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

mapping the suitability for ice core drilling of glaciers in the european alps and the asian high mountains ice cores from mid latitude mountain glaciers provide detailed information on past climate conditions and regional environmental changes which is essential for placing current climate change into a longer term perspective in this context it is important to define guidelines and create dedicated maps to identify suitable areas for future ice core drillings in this study the suitability for ice core drilling sicd of a mountain glacier is defined as the possibility of extracting an ice core with preserved stratigraphy suitable for reconstructing past climate morphometric and climatic variables related to sicd are selected through literature review and characterization of previously drilled sites a quantitative weight of evidence method is proposed to combine selected variables i e slope local relief temperature and direct solar radiation to map the potential drilling sites in mid latitude mountain glaciers the method was first developed in the european alps and then applied to the asian high mountains model performances and limitations are discussed and first indications of new potential drilling sites in the asian high mountains are provided results presented here can facilitate the selection of future drilling sites especially on unexplored asian mountain glaciers towards the understanding of climate and environmental changes

predicting gully occurrence at watershed scale comparing topographic indices and multivariate statistical models abstract in this study the ability of five topographic indices to predict the gully trajectories observed in two adjacent watersheds located in sicily italy was evaluated two of these indices named mspi and mtwi as far as we know have never been employed to this aim they were obtained by multiplying the stream power index spi and the topographic wetness index twi respectively by the convergence index ci the predictive ability of the topographic indices was measured by using both cut off independent auc area under the receiver operating characteristic curve and dependent statistics cohen s kappa index sensitivity specificity these statistics were calculated also for 100 mars multivariate adaptive regression splines and 100 lr logistic regression model runs which used as predictors the topographic variables i e contributing area slope steepness plan curvature and convergence index combined into the five indices performance statistics of both topographic indices and statistical models were calculated using 100 random samples of 2 m grid cells which were extracted only from flow concentration lines this was done in order to focus the validation process on where gully erosion is more likely to occur mspi achieved the best predictive skill auc 0 93 0 71 among the topographic indices and exhibited similar and better accuracy than local i e trained and validated in the same watershed and transferred i e trained in one watershed and tested in the other one lr models respectively on the other hand mspi performed similarly to transferred mars runs auc 0 92 0 71 but slightly worse than local mars runs auc 0 95 0 77 based on the results of this experiment it can be inferred that i including ci helps in detecting hollow areas where gullies are more likely to occur and ii mpsi can be a valid alternative to a data driven approach for mapping gully erosion susceptibility in areas where a gully inventory is not available which is necessary to calibrate statistical models

analysis of landslide inventories for accurate prediction of debris flow source areas abstract for the generation of susceptibility maps on medium scales 1 25 000 to 1 50 000 using statistical techniques a reliable landslide inventory is needed together with factor maps used as inputs this paper compares landslide susceptibility maps obtained with the same methodology but using different landslide inventories the official italian landslide inventory geoiffi for the lombardy region and a recently mapped inventory df2001 the analysis included four main steps i preparation of debris flow inventories using both random and spatial partitions and factor maps as explanatory variables ii calculation of accountability and reliability indices for a preliminary susceptibility analysis and selection of an appropriate combination of the factor maps for detailed analysis iii evaluation and validation of the obtained susceptibility maps and iv comparison of the results and selection of the final map the study area is located in the valtellina valley in the central italian alps the analysis identified highly susceptible areas of shallow landslides that may generate debris flows it was demonstrated that more precisely delimited source areas for landslide induced debris flows produce better susceptibility maps however the improvement of these maps was relatively limited when the inventories were randomly subdivided higher improvements were observed after the subdivision of the inventories into three geographical parts with different geomorphological characteristics although the modelling showed very similar results if evaluation is made using standard techniques the spatial pattern of the susceptibility maps was highly variable and dependent on the combination of the factor maps used

