also desk studies including geographical information system gis applications and statistical assessments were performed to justify the training data used in logistic regression analyses as representative a random sampling procedure was applied by using the results of the logistic regression analysis the debris source area probability map of the region is produced however according to the field experiences of the authors the produced map yielded over predicted results the main source of the over prediction is structural relation between the bedding planes and slope aspects on the basis of the field observations for the generation of debris the dip of the bedding planes must be taken into consideration regarding the slope face in order to eliminate this problem in this study an approach has been developed using probability distribution of the aspect values with the application of structural adjustment the final adjusted debris source area probability map is obtained for the study area the field observations revealed that the actual debris source areas in the field coincide with the areas having high probability values on this final map

geomorphological and historical data in assessing landslide hazard traditionally earth scientists assess landslide occurrence on the basis of geomorphological investigations carried out through aerial photograph interpretation and eldwork conversely local administrators primarily evaluate the impact of natural catastrophes such as landsliding on the basis of historical records and data owing to the substantial difference in the structure and spatial density of these two types of information it is dif cult to compare them directly and few investigators have attempted this we compared landslide information derived from geomorphological mapping and historical data in a pilot area the staffora river basin northern italy to do this we generated two multivariate statistical models where the dependent variable was either the mapped landslide deposits geomorphological model or the historical sites affected by landslide induced damage historical model by quantitatively comparing these two model maps we demonstrate that the geomorphological model performs better in terms of percentage of terrain units correctly predicted as stable or unstable the historical model underestimates landslide hazard mainly where human structures are lacking however it highlights slopes where landslide movements take place with a high frequency at the temporal scale of human life hence the joint use of these two models may facilitate the knowledge of the overall instability conditions of a given region and the identi cation of the landslides that are most frequently reactivated copyright 2003 john wiley sons ltd

landslide susceptibility assessment in lianhua county china a comparison between a random forest data mining technique and bivariate and multivariate statistical models abstract landslides are an important natural hazard that causes a great amount of damage around the world every year especially during the rainy season the lianhua area is located in the middle of china s southern mountainous area west of jiangxi province and is known to be an area prone to landslides the aim of this study was to evaluate and compare landslide susceptibility maps produced using the random forest rf data mining technique with those produced by bivariate evidential belief function and frequency ratio and multivariate logistic regression statistical models for lianhua county china first a landslide inventory map was prepared using aerial photograph interpretation satellite images and extensive field surveys in total 163 landslide events were recognized in the study area with 114 landslides 70 used for training and 49 landslides 30 used for validation next the landslide conditioning factors including the slope angle altitude slope aspect topographic wetness index twi slope length ls plan curvature profile curvature distance to rivers distance to faults distance to roads annual precipitation land use normalized difference vegetation index ndvi and lithology were derived from the spatial database finally the landslide susceptibility maps of lianhua county were generated in arcgis 10 1 based on the random forest rf evidential belief function ebf frequency ratio fr and logistic regression lr approaches and were validated using a receiver operating characteristic roc curve the roc plot assessment results showed that for landslide susceptibility maps produced using the ebf fr lr and rf models the area under the curve auc values were 0 8122 0 8134 0 7751 and 0 7172 respectively therefore we can conclude that all four models have an auc of more than 0 70 and can be used in landslide susceptibility mapping in the study area meanwhile the ebf and fr models had the best performance for lianhua county china thus the resultant susceptibility maps will be useful for land use planning and hazard mitigation aims

landslide hazard evaluation a review of current techniques and their application in a multi scale study central italy in recent years growing population and expansion of settlements and life lines over hazardous areas have largely increased the impact of natural disasters both in industrialized and developing countries third world countries have difficulty meeting the high costs of controlling natural hazards through major engineering works and rational land use planning industrialized societies are increasingly reluctant to invest money in structural measures that can reduce natural risks hence the new issue is to implement warning systems and land utilization regulations aimed at minimizing the loss of lives and property without investing in long term costly projects of ground stabilization government and research institutions worldwide have long attempted to assess landslide hazard and risks and to portray its spatial distribution in maps several different methods for assessing landslide hazard were proposed or implemented the reliability of these maps and the criteria behind these hazard evaluations are ill formalized or poorly documented geomorphological information remains largely descriptive and subjective it is hence somewhat unsuitable to engineers policy makers or developers when planning land resources and mitigating the effects of geological hazards in the umbria and marche regions of central italy attempts at testing the proficiency and limitations of multivariate statistical techniques and of different methodologies for dividing the territory into suitable areas for landslide hazard assessment have been completed or are in progress at various scales these experiments showed that despite the operational and conceptual limitations landslide hazard assessment may indeed constitute a suitable cost effective aid to land use planning within this framework engineering geomorphology may play a renewed role in assessing areas at high landslide hazard and helping mitigate the associated risk

susceptibility assessments of shallow earthflows triggered by heavy rainfall at three catchments by logistic regression analyses abstract sometimes regional meteorological anomalies trigger different types of mass movements in may 1998 the western black sea region of turkey experienced such a meteorological anomaly numerous residential and agricultural areas and engineering lifelines were buried under the flood waters besides the reactivation of many previously delineated landslides thousands of small scale landslides mostly the earthflow type occurred all over the region the earthflows were mainly developed in flysch type units which have already presented high landslide concentrations in this study three different catchments namely agustu egerci and kelemen were selected because they have the most landslide prone geological units of the region the purposes of the present study are to put forward the spatial distributions of the shallow earthflows triggered to describe the possible factors conditioning the earthflows and to produce the shallow earthflow susceptibility maps of the three catchments the unique condition units ucu were employed during the production of susceptibility maps and during statistical analyses the unique condition units numbered 4052 for the agustu catchment 13 241 for the egerci catchment and 12 314 for the kelemen catchment the earthflow intensity is the highest in the agustu catchment 0 038 flow ucu and lowest in the egerci catchment 0 0035 flow ucu logistic regression analyses were also employed however during the analyses some difficulties were encountered to overcome the difficulties a series of sensitivity analyses were performed based on some decision rules introduced in the present study considering the decision rules the proper ratios of ucu free from earthflow 0 ucu including the earthflow 1 for the agustu egerci and kelemen catchments were obtained as 3 6 and 5 respectively also a chart for the proper ratio selection was developed the regression equations from the selected ratios were then applied to the entire catchment and the earthflow susceptibility maps were produced the landslide susceptibility maps revealed that 15 of the agustu catchment 8 of the egerci catchment and 7 of the kelemen catchment have very high earthflow susceptibility and most of the earthflows triggered by the may 1998 meteorological event were found in the very high susceptibility zones