assessing ocean alkalinity for carbon sequestration over the coming century humanity may need to find reservoirs to store several trillions of tons of carbon dioxide co2 emitted from fossil fuel combustion which would otherwise cause dangerous climate change if it were left in the atmosphere carbon storage in the ocean as bicarbonate ions by increasing ocean alkalinity has received very little attention yet recent work suggests sufficient capacity to sequester copious quantities of co2 it may be possible to sequester hundreds of billions to trillions of tonnes of c without surpassing post industrial average carbonate saturation states in the surface ocean when globally distributed the impact of elevated alkalinity is potentially small and may help ameliorate the effects of ocean acidification however the local impact around addition sites may be more acute but is specific to the mineral and technology the alkalinity of the ocean increases naturally because of rock weathering in which 1 5 moles of carbon are removed from the atmosphere for every mole of magnesium or calcium dissolved from silicate minerals e g wollastonite olivine anorthite and 0 5 moles for carbonate minerals e g calcite dolomite these processes are responsible for naturally sequestering 0 5 billion of co2 tons per year alkalinity is reduced in the ocean through carbonate mineral precipitation which is almost exclusively formed from biological activity most of the previous work on the biological response to changes in carbonate chemistry have focused on acidifying conditions more research is required to understand carbonate precipitation at elevated alkalinity to constrain the longevity of carbon storage a range of technologies have been proposed to increase ocean alkalinity accelerated weathering of limestone enhanced weathering electrochemical promoted weathering ocean liming the cost of which may be comparable to alternative carbon sequestration proposals e g 20 100 tco2 1 there are still many unanswered technical environmental social and ethical questions but the scale of the carbon sequestration challenge warrants research to address these

spatial agreement of predicted patterns in landslide susceptibility maps abstract the aim of the study is to assess the degree of spatial agreement among different patterns of landslide susceptibility maps with almost similar success and prediction rate curves obtained using different combinations of predictive factors our approach was tested in an alpine environment italian alps where debris flows represent one of the most frequent dangerous processes a data driven bayesian method the weights of evidence modelling technique was successfully applied and success and prediction rate curves were computed for supporting the modelling results and assessing the robustness of the models the values of the area under curves were very similar for different models ranging from 84 36 to 86 49 for the success rate curves and from 82 46 to 85 66 for the prediction rate curves then the post probability output maps were classified into rank based maps by using an equal area criterion to compare the predicted results afterwards appropriate statistical techniques kappa statistic principal component analysis and distance weighted entropy were applied kappa statistic and principal component analysis outcomes called for significant differences within the output spatial patterns of the predicted maps as well as within the highest susceptibility classes moreover the estimated distance weighted entropy values showed a very low overall entropy at the valley bottom as all models predicted this area equally as low susceptible in contrast areas characterised by the highest values of entropy were more concentrated in the northern and southern slopes of the study site lying in zones where landslide density was higher consequently susceptibility maps with similar predictive power may not have the same meaning in terms of spatial pattern of predicted results it is for this reason that landslide susceptibility maps should be distributed together with map documents aimed at defining the level of accuracy of the predicted results to provide the end users with informative selection criteria

landslide detection and susceptibility mapping in the sagimakri area korea using kompsat 1 and weight of evidence technique the purpose of this study is to detect landslide locations from satellite images and use them for landslide susceptibility mapping in the sagimakri area korea using a geographic information system and a data driven weight of evidence model the landslide location areas were identified from korea multipurpose satellite images by means of change detection technique and further verified by extensive field survey subsequently landslide locations were randomly selected in a 70 30 ratio for training and validation of the model respectively a spatial database was constructed which is composed of topography forest soil and land cover and 14 landslide related factors were extracted from the database the relationships between the detected landslide locations and the factors were identified and quantified by weights of evidence model tests of conditional independence were performed for the selection of factors allowing five different combinations of factors to be analyzed the relationships were used as the contrast values w and w of factor ratings in the overlay analysis to create landslide susceptibility indexes and maps the results of the analysis were validated by comparison with known landslide locations that were not used directly in the analysis

optimal landslide susceptibility zonation based on multiple forecasts abstract environmental and multi temporal landslide information for an area in umbria italy was exploited to produce four single and two combined landslide susceptibility zonations the 78 9 km2 study area was partitioned in 894 slope units and the single susceptibility zonations were obtained through linear discriminant analysis lda quadratic discriminant analysis qda logistic regression lr and by training a neural network nn the presence or absence of landslides in the slope units in the period from pre 1941 to 1996 training set was used as the dependent variable for the terrain classification next adopting a regression approach two optimal combinations of the four single zonations were prepared the single and the combined zonations were tested against landslides in the 9 year period from 1997 to 2005 validation set different metrics were used to evaluate the quality of the susceptibility zonations including degree of model fit uncertainty in the probability estimates and model prediction skills these metrics showed that the degree of model fit was not a good indicator of the model forecasting skills zonations obtained through classical multivariate classification techniques lda qda and lr produced superior predictions when compared to the nn model that over fitted the landslide information in the training set lda and lr produced less uncertain zonations than qda and nn the combined models resulted in a reduced number of errors and in less uncertain predictions an important result that suggests that the combination of landslide susceptibility zonations can provide optimal susceptibility assessments

quantitative assessment of landslide susceptibility along the xianshuihe fault zone tibetan plateau china the xianshuihe fault xsf zone is a sinistral slip fault system on the eastern margin of the tibetan plateau with high quaternary activity and frequent historic earthquakes large landslides along the fault zone have caused substantial damage and are the second most important regional hazard after earthquakes a landslide inventory in a 7339 km2 area along the xsf zone documented 415 landslides and evaluated landslide distribution characteristics using frequency ratio fr and weight of evidence woe models to map landslide susceptibility a total of 11 variables were analyzed as input variables slope angle slope aspect altitude planform curvature topographic wetness index distance from active faults lithology annual rainfall distance from rivers distance from roads and the ndvi of the study area among these factors the distance from active faults altitude slope angle aspect lithology and rainfall were the dominant influencing factors assessment of six susceptibility mapping schemes with fr and woe models using the roc method showed that while all six of the model schemes produced good results on the whole the fr model performed better than the woe model the landslide susceptibility map of the fr model with six variables performed as well as the woe model with the full 11 variables inclusion of more variables did not necessarily translate into a better predictive capability several factors typically associated with susceptibility to rainfall triggered landslides topographic convergence rainfall and topographic wetness index either did not follow expected patterns rainfall or were not good general predictors of landslide locations topographic convergence and wetness index in contrast distance to active faults slope aspect and topographic divergence were the best predictors as measured by the fr method this combination points to earthquakes rather than rainfall as the dominant landslide triggering mechanism in the study area

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

landslide temporal analysis and susceptibility assessment as bases for landslide mitigation machu picchu peru multi temporal landslide occurrence information acquired through aerial photo interpretation and field mapping was used to assess occurrence frequencies on the slopes around the unesco cultural world heritage site of machu picchu peru this showed that the coarse time resolution of the historical landslide information may lead to inaccurate interpretations regarding landslide occurrence frequencies in some parts of the study area in addition the assumption that the past landslide frequency can be used to describe the future landslide occurrence was not proved in the study area thereafter unique conditional analyses were undertaken to assess landslide susceptibility using a limited number of preparatory factor maps it showed that large majority of the inca city is located on least susceptible areas within the region the results of the susceptibility assessment combined with landslide occurrence frequencies may serve as a basis for the landslide hazard mitigation in the studied area for these purposes pixel based susceptibility maps were generalized into expert defined landslide management units these units provide site managers with easily understandable and applicable hence reliable information about future landslide occurrences an approach describing usage of the resulting susceptibility maps for onsite mitigation purposes was described with respect to the needs of machu picchu site managers