landslide hazard zonation using analytical hierarchy process along national highway 3 in mid himalayas of himachal pradesh india landslide zonation studies emphasize on preparation of landslide hazard zonation maps considering major instability factors contributing to occurrence of landslides this paper deals with geographic information system based landslide hazard zonation in mid himalayas of himachal pradesh from mandi to kullu by considering nine relevant instability factors to develop the hazard zonation map analytical hierarchy process was applied to assign relative weightages over all ranges of instability factors of the slopes in study area to generate landslide hazard zonation map layers in geographic information system were created corresponding to each instability factor an inventory of existing major landslides in the study area was prepared and combined with the landslide hazard zonation map for validation purpose the validation of the model was made using area under curve technique and reveals good agreement between the produced hazard map and previous landslide inventory with prediction accuracy of 79 08 the landslide hazard zonation map was classified by natural break classifier into very low hazard low hazard moderate hazard high hazard and very high landslide hazard classes in geographic information system depending upon the frequency of occurrence of landslides in each class the resultant hazard zonation map shows that 14 30 of the area lies in very high hazard zone followed by 15 97 in high hazard zone the proposed model provides the best fit classification using hierarchical approach for the causative factors of landslides having complex structure the developed hazard zonation map is useful for landslide preparedness land use planning and social economic and sustainable development of the region

a new technique for recognition of geological and geomorphological patterns in digital terrain models abstract we have developed a technique that recognizes monoclinal sedimentary strata showing strike ridge geomorphology and fluvial deposits from digital terrain models dtms this technique is efficient and reliable and may be expanded to analysis of other landforms techniques for rapid geomorphic analysis of dtms are becoming increasingly useful since digital stereoscopic spot data will soon be available worldwide our technique recognizes geomorphic elements in two steps first elementary objects including crests thalwegs and various slope types are classified from slope changes along n s e w nw se and ne sw profiles through pixels in the dtm image second grammatical pattern recognition is used to identify and map geomorphic forms from the succession of elementary objects

a gis based approach for gully erosion susceptibility modelling using bivariate statistics methods in the ourika watershed morocco gully erosion is an important environmental issue with severe impacts this study aimed to characterize gully erosion susceptibility and assess the capability of information value infval and frequency ratio fr models for its spatial prediction in ourika watershed of the high atlas region of morocco these two bivariate statistical methods have been used for gully erosion susceptibility mapping by comparing each data layer of causative factor to the existing gully distribution weights to the gully causative factors are assigned based on gully density gullies have been mapped through field surveys and google earth high resolution images lithofacies land use slope gradient length slope aspect stream power index topographical wetness index and plan curvature were considered predisposing factors to gullying the digitized gullies were randomly split into two parts sixty five percent 65 of the mapped gullies were randomly selected as training set to build gully susceptibility models while the remaining 35 cases were used as validation set for the models validation the results showed that barren and sparse vegetation lands and slope gradient above 50 were very susceptible to gully erosion the roc curve was used for testing the accuracy of the mentioned models the analysis confirms that the fr model auc 80 61 shows a better accuracy than infval model auc 52 07 the performance of the gully erosion susceptibility map constructed by fr model is greater than that of the map produced by infval model the findings proved that gis based bivariate statistical methods such as frequency ratio model could be successfully applied in gully susceptibility mapping in morocco mountainous regions and in other similar environments the produced susceptibility map represents a useful tool for sustainable planning conservation and protection of land from gully processes

landslide susceptibility map refinement using psinsar data abstract landslide susceptibility maps lsm are commonly used by local authorities for land use management and planning activities representing a valuable tool used to support decision makers in urban and infrastructural planning the accuracy of a landslide susceptibility map is affected by false negative and false positive errors which can decrease the reliability of this useful product in particular false negative errors are generally worse in terms of social and economic losses with respect to the losses associated with false positives in this paper we present a new technique to improve the accuracy of landslide susceptibility maps using permanent scatterer interferometric synthetic aperture radar psinsar data the proposed approach uses two different data sets acquired in ascending and descending geometry the ps velocity measured along the line of sight is re projected into a new velocity along the steepest slope direction v slope integration between the lsm and the ground deformation velocity map along the slope was performed using an empirical contingency matrix which takes into account the average v slope and the susceptibility degree obtained using the random forests algorithm the results show that the susceptibility degree increased in 56 41 km 2 of the study area the combination of psinsar data and the landslide susceptibility map lsm improved the prediction reliability of slow moving landslides which particularly affect urbanized areas the use of this procedure can be easily applied in different areas where psi data sets are available this approach will help planning and decision making authorities produce reliable landslide susceptibility maps correcting some of the lsm errors