the influence of the inventory on the determination of the rainfall induced shallow landslides susceptibility using generalized additive models abstract data driven methodologies are widely used for the reconstruction of shallow landslide susceptibility maps the outputs of these models strictly depend on the type of landslide inventories used for the modelling thus this work performed a deep analysis of the role of different inventories on the definition of shallow landslide susceptibility of a particular area modeled through a data driven technique generalized additive model distinct shallow landslide inventories referred to the same rainfall event or to different rainfall events can produce different maps of susceptibility distribution for the same area despite a similar predictive capability the models built for the same area produced different susceptibility maps as estimated by low values of the cohen s kappa coefficient 0 13 0 46 if inventories obtained using different landslide detection methods are available the models of susceptibility will be affected by the position and shape of the phenomena that could be detected by each tool an inventory created integrating the visual interpretation of high resolution images with field surveys allows to obtain more accurate inventories to derive a better representation of the proneness of the territory towards shallow landsliding in the case of inventories related to the same rainfall event carried out with different criteria the susceptibility distribution is influenced by the choices adopted as regards in particular the type and the mapping criteria of phenomena included in the inventory for shallow landslide inventories triggered by different rainfall events in the same area the classification of the territory in terms of susceptibility is strictly connected to each specific rainfall event and reflects the relative shallow slope stability of a region only under similar rainfall conditions shallow landslide susceptibility obtained with a multi temporal inventory grouping landslides occurred in few years during more events provides a more accurate estimation of the predisposition to shallow landsliding in consequence of the typical rainfall triggering patterns of an area

detection and projection of carbonate dissolution in the water column and deep sea sediments due to ocean acidification 1 dissolution of fossil fuel co2 in seawater results in decreasing carbonate ion concentration and lowering of seawater ph with likely negative impacts for many marine organisms we project detectable changes in carbonate dissolution and evaluate their potential to mitigate atmospheric co2 and ocean acidification with a global biogeochemistry model hamocc forced by different co2 emission scenarios our results suggest that as the anthropogenic co2 signal penetrates into ocean interior the saturation state of carbonate minerals will drop drastically with undersaturation extending from the ocean floor up to 100 150 m depth in the next century this will induce massive dissolution of caco3 in the water column as well as the sediment increasing the total alkalinity ta by up to 180 mol kg 1 at the surface and in the ocean interior over the next 2500 years model results indicate an inhomogeneous response among different ocean basins atlantic carbonate chemistry responds faster and starts recovering two millennia after co2 emissions cease which is not the case in the pacific caco3rain stops in the pacific ocean around 2230 using an observation derived detection threshold for ta we project detectable dissolution driven changes only by the year 2070 in the surface ocean and after 2230 and 2500 in the deep atlantic and pacific respectively we show that different model assumptions regarding dissolution and calcification rates have little impact on future projections instead anthropogenic co2 emissions overwhelmingly control the degree of perturbation in ocean chemistry in conclusion ocean carbonate dissolution has insignificant potential in mitigating atmospheric co2 and ocean acidification in the next millennia

landslide susceptibility analysis and verification using the bayesian probability model the bayesian probability model using the weight of evidence method was applied to the task of evaluating landslide susceptibility using gis data the location chosen for the study was the janghung area in korea which suffered substantial landslide damage following heavy rain in 1998 using the location of the landslides as well as topographic factors such as soil forest and land use the weight of evidence method was used to calculate each factor s rating tests of conditional independence were performed for the selection of the factors allowing the large number of combinations of factors to be analyzed for each factor rating the contrast values w and w were overlaid for landslide susceptibility mapping the results of the analysis were verified using the observed landslide locations and among the combinations the slope aspect curvature soil material and wood types show the best results

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

future ocean acidification in the canada basin and surrounding arctic ocean from cmip5 earth system models 1 six earth system models that include an interactive carbon cycle and have contributed results to the 5th coupled model intercomparison project cmip5 are evaluated with respect to arctic ocean acidification projections under representative concentration pathways rcps 8 5 and 4 5 consistently show reductions in the bidecadal mean surface ph from about 8 1 in 1986 2005 to 7 7 7 9 by 2066 2085 in the canada basin closely linked to reductions in the calcium carbonate saturation state xa c from about 1 4 2 0 to 0 7 1 0 for aragonite calcite for rcp8 5 the large but opposite effects of dilution and biological drawdown of dic and dilution of alkalinity lead to a small seasonal amplitude change in x as well as intermodel differences in the timing and sign of the summer minimum the canada basin shows a characteristic layering in x affected by ice melt and inflowing pacific water shallow undersaturated layers form at the surface and subsurface creating a shallow saturation horizon which expands from the surface downward this is in addition to the globally observed deep saturation horizon which is continuously expanding upward with increasing co2 uptake the eurasian basin becomes undersaturated much later than the rest of the arctic these cmip5 model results strengthen earlier findings although large intermodel differences remain below 200 m xa varies by up to 1 0 in the canada basin and the deep saturation horizon varies from 2000 to 4000 m among the models differences of projected acidification changes are primarily related to sea ice retreat and responses of wind mixing and stratification

comparing models of debris flow susceptibility in the alpine environment abstract debris flows are widespread in val di fassa trento province eastern italian alps where they constitute one of the most dangerous gravity induced surface processes from a large set of environmental characteristics and a detailed inventory of debris flows we developed five models to predict location of debris flow source areas the models differ in approach statistical vs physically based and type of terrain unit of reference slope unit vs grid cell in the statistical models a mix of several environmental factors classified areas with different debris flow susceptibility however the factors that exert a strong discriminant power reduce to conditions of high slope gradient pasture or no vegetation cover availability of detrital material and active erosional processes since slope and land use are also used in the physically based approach all model results are largely controlled by the same leading variables overlaying susceptibility maps produced by the different methods statistical vs physically based for the same terrain unit of reference grid cell reveals a large difference nearly 25 spatial mismatch the spatial discrepancy exceeds 30 for susceptibility maps generated by the same method discriminant analysis but different terrain units slope unit vs grid cell the size of the terrain unit also led to different susceptibility maps almost 20 spatial mismatch maps based on different statistical tools discriminant analysis vs logistic regression differed least less than 10 hence method and terrain unit proved to be equally important in mapping susceptibility model performance was evaluated from the percentages of terrain units that each model correctly classifies the number of debris flow falling within the area classified as unstable by each model and through the metric of roc curves although all techniques implemented yielded results essentially comparable the discriminant model based on the partition of the study area into small slope units may constitute the most suitable approach to regional debris flow assessment in the alpine environment

impacts of artificial ocean alkalinization on the carbon cycle and climate in earth system simulations using the state of the art emissions driven max planck institute earth system model we explore the impacts of artificial ocean alkalinization aoa with a scenario based on the representative concentration pathway rcp framework addition of 114 pmol of alkalinity to the surface ocean stabilizes atmospheric co2 concentration to rcp4 5 levels under rcp8 5 emissions this scenario removes 940 gtc from the atmosphere and mitigates 1 5 k of global warming within this century the climate adjusts to the lower co2 concentration preventing the loss of sea ice and high sea level rise seawater ph and the carbonate saturation state rise substantially above levels of the current decade pronounced differences in regional sensitivities to aoa are projected with the arctic ocean and tropical oceans emerging as hot spots for biogeochemical changes induced by aoa thus the co2 mitigation potential of aoa comes at a price of an unprecedented ocean biogeochemistry perturbation with unknown ecological consequences

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 comparison of statistical and deterministic methods for shallow landslide susceptibility zoning in clayey soils abstract shallow landslides are widespread in different geological contexts and generally occur as multiple events over large areas when these phenomena involve fine grained soils they may cause serious consequences in terms of environmental and property damages and thus their spatial forecasting becomes a relevant issue for land use planning and design purposes the existing literature provides several methods for landslide susceptibility assessment categorized in qualitative and quantitative methods when dealing with analyses at large scale 1 5000 quantitative methods are generally preferred in this paper landslide susceptibility maps are produced for a study area prone to shallow landsliding located in catanzaro southern italy to this aim two quantitative methods are implemented the statistical information value method and the deterministic trigrs model the two approaches are compared by means of two indicators of the grade of correctness of the landslide susceptibility maps the area under curve of the roc curve auc and the overestimation index oi the results of the analyses in terms of auc values demonstrate the effectiveness and consistency of both methods in performing the susceptibility mapping of the study area when the oi values are considered the results provided by the deterministic model are slightly better than the ones resulting from the statistical analysis this does not come as a surprise for the case study at hand and it can be ascribed to the availability within the study area of a reliable database of soil properties and an in depth knowledge of the behaviour of the considered landslides