spatial analysis of factors controlling the presence of closed depressions and gullies under forest application of rare event logistic regression abstract although numerous studies have reported on past geomorphic change it is a common difficulty to identify the relative role of driving human or climatic forces to that end the possibilities of rare events logistic regression are explored in a 1300 hectare large ancient forest in central belgium here 43 permanent gullies and 71 closed depressions were observed that were probably caused by an anthropogenically induced land use change in the past this human origin was confirmed for a limited number of case study areas by recent geomorphic research with dating and soil profile analysis the objective of this study is to analyze the factors controlling the position of all gullies and closed depressions in the study area and investigate their mutual relation this will indicate whether or not the results obtained for the small case study areas can be extrapolated to the rest of the geomorphic features found in the whole study area the obtained logistic regression models show that both anthropogenic and physical factors are important in the spatial distribution of both geomorphic features for the prediction of the occurrence of closed depressions anthropogenic factors are most important however the probability of finding a depression is larger close to reported prehistoric and roman archaeological sites on well developed undisturbed luvisols and on northeast to southeast facing slopes the local slope gradient of the soil surface is the most important factor in the multivariate model for predicting the presence of the permanent gullies the occurrence probability of permanent gullies is also larger on northeast to southeast facing slopes the anthropogenic factor expressed by the distance to the closed depressions is significant as a univariate model this suggests that a critical slope gradient is a prerequisite for gully incision but gully formation still needs to be triggered by a human induced land use change it can therefore be concluded that both the gullies and the closed depressions in the meerdaal forest are related to past human activity either directly through mining of loess or indirectly through runoff production on cropland this study also showed the potential of rare events logistic regression for analyzing the spatial pattern of geomorphological features in relation to environmental factors

regional seismic slope assessment improvements considering slope aspect and vertical ground motion abstract seismic slope stability assessments in active fault zones are very important prior to designing and constructing large engineering structures however in most previous regional scale analyses ground motion records are either used directly or replaced by empirical regression equations in this paper we present an improved regional seismic slope stability assessment method considering the vertical slope aspect and ground motion based on limit equilibrium models and finite element models best fit equations are obtained to calculate the sliding angle and factor of safety fos then a two stage integration process is applied to obtain the permanent displacement the new model has been tested in the chenghai active fault zone china under a seismic precautionary intensity of 9 and the results of the new model are compared with those of traditional infinite slope models the results show that ignoring the vertical ground motion and slope aspect leads to underestimation of co seismic landslide hazards on regional scales and the new model provides a more accurate index to evaluate co seismic slope behaviours in large areas

assessing subsidence susceptibility to coal mining using frequency ratio statistical index and mamdani fuzzy models evidence from raniganj coalfield india raniganj an important coalfield in india is susceptible to mining subsidence ejection of toxicants in the environment and huge subsurface destruction mining with opencast method poses a great risk to the surrounding areas of this coalfield anthropogenic and natural activities have caused ground movement leading to subsidence in raniganj coalfield existing knowledge on subsidence susceptibility to coal mining in raniganj coalfield is scant the study makes an attempt to analyze mining subsidence susceptibility in raniganj coalfield using site specific parameters we first prepared subsidence inventory map to identify old subsidence locations and to construct the model it was later utilized for validating the models fifteen site specific parameters related to subsidence were chosen to analyze coal mining subsidence frequency ratio fr statistical index si and mamdani fuzzy mf models were utilized to assess their effectiveness in preparing susceptibility map findings of the study revealed very high susceptibility in the central part high susceptibility in north western part and moderate susceptibility in the eastern part of raniganj coalfield low and very low susceptibility was found in those parts having largest area under vegetation and water bodies the models were validated through roc curve seed cell area index scai and spatially agreed area approach mamdani fuzzy model with highest success rate 87 and prediction accuracy 85 was found the best fit model for analyzing mining subsidence susceptibility the framework of the methodology will be instructive for analyzing susceptibility at different geographical locations

high resolution aquifer characterization using crosshole gpr full waveform tomography comparison with direct push and tracer test data limited knowledge about the spatial distribution of aquifer properties typically constrains our ability to predict subsurface flow and transport here we investigate the value of using high resolution full waveform inversion of cross borehole ground penetrating radar gpr data for aquifer characterization by stitching together gpr tomograms from multiple adjacent crosshole planes we are able to image with a decimeter scale resolution the dielectric permittivity and electrical conductivity of an alluvial aquifer along cross sections of 50 m length and 10 m depth a logistic regression model is employed to predict the spatial distribution of lithological facies on the basis of the gpr results vertical profiles of porosity and hydraulic conductivity from direct push flowmeter and grain size data suggest that the gpr predicted facies classification is meaningful with regard to porosity and hydraulic conductivity even though the distributions of individual facies show some overlap and the absolute hydraulic conductivities from the different methods direct push flowmeter grain size differ up to approximately one order of magnitude comparison of the gpr predicted facies architecture with tracer test data suggests that the plume splitting observed in a tracer experiment was caused by a hydraulically low conductive sand layer with a thickness of only a few decimeters because this sand layer is identified by gpr full waveform inversion but not by conventional gpr ray based inversion we conclude that the improvement in spatial resolution due to full waveform inversion is crucial to detect small scale aquifer structures that are highly relevant for solute transport

landslide susceptibility mapping based on support vector machine a case study on natural slopes of hong kong china abstract the support vector machine svm is an increasingly popular learning procedure based on statistical learning theory and involves a training phase in which the model is trained by a training dataset of associated input and target output values the trained model is then used to evaluate a separate set of testing data there are two main ideas underlying the svm for discriminant type problems the first is an optimum linear separating hyperplane that separates the data patterns the second is the use of kernel functions to convert the original non linear data patterns into the format that is linearly separable in a high dimensional feature space in this paper an overview of the svm both one class and two class svm methods is first presented followed by its use in landslide susceptibility mapping a study area was selected from the natural terrain of hong kong and slope angle slope aspect elevation profile curvature of slope lithology vegetation cover and topographic wetness index twi were used as environmental parameters which influence the occurrence of landslides one class and two class svm models were trained and then used to map landslide susceptibility respectively the resulting susceptibility maps obtained by the methods were compared to that obtained by the logistic regression lr method it is concluded that two class svm possesses better prediction efficiency than logistic regression and one class svm however one class svm which only requires failed cases has an advantage over the other two methods as only failed case information is usually available in landslide susceptibility mapping