estimating the quality of landslide susceptibility models we present a landslide susceptibility model for the collazzone area central italy and we propose a framework for evaluating the model reliability and prediction skill the landslide susceptibility model was obtained through discriminant analysis of 46 thematic environmental variables and using the presence of shallow landslides obtained from a multi temporal inventory map as the dependent variable for statistical analysis by comparing the number of correctly and incorrectly classified mapping units it is established that the model classifies 77 0 of 894 mapping units correctly model fitting performance is investigated by comparing the proportion of the study area in each probability class with the corresponding proportion of landslide area we then prepare an ensemble of 350 landslide susceptibility models using the same landslide and thematic information but different numbers of mapping units this ensemble is exploited to investigate the model reliability including the role of the thematic variables used to construct the model and the model sensitivity to changes in the input data by studying the variation of the model s susceptibility estimate the error associated with the susceptibility assessment for each mapping unit is determined this result is shown on a map that complements the landslide susceptibility map prediction skill of the susceptibility model is then estimated by comparing the forecast with two recent event inventory maps the susceptibility model is found capable of predicting the newly triggered landslides a general framework for testing a susceptibility model is proposed including a scheme for ranking the quality of the susceptibility assessment

forecasting and validation of landslide susceptibility using an integration of frequency ratio and neuro fuzzy models a case study of seorak mountain area in korea landslides susceptibility maps were constructed in seorak mountain area korea using an integration of frequency ratio and adaptive neuro fuzzy inference system anfis in geographical information system gis environment landslide occurrence areas were detected in the study by interpreting aerial photographs and field survey data landslide locations were randomly selected in a 50 50 ratio for training and validation of the models respectively topography geology soil and forest databases were also constructed maps relevant to landslide occurrence were assembled in a spatial database using the constructed spatial database 17 landslide related factors were extracted the adaptive anfis model with different types of membership functions mfs was then applied for landslide susceptibility mapping in the study area two landslide susceptibility maps were prepared using the different mfs the frequency ratio model was also applied to the landslide susceptibility mapping for comparing with the probabilistic anfis model finally the resulting landslide susceptibility maps were validated using the landslide locations which were not used for training the anfis the validation results showed 75 57 accuracy using the generalized bell shaped mf model 74 94 accuracy using the sigmoidal 2 mf model and 73 07 accuracy using frequency ratio model these accuracy results show that an anfis can be an effective tool in landslide susceptibility mapping

estimating the topographic predictability of debris flows abstract the norwegian traffic network is impacted by about 2000 landslides avalanches and debris flows each year that incur high economic losses despite the urgent need to mitigate future losses efforts to locate potential debris flow source areas have been rare at the regional scale we tackle this research gap by exploring a minimal set of possible topographic predictors of debris flow initiation that we input to a weights of evidence wofe model for mapping the regional susceptibility to debris flows in western norway we use an inventory of 429 debris flows that were recorded between 1979 and 2008 and use the terrain variables of slope total curvature and contributing area flow accumulation to compute the posterior probabilities of local debris flow occurrence the novelty of our approach is that we quantify the uncertainties in the wofe approach arising from different predictor classification schemes and data input while estimating model accuracy and predictive performance from independent test data our results show that a percentile based classification scheme excels over a manual classification of the predictor variables because differing abundances in manually defined bins reduce the reliability of the conditional independence tests a key and often neglected prerequisite for the wofe method the conditional dependence between total curvature and flow accumulation precludes their joint use in the model slope gradient has the highest true positive rate 88 although the fraction of area classified as susceptible is very large 37 the predictive performance i e the reduction of false positives is improved when combined with either total curvature or flow accumulation bootstrapping shows that the combination of slope and flow accumulation provides more reliable predictions than the combination of slope and total curvature and helps refining the use of slope area plots for identifying morphometric fingerprints of debris flow source areas an approach used outside the field of landslide susceptibility assessments

a new late quaternary palaeohydrological record from the humid tropics of northeastern australia abstract high resolution x ray fluorescence xrf is presented as a robust palaeoclimatic proxy suitable for use on late pleistocene to holocene sediments located in a volcanic crater on the atherton tableland in northeastern queensland australia the proxy allows identification of wet and dry shifts in a complex sedimentary sequence comprised of peat gyttja laminated organic rich muds and fine clastic silt rich sediments significant correlation is found between the xrf record and other proxies including magnetic susceptibility humification grain size macrocharcoal 13c and c n and pollen sixteen wetter periods are identified in the 37 ka sedimentary record for bromfield swamp three wetter periods commence in late marine isotope stage 3 nine in the early glacial one in the late de glacial and four in holocene nineteen drier periods are identified four in late mis 3 seven in the early glacial one during the lgm one in the late de glacial period and six in the holocene the xrf record for bromfield swamp is specifically used to identify periods of abrupt climate change marked changes in effective precipitation are detected at 32 690 30 080 24 660 21 870 11 880 10 020 9170 and 5120 cal yr bp the detection of these abrupt climate events may allow correlation with records from terrestrial sites across the southern hemisphere and potentially the northern hemisphere

modeling the stability of terraced slopes an approach from valtellina northern italy this study focuses on the relationships between hydrological processes and the stability of terraced slopes emphasis is given to the presence of dry stone retaining walls and how to explicitly consider them when performing a distributed stability analysis valtellina an alpine valley of northern italy is selected as study area in detail the slope uphill the village of tresenda affected by several superficial landslides since 1983 is studied dry stone walls heavily influence the hydrological and geotechnical processes at the slope scale and it is therefore crucial to consider them when performing a stability analysis on mountainous terraced areas walls are usually 0 60 1 00 m wide and therefore base maps digital elevation models and soil depth map with a horizontal resolution of 1 m have been appositely derived working at this horizontal resolution leads to the failure of some basic assumptions of the infinite slope method usually applied for distributed stability analysis in this study we propose an alternative approach based on the global method of equilibrium applied to sections of single terraces one cell wide a specific sensitivity analysis allowed to fix some constrains to the model in order to improve the reliability of the results under different mechanical and hydrological conditions the proposed stability model was calibrated and evaluated on recorded past rainfall events it resulted to be a good instrument for the identification of the most unstable areas when stressed with high pore water pressure conditions

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

geology and lithic procurement in upper palaeolithic europe a weights of evidence based gis model of lithic resource potential abstract in this paper we examine ways to predict the distribution of siliceous rock in europe using a bayesian technique known as weights of evidence we use the technique to classify bedrock geological formations in terms of their likelihood of yielding tool quality lithic raw materials and we use the results to re examine possible causes of a west east cline in maximum lithic raw material transfer distances observed when comparing sites in both middle and upper palaeolithic europe it is evident from our results that there is a decline in abundance of geological formations highly predictive of tool quality rock along a west east cline predominantly reflecting a decrease in abundance of jurassic and cretaceous chert bearing sedimentaries our results are consistent with an interpretation of the upper palaeolithic record of transfer distances as indicating special purpose procurement

exploring discrepancies between quantitative validation results and the geomorphic plausibility of statistical landslide susceptibility maps abstract empirical models are frequently applied to produce landslide susceptibility maps for large areas subsequent quantitative validation results are routinely used as the primary criteria to infer the validity and applicability of the final maps or to select one of several models this study hypothesizes that such direct deductions can be misleading the main objective was to explore discrepancies between the predictive performance of a landslide susceptibility model and the geomorphic plausibility of subsequent landslide susceptibility maps while a particular emphasis was placed on the influence of incomplete landslide inventories on modelling and validation results the study was conducted within the flysch zone of lower austria 1 354 km 2 which is known to be highly susceptible to landslides of the slide type movement sixteen susceptibility models were generated by applying two statistical classifiers logistic regression and generalized additive model and two machine learning techniques random forest and support vector machine separately for two landslide inventories of differing completeness and two predictor sets the results were validated quantitatively by estimating the area under the receiver operating characteristic curve auroc with single holdout and spatial cross validation technique the heuristic evaluation of the geomorphic plausibility of the final results was supported by findings of an exploratory data analysis an estimation of odds ratios and an evaluation of the spatial structure of the final maps the results showed that maps generated by different inventories classifiers and predictors appeared differently while holdout validation revealed similar high predictive performances spatial cross validation proved useful to expose spatially varying inconsistencies of the modelling results while additionally providing evidence for slightly overfitted machine learning based models however the highest predictive performances were obtained for maps that explicitly expressed geomorphically implausible relationships indicating that the predictive performance of a model might be misleading in the case a predictor systematically relates to a spatially consistent bias of the inventory furthermore we observed that random forest based maps displayed spatial artifacts the most plausible susceptibility map of the study area showed smooth prediction surfaces while the underlying model revealed a high predictive capability and was generated with an accurate landslide inventory and predictors that did not directly describe a bias however none of the presented models was found to be completely unbiased this study showed that high predictive performances cannot be equated with a high plausibility and applicability of subsequent landslide susceptibility maps we suggest that greater emphasis should be placed on identifying confounding factors and biases in landslide inventories a joint discussion between modelers and decision makers of the spatial pattern of the final susceptibility maps in the field might increase their acceptance and applicability