relationships between tectonic and geomorphological linear features in the guadix baza basin southern spain linear elements of the landscape of the guadix baza basin southern spain were identified from a landsat tm image three important lineament trends have been identified in the guadix baza basin the first is ne sw which is the dominant trend in the basin the second is nw se and the third is ene wsw these three trends are correlated to the major faults of the guadix baza basin the study of linear features by the analysis of satellite data has revealed a strong link between the buried tectonic structures and the morphological features appearing at the surface the distribution and density of lineaments explains much of the morphology of the land surface it is possible to reconstruct elements of the tectonic and denudational history of the region and show that during quaternary times lineaments controlled the sedimentation of the basin and the drainage pattern copyright 1999 john wiley sons ltd

a comparative study of frequency ratio weights of evidence and logistic regression methods for landslide susceptibility mapping sultan mountains sw turkey abstract this study evaluated and compared landslide susceptibility maps produced with three different methods frequency ratio weights of evidence and logistic regression by using validation datasets the field surveys performed as part of this investigation mapped the locations of 90 landslides that had been identified in the sultan mountains of south western turkey the landslide influence parameters used for this study are geology relative permeability land use land cover precipitation elevation slope aspect total curvature plan curvature profile curvature wetness index stream power index sediment transportation capacity index distance to drainage distance to fault drainage density fault density and spring density maps the relationships between landslide distributions and these parameters were analysed using the three methods and the results of these methods were then used to calculate the landslide susceptibility of the entire study area the accuracy of the final landslide susceptibility maps was evaluated based on the landslides observed during the fieldwork and the accuracy of the models was evaluated by calculating each model s relative operating characteristic curve the predictive capability of each model was determined from the area under the relative operating characteristic curve and the areas under the curves obtained using the frequency ratio logistic regression and weights of evidence methods are 0 976 0 952 and 0 937 respectively these results indicate that the frequency ratio and weights of evidence models are relatively good estimators of landslide susceptibility in the study area specifically the results of the correlation analysis show a high correlation between the frequency ratio and weights of evidence results and the frequency ratio and logistic regression methods exhibit correlation coefficients of 0 771 and 0 727 respectively the frequency ratio model is simple and its input calculation and output processes are easily understood the interpretations of the susceptibility map reveal that geology slope steepness slope aspect and elevation played major roles in landslide occurrence and distribution in the sultan mountains the landslide susceptibility maps produced from this study could therefore assist planners and engineers during development and land use planning

the application of gis based logistic regression for landslide susceptibility mapping in the kakuda yahiko mountains central japan as a first step forward in regional hazard management multivariate statistical analysis in the form of logistic regression was used to produce a landslide susceptibility map in the kakuda yahiko mountains of central japan there are different methods to prepare landslide susceptibility maps the use of logistic regression in this study stemmed not only from the fact that this approach relaxes the strict assumptions required by other multivariate statistical methods but also to demonstrate that it can be combined with bivariate statistical analyses bsa to simplify the interpretation of the model obtained at the end in susceptibility mapping the use of logistic regression is to find the best fitting function to describe the relationship between the presence or absence of landslides dependent variable and a set of independent parameters such as slope angle and lithology here an inventory map of 87 landslides was used to produce a dependent variable which takes a value of 0 for the absence and 1 for the presence of slope failures lithology bed rock slope relationship lineaments slope gradient aspect elevation and road network were taken as independent parameters the effect of each parameter on landslide occurrence was assessed from the corresponding coefficient that appears in the logistic regression function the interpretations of the coefficients showed that road network plays a major role in determining landslide occurrence and distribution among the geomorphological parameters aspect and slope gradient have a more significant contribution than elevation although field observations showed that the latter is a good estimator of the approximate location of slope cuts using a predicted map of probability the study area was classified into five categories of landslide susceptibility extremely low very low low medium and high the medium and high susceptibility zones make up 8 87 of the total study area and involve mid altitude slopes in the eastern part of kakuda mountain and the central and southern parts of yahiko mountain

a data based landslide susceptibility map of africa abstract our understanding of the spatial patterns of landslides in africa is limited with available landslide studies typically focusing on only one or a few study areas moreover africa is clearly underrepresented in terms of available landslide inventories this study aims to produce a first continent wide landslide susceptibility map for africa calibrated with a well distributed landslide dataset we reviewed the literature on landslides in africa and compiled all available landslide inventories ca 10 800 landslides supplemented by additional landslide mapping using google earth imagery in underrepresented regions ca 7250 landslides this resulted in a dataset of approximately 18 050 landslides various environmental variables were investigated for their significance in explaining the observed spatial patterns of landslides to account for potential mapping biases in the dataset we used monte carlo simulations that selected different subsets of mapped landslides to test the significance of the considered environmental variables based on these analyses we constructed two landslide susceptibility maps for africa one for all landslide types and one excluding the known rockfalls in both maps topography is by far the most significant variable we evaluated the performance of the fitted multiple logistic regression models using independent subsets of landslides selected from the total dataset overall both maps perform very well in predicting intra continental patterns of landslides in africa and explain about 80 of the observed variance in landslide occurrence to further test the robustness and sensitivity to mapping biases we also modelled landslide susceptibility while excluding regions with arid climates as landslides in these environments are expected to be better preserved over time and therefore likely relatively overrepresented despite this potential bias the effect on the landslide susceptibility model is limited based on the constructed database and our analyses we further discuss potential research gaps for landslide prediction in africa and at continental scales for example analysis of the african countries mean landslide susceptibility shows a lack of landslide research in various countries prone to landsliding e g guinea gabon lesotho madagascar apart from the intrinsic value of this landslide susceptibility map as a natural hazard risk management tool the map and compiled database are highly promising for other applications for example we explored the potential significance of landslides as a geomorphic process by confronting our landslide susceptibility map with an available database of measured catchment sediment yield for 500 rivers in africa overall a significant positive but relatively weak relation between landslide susceptibility and sediment yield is observed

comparison of satellite and air photo based landslide susceptibility maps landslide susceptibility maps can be prepared in a variety of ways many geoscientists favour the use of an overlay model approach in which several map layers are combined by some arithmetic rules to determine the potential for sliding in an area or region the resulting susceptibility maps although based on a subjective weighting of relevant factors can often be of high accuracy and utility in order to obtain the relevant input data for this type of analysis remotely sensed data are often used to date susceptibility mapping just as the mapping of historic and individual landslides has tended to require higher resolution imagery this has somewhat limited the application of landslide susceptibility mapping while high resolution air photo or satellite imagery is superior to lower resolution imagery for the purpose of mapping of historic and individual landslides such higher levels of resolution may not be required for the development of landslide susceptibility maps in order to determine if medium resolution satellite imagery such as spot or aster could provide the needed data for landslide susceptibility mapping a comparison was undertaken of landslide susceptibility model output resulting from the use of stereo napp aerial photography versus the use of data obtained from stereo spot imagery the test area selected for this study consisted of two watersheds pena canyon and big rock canyon situated west of santa monica california usa along the pacific coast highway both watersheds have a long and well documented history of landslide activity and sufficient geologic variability and complexity to provide a good test site the specific overlay model used in this evaluation required input data consistent with the needs of many other models of this type the model output derived from the two different data sources and presented here in the form of susceptibility maps were virtually identical statistical and difference analysis confirmed that both methods of obtaining input data provide similar results and successfully identified landslide prone areas these results suggest that satellite imagery in this instance spot images could potentially be used in lieu of conventional air photos to evaluate landslide susceptibility in many situations especially in the case of remote locations and or developing countries this capability should result in substantial savings in terms of time financial resources and overall viability

assessment of landslide susceptibility on the natural terrain of lantau island hong kong steep terrain and the high frequency of tropical rainstorms make landslide occurrence on natural terrain a common phenomenon in hong kong for example more than 800 slope failures were triggered by a rainstorm in november 1993 on lantau island hong kong maps of recent landslides interpreted from aerial photographs in combination with a geographical information system were used to evaluate the frequency and distribution of landslides with particular reference to such physical parameters as lithology slope gradient slope aspect elevation vegetation cover and proximity to drainage line all of which are considered to be influential in the occurrence of landslides a stepwise logistic regression model was obtained between landslide susceptibility and the above mentioned physical parameters the study area has been classified into five classes of relative landslide susceptibility namely very low low moderate high and very high based on this methodology

landslide susceptibility assessment what are the effects of mapping unit and mapping method landslide susceptibility assessment forms the basis of any hazard mapping which is one of the essential parts of quantitative risk mapping for the same study area different susceptibility maps can be achieved depending on the type of susceptibility mapping methods mapping unit and scale although there are various methods of obtaining susceptibility maps the efficiency and performance of each method should be evaluated in this study the effect of mapping unit and susceptibility mapping method on landslide susceptibility assessment is investigated when analyzing the effect of susceptibility mapping method logistic regression lr which is widely used in landslide susceptibility mapping and spatial regression sr which have not been used for landslide susceptibility mapping are selected the susceptibility maps with logistic and spatial regression models are obtained using two different mapping units namely slope unit based and grid based mapping units the procedure for investigation of effect of mapping unit on different susceptibility mapping methods is applied to kumluca watershed in bartin province of western black sea region turkey 18 factor maps are prepared for landslide susceptibility assessment in the study region geographic information systems and remote sensing techniques are used to create the landslide factor maps to obtain susceptibility maps and to compare the results the relative operating characteristics roc curve is used to compare the predictive abilities of each model and mapping unit and also the accuracy is evaluated depending on the observations made during field surveys by analyzing the area under the roc curve for grid based and slope unit based mapping units it can be concluded that sr model provide better predictive performance 0 774 in grids and 0 898 in slope units as compared to the lr model 0 744 in grids and 0 820 in slope units this result is also supported by the accuracy analysis for both mapping units the sr model provides more accurate result 0 55 for grids and 0 57 for slope units than the lr model 0 50 for grids and 0 48 for slopes the main reason for this better performance is that the spatial correlations between the mapping units are incorporated into the model in sr while this fact is not considered in lr model

landslide susceptibility assessment using logistic regression and its comparison with a rock mass classification system along a road section in the northern himalayas india landslide studies are commonly guided by ground knowledge and field measurements of rock strength and slope failure criteria with increasing sophistication of gis based statistical methods however landslide susceptibility studies benefit from the integration of data collected from various sources and methods at different scales this study presents a logistic regression method for landslide susceptibility mapping and verifies the result by comparing it with the geotechnical based slope stability probability classification sspc methodology the study was carried out in a landslide prone national highway road section in the northern himalayas india logistic regression model performance was assessed by the receiver operator characteristics roc curve showing an area under the curve equal to 0 83 field validation of the sspc results showed a correspondence of 72 between the high and very high susceptibility classes with present landslide occurrences a spatial comparison of the two susceptibility maps revealed the significance of the geotechnical based sspc method as 90 of the area classified as high and very high susceptible zones by the logistic regression method corresponds to the high and very high class in the sspc method on the other hand only 34 of the area classified as high and very high by the sspc method falls in the high and very high classes of the logistic regression method the underestimation by the logistic regression method can be attributed to the generalisation made by the statistical methods so that a number of slopes existing in critical equilibrium condition might not be classified as high or very high susceptible zones