regionalization of rainfall thresholds an aid to landslide hazard evaluation rainfall soil properties and morphology are major factors controlling shallow landsliding a series of meteorological events that triggered soil slips in northern italy were studied to define rainfall thresholds and to evaluate a possible regionalization soil properties triggering rainfall and local lithological and morphometrical settings of different sites were used as input to an infiltration model the approach allows the recognition of several triggering conditions in the piedmont pre alpine and alpine regions this suggests the need for different rainfall thresholds with respect to those derived with other methods intensity versus rainfall duration relationships become particularly important when related to soil permeability and thickness and demonstrate the role of antecedent precipitation events with exceptional water discharge from obstructed road culverts reveal the role played by anthropic structures in triggering such phenomena different approaches to slope stability analysis are shown taking into account bedrock lithology topography seepage and local saturation conditions

mapping landslide susceptibility from small datasets a case study in the pays de herve e belgium a landslide susceptibility map is proposed for the pays de herve e belgium where large landslides affect cretaceous clay outcrop areas based on a bayesian approach this gis supported probabilistic map identifies the areas most susceptible to deep landslides the database is comprised of the source areas of ten pre existing landslides i e a sample of 154 grid cells and of six environmental data layers namely lithology proximity to active faults slope angle and aspect elevation and distance to the nearest valley floor a 30 m resolution dem from the belgian national geographical institute is used for the analysis owing to the small size of the sample a special cross validation procedure of the susceptibility map is performed which uses in an iterative way each of the landslides to test the predictive power of the map derived from the other landslides four different sets of variables are used to produce four susceptibility maps whose prediction curves are compared while the prediction rates associated with the models not involving the proximity to active fault criterion are comparable to those of the models considering this variable strong weaknesses inherent in the fault data on which the latter rely suggest that the final susceptibility map should be based on a model that excludes any reference to fault this highlights the difference between a triggering factor and determining factors and in the same time broadens the scope of the produced map a single reactivated slide is also used to test the possibility of predicting future reactivation of existing landslides in the area finally the need for geomorphological control over the mathematical treatment is underlined in order to obtain realistic prediction maps 2007 elsevier b v all rights reserved

predicting landslides for risk analysis spatial models tested by a cross validation technique abstract a landslide hazard map is intended to show the location of future slope instability most spatial models of the hazard lack reliability tests of the procedures and predictions for estimating the probabilities of future landslides thus precluding use of the maps for probabilistic risk analysis to correct this deficiency we propose a systematic procedure comprising two analytical steps relative hazard mapping and empirical probability estimation a mathematical model first generates a prediction map by dividing an area into prediction classes according to the relative likelihood of occurrence of future landslides conditional by local geomorphic and topographic characteristics the second stage estimates empirically the probability of landslide occurrence in each prediction class by applying a cross validation technique cross validation a blind test here using non overlapping spatial or temporal subsets of mapped landslides evaluates accuracy of the prediction and from the resulting statistics estimates occurrence probabilities of future landslides this quantitative approach exemplified by several experiments in an area near lisbon portugal can accommodate any subsequent analysis of landslide risk