a spatiotemporal probabilistic modelling of storm induced shallow landsliding using aerial photographs and logistic regression landslides constitute one of the major natural hazards that could cause significant losses of life and property mapping or delineating areas prone to landsliding is therefore essential for land use activities and management decision making in hilly or mountainous regions a landslide hazard map can be constructed by a qualitative combination of maps of site conditions including geology topography and geomorphology by statistical methods through correlating landslide occurrence with geologic and geomorphic factors or by using safety factors from stability analysis a landslide hazard map should provide information on both the spatial and temporal probabilities of landsliding in a certain area however most previous studies have focused on susceptibility mapping rather than on hazard mapping in a spatiotemporal context this study aims at developing a predictive model based on both quasi static and dynamic variables to determine the probability of landsliding in terms of space and time the study area selected is about 13 km 2 in north lantau hong kong the source areas of the landslides caused by the rainstorms of 18 july 1992 and 4 5 november 1993 were interpreted from multi temporal aerial photographs landslide data lithology digital elevation model data land cover and rainfall data were digitized into a geographic information system database a logistic regression model was developed using lithology slope gradient slope aspect elevation slope shape land cover and rolling 24 it rainfall as independent variables since the dependent variable could be expressed in a dichotomous way this model achieved an overall accuracy of 87 2 with 89 5 of landslide grid cells correctly classified and found to be performing satisfactorily the model was then applied to rainfalls of a variety of periods of return to predict the probability of landsliding on natural slopes in space and time it is observed that the modelling techniques described here are useful for predicting the spatiotemporal probability of landsliding and can be used by land use planners to develop effective management strategies copyright 0 2003 john wiley sons ltd

prediction of landslide susceptibility using rare events logistic regression a case study in the flemish ardennes belgium abstract in this article a statistical multivariate method i e rare events logistic regression is evaluated for the creation of a landslide susceptibility map in a 200 km2 study area of the flemish ardennes belgium the methodology is based on the hypothesis that future landslides will have the same causal factors as the landslides initiated in the past the information on the past landslides comes from a landslide inventory map obtained by detailed field surveys and by the analysis of lidar light detection and ranging derived hillshade maps information on the causal factors e g slope gradient aspect lithology and soil drainage was extracted from digital elevation models derived from lidar and from topographical lithological and soil maps in landslide affected areas however we did not use the present day hillslope gradient in order to reflect the hillslope condition prior to landsliding the pre landslide hillslope was reconstructed and its gradient was used in the analysis because of their limited spatial occurrence the landslides in the study area can be regarded as rare events rare events logistic regression differs from ordinary logistic regression because it takes into account the low proportion of 1s landslides to 0s no landslides in the study area by incorporating three correction measures the endogenous stratified sampling of the dataset the prior correction of the intercept and the correction of the probabilities to include the estimation uncertainty for the study area significant model results were obtained with pre landslide hillslope gradient and three different clayey lithologies being important predictor variables receiver operating characteristic roc curves and the kappa index were used to validate the model both show a good agreement between the observed and predicted values of the validation dataset based on a qualified judgement the created landslide susceptibility map was classified into four classes i e very high high moderate and low susceptibility if interpreted correctly this classified susceptibility map is an important tool for the delineation of zones where prevention measures are needed and human interference should be limited in order to avoid property damage due to landslides

comparison of landslide susceptibility based on a decision tree model and actual landslide occurrence the akaishi mountains japan abstract this paper proposes a statistical decision tree model to analyze landslide susceptibility in a wide area of the akaishi mountains japan the objectives of this study were to validate the decision tree model by comparing landslide susceptibility and actual landslide occurrence and to reveal the relationships among landslide occurrence topography and geology landslide susceptibility was examined through ensemble learning with a decision tree decision trees are advantageous in that estimation processes and order of important explanatory variables are explicitly represented by the tree structures topographic characteristics elevation slope angle profile curvature plan curvature and dissection and undissection height and geological data were used as the explanatory variables these topographic characteristics were calculated from digital elevation models dems the objective variables were landslide occurrence and reactivation data between 1992 and 2002 that were depicted by satellite image analysis landslide susceptibility was validated by comparing actual data on landslides that occurred and reactivated after the model was constructed between 2002 and 2004 this study revealed that from 2002 to 2004 landslides tended to occur and reactivate in catchments with high landslide susceptibility the landslide susceptibility map thus depicts the actual landslide occurrence and reactivation in the akaishi mountains this result indicates that the decision tree model has appropriate accuracy for estimating the probabilities of future landslides the tree structure indicates that landslides occurred and reactivated frequently in the catchments that had an average slope angle exceeding ca 29 and a mode of slope angle exceeding 33 which agree well with previous studies a decision tree also quantitatively expresses important explanatory variables at the higher order of the tree structure

modeling landslide susceptibility in data scarce environments using optimized data mining and statistical methods abstract this study evaluated the generalizability of five models to select a suitable approach for landslide susceptibility modeling in data scarce environments in total 418 landslide inventories and 18 landslide conditioning factors were analyzed multicollinearity and factor optimization were investigated before data modeling and two experiments were then conducted in each experiment five susceptibility maps were produced based on support vector machine svm random forest rf weight of evidence woe ridge regression rid r and robust regression rr models the highest accuracy auc 0 85 was achieved with the svm model when either the full or limited landslide inventories were used furthermore the rf and woe models were severely affected when less landslide samples were used for training the other models were affected slightly when the training samples were limited

landslide susceptibility mapping using geological data a dem from aster images and an artificial neural network ann an efficient and accurate method of generating landslide susceptibility maps is very important to mitigate the loss of properties and lives caused by this type of geological hazard this study focuses on the development of an accurate and efficient method of data integration processing and generation of a landslide susceptibility map using an ann and data from aster images the method contains two major phases the first phase is the data integration and analysis and the second is the artificial neural network training and mapping the data integration and analysis phase involve gis based statistical analysis relating landslide occurrence to geological and dem digital elevation model derived geomorphological parameters the parameters include slope aspect elevation geology density of geological boundaries and distance to the boundaries this phase determines the geological and geomorphological factors that are significantly correlated with landslide occurrence the second phase further relates the landslide susceptibility index to the important geological and geomorphological parameters identified in the first phase through ann training the trained ann is then used to generate a landslide susceptibility map landslide data from the 2004 niigata earthquake and a dem derived from aster images were used the area provided enough landslide data to check the efficiency and accuracy of the developed method based on the initial results of the experiment the developed method is more than 90 accurate in determining the probability of landslide occurrence in a particular area

landslide databases for climate change detection and attribution abstract a systematic inventory of landslide events over regional spatial scales and through time is required for investigating changes in landslide frequency along side changes in landslide triggers this paper describes the methods used to compile a european wide landslide inventory and some of the methodological and practical obstacles that inhibit better use and development of such inventories we argue that these methods can be used more widely to provide a comprehensive picture of landslide populations and to further enrich our understanding of the impact of climate change and other drivers on landslide frequency and magnitude

drill bit displacement source model source performance and drilling parameters the emission properties of a drill bit source and the signature of the drill bit seismograms depend on the dynamic action of the drill bit which in turn is a function of the geological conditions rock properties and drilling parameters in fact drilling is a variable dynamic process in which the vibrations produced by the drill bit are transmitted into the drillstring and formation with a partition of energy determined by the impedances at the bit in this analysis we study drill bit performance and calculate the forces produced by an ideal drill bit to determine the variations in the signal signature and ultimately the conditions of source repeatability as a function of average drilling parameters and signal frequency the model includes near field effects and assumes the drill bit acts as a displacement source producing axial bit forces with relative bit formation displacement and vertical penetration in the formation the analysis shows that the expected bit signature which is equivalent to the ground force in vibroseis depends on average tooth impact area percussion frequency rate of penetration formation strength bit wear and downhole pressure in particular the results show that larger amplitudes of the axial forces are expected at a lower rate of penetration higher formation strength and lower formation pressure

frequency and spatial distribution of landslides in a mountainous drainage basin western foothills taiwan maps from 1904 and 1915 and air photographs from 1963 1980 1985 1993 and 1996 provide a record of landslide incidence in a 92 1 km2 drainage basin a headwater tributary of the cho shui river in taiwan interpretation of landslide patterns from the early maps indicate that in four sub basins 36 km2 structural geological factors control chronic landsliding regularly reactivated by intense rains within these four sub basins all later air photographs reveal a continuing high incidence of landslides with landslide densities of 3 11 ha km2 air photographs taken in 1963 following extensive logging in 1985 following highway construction and in 1996 following the very large typhoon herb event demonstrate the short term effects of disturbance in these structurally weak sub basins air photographs from 1980 and 1993 demonstrate recovery of the land surface from logging and highway construction impacts respectively for the adjacent sub basins 56 km2 two modes of response to perturbations were identified six sub basins 48 km2 showed direct response to logging road construction and typhoon herb and five sub basins 8 km2 were more buffered and showed some lagged responses even this last category of sub basins is more active than the average for taiwan where the mean landslide density is 0 84 ha km2 it is proposed that for the 92 1 km2 hoshe basin the formative event sensu brunsden z geomorphol suppl 79 1990 1 is one that produces approximately 200 ha of landslides a value that has been equaled or exceeded in each of the periods of study 1963 1980 1980 1985 1985 1993 and 1993 1996 logging activity major road construction and extreme typhoon and earthquake events produce short term acceleration of landslide incidence in principle recovery rates of the land from pulsed perturbations of about 20 years for logging activity and about 8 years for major road construction may also be suggested

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

anthropogenically accelerated mass movement kulu valley himachal pradesh india abstract a devastating landslide occurred on 12 september 1995 near luggar bhatti kulu himachal pradesh and killed 65 people an estimated 0 96 106 m3 of unconsolidated mass slid sse down the terminal part of a thick alluvial fan of quaternary age on the left bank of the beas river about 0 03 106 m3 of dislodged material formed a 15 m high and 150 m long hump at the bottom of the failed slope a shallow sag pond developed in the rear the slide occurred after heavy rains on 3 6 september in the region when the beas rose to a bankfull position factors involved in this toppling cum debris slide include steep slope continuous seepage with high pore water pressure in unconsolidated material a road cut obliterating the foot of the fan slope and impinging by the beas river during the flood a survey in the area showed that a variety of mass movement processes were triggered by the heavy rains in september the most predominant being a series of slope failures on the outside of meander loops and bank erosion caused by turbulence of the overflowing beas river extensive damage was sustained by national highway 21 nh 21 a bridge ramp near bhuntar a suspension bridge at kulu and two other bridges upstream most damage occurred in the manali area where massive buildings were washed away by the flash flood this paper examines the factors and processes responsible for triggering widespread mass movement and related damages in the kulu valley whereas some smaller events occurred in the early and middle part of this century the recurrence and intensity of mass movements are recent phenomena attributed mainly to escalating socio economic development growth of tourism and population pressure some long term policy is suggested for mitigation of landslides and other denudational processes in relation to impelling human factors

different landslide sampling strategies in a grid based bi variate statistical susceptibility model abstract this study had three aims the first was to assess the performance of the weights of evidence wofe landslide susceptibility model in areas that are very different in terms of size geoenvironmental settings and landslide types the second was to test the appropriate strategies to sample the mapped landslide polygon the final aim was to evaluate the performance of the method to changes in the landslide sample size used to train the model the method was applied to two areas the fella river basin eastern italian alps containing debris flows and buzau county romanian carpathians with shallow landslides the three landslide sampling strategies used were 1 the landslide scarp centroid 2 points populating the scarp on a 50 m grid and 3 the entire scarp polygon the highest success rates were obtained when sampling shallow landslides as 50 m grid points and debris flow scarps as polygons prediction rates were highest when using the entire scarp polygon method for both landslide types the sample size test using the landslide centroids showed that a sample of 104 debris flow scarps was sufficient to predict the remaining 941 debris flows in the fella river basin while 161 shallow landslides was the minimum required number to predict the remaining 1451 scarps in buzau county below these landslide sample thresholds model performance was too low however using more landslides than the threshold produced a plateau effect with little to no increase in the model performance rates

spatio temporal patterns of historical shallow landslides in a volcanic area mt aso japan abstract the evaluation of spatially and temporally distributed records of translational shallow landslides in heterogeneous watersheds provides insights needed to understand disastrous processes recurrent slope instability events occurred between 1953 and 1998 in two watersheds of mt aso western japan this paper investigates 1 the spatio temporal characteristics of translational shallow landslides dimensions numbers densities and area subjected to failure observed at a particular location 2 dem based landform characteristics elevation slope angles curvatures and their control on landslide distribution and 3 rainfall characteristics the evaluation of the landslide history consequences and characteristics of spatially and temporally distributed landslides are based on the series of inventory maps for years 1954 1977 1990 and 1998 geologically the watersheds consist of pyroxene olivine andesite basalt lava pyroclastics deposits gravel sand and clay deposits originated from takadake nekodake and washigamine volcanoes during 45 years 1953 1998 a total of 619 and 976 numbers of shallow landslides have been recognized in the sakurakigawa and furuegawa watersheds respectively repeated sliding denuded a total surface area of 0 372 km 2 in the sakurakigawa watershed representing 35 of the watershed area similarly slides denuded a total of 0 534 km 2 in the furuegawa watershed representing 12 of the watershed area for example storm events of june 1953 and july 1990 with rainfall intensities of 49 and 61 mm h 1 respectively triggered numerous landslides about 25 and 47 of sakurakigawa and furuegawa watersheds respectively still bears the potential to produce landslides landslides were commonly observed where thick unconsolidated tephra layers and pyroclastics rocks overlain by thin tephra bed existed and for a slope inclination range of 30 35

selecting and weighting spatial predictors for empirical modeling of landslide susceptibility in the darjeeling himalayas india in this paper we created predictive models for assessing the susceptibility to shallow translational rocksliding and debris sliding in the darjeeling himalayas india by empirically selecting and weighting spatial predictors of landslides we demonstrate a two stage methodology 1 quantifying associations of individual spatial factors with landslides of different types using bivariate analysis to select predictors and 2 pairwise comparisons of the quantified associations using an analytical hierarchy process to assign predictor weights we integrate the weighted spatial predictors through multi class index overlay to derive predictive models of landslide susceptibility the resultant model for shallow translational landsliding based on selected and weighted predictors outperforms those based on all weighted predictors or selected and unweighted predictors therefore spatial factors with negative associations with landslides and unweighted predictors are ineffective in predictive modeling of landslide susceptibility we also applied logistic regression to model landslide susceptibility but some of the selected predictors are less realistic than those from our methodology and our methodology gives better prediction rates although previous predictive models of landslide susceptibility indicate that multivariate analyses are superior to bivariate analyses we demonstrate the benefit of the proposed methodology including bivariate analyses

multidisciplinary investigations in evaluating landslide susceptibility an example in the serchio river valley italy abstract the proposed experimental study is aimed at contributing to the landslide susceptibility evaluation using a multidisciplinary approach geological geomorphological and geo engineering survey together with multivariate statistical analysis and gis technique it is included in a wider research project aimed at defining the landslide hazard in the area of the map no 250 castelnuovo di garfagnana 1 50 000 scale this study is based on the realization of a landslides inventory map and statistical data analysis using probabilistic methods the methodology applied in ranking slope instability proceeded step by step at first geomorphologic investigation was performed in order to realize a landslide inventory map a gis database was created to collect the characteristics related to landslides geometry type of movement and state of activity geo engineering survey and characterization with in situ and laboratory tests allowed assessing rock mass classification and geotechnical properties of soils texture and consistency the statistical approach for evaluating the landslide susceptibility is based on the assumption that the landslide probability for the currently landslides free areas could be evaluated studying the conditions which led to past and present instability a set of environmental factors thought to be related to landslides were analysed and their spatial distribution organized in different layers then gis supported spatial analysis conditional and multivariate analysis allowed to calculate the connections between instability factors and landslide distribution this step evolved towards two distinct statistical methods both indirect and quantitative leading to a classification of the land surface in some different susceptibility domains conditional analysis was applied to a particular type of terrain unit named unique condition unit ucu that is a unique combination of the instability factors the computer aided evaluation of the landslide index within each ucu represents the probability of landslide occurrence according to bayes statistical concept multivariate analysis was applied to the same set of instability factors but to a different type of terrain unit the grid cell the results showed a quantitative response more reliable about the effectiveness of each instability factors with the possibility of verifying their statistical significance

improving landslide susceptibility mapping using morphometric features in the mawat area kurdistan region ne iraq comparison of different statistical models abstract susceptibility mapping provides information about vulnerable locations and thus helps to potentially decrease infrastructure damage due to mass wasting during the past decades expansion of settlements into areas prone to landslides in iraq has highlighted the importance of accurate landslide susceptibility studies the main goal of this research is to implement selected morphometric parameters to improve prediction of landslide susceptibility in the zagros mountain region we used the mawat area in the kurdistan region ne iraq to test the added value of morphometric indicators sixteen morphometric factors mainly derived from a digital elevation model dem extracted using the stereo ability of the advanced spaceborne thermal emission and reflection radiometer aster satellite as well as geological and environmental predictive factors were appraised we evaluated and compared frequency ratio fr weight of evidence woe logistic regression lr and probit regression pr approaches in combination with morphometric indices to determine the landslide susceptibility ls the areas under the curve auc of the prediction rate curve prc relative landslide density index r index and true positive percentage tpp for the four models show that all models perform similarly and the focus should be on careful selection of the predictive factors which is far more important than the methods used results indicate that lithology and slope aspects are the more dominant factors that lead to detect possible occurrence of landslides furthermore this work demonstrates that the hypsometric integral performs better than the commonly used slope curvature as a predictor and thus increases the prediction accuracy of the susceptibility map we argue that the use of adequate morphometric parameters can increase the efficiency of the ls mapping in other regions of the world