Landslide susceptibility modeling based on GIS and novel bagging-based Kernel logistic regression

Landslides cause a considerable amount of damage around the world every year. Landslide susceptibility assessments are useful for the mitigation of the associated potential risks to local economic development, land use planning, and decision makers. The main aim of this study was to present a novel hybrid approach of bagging (B)-based kernel logistic regression (KLR), named the BKLR model, for spatial prediction of landslides in the Shangnan County, China. We first selected 15 conditioning factors for landslide susceptibility modeling. Then, the prediction capability of all conditioning factors was evaluated using the least square support vector machine method. Model validation and comparison were performed based on the area under the receiver operating characteristic curve and several statistical-based indexes, including positive predictive rate, negative predictive rate, sensitivity, specificity, kappa index, and root mean square error. Results indicated that the BKLR ensemble model outperformed and outclassed the KLR and the benchmark support vector machine model. Our findings overall confirmed that a combination of the meta model with a decision tree classifier based on a functional algorithm can decrease the overfitting and variance problems of data, which could enhance the prediction power of the landslide model. The resultant susceptibility maps could be useful for hazard mitigation in the study area and other similar landslide-prone areas

Morphological parameters causing landslides: A case study of elevation

The history of landslide susceptibility maps goes back about 50 years. Hazard and risk maps later followed these maps. Inventory maps provide the source of all these. There are different parameters selected specially for each field in the literature as well as parameters selected because they are easy to produce and obtain data. This study tried to research the effect of elevation on landslides by reviewing the literature in detail. The used class ranges and elevation values were reviewed and applied to map sections selected from Turkey. By analyzing the results, the goal was to determine at which elevation ranges landslides occurred. The study tried to investigate the effect of the parameter of elevation using data from the literature. It works to compare the elevation values for map sections selected to compare with the literature. The study comprises two stages. The first step tried to acquire statistical data by researching the data from the literature. The data were investigated in the second stage. For this purpose, close to 1.500 studies prepared between 1967 and 2019 were reviewed. According to the literature, the parameter of was used in analyses because it is easy to produce and is morphologically effective

Space-Time Landslide Predictive Modelling

Landslides are nearly ubiquitous phenomena and pose severe threats to people, properties, and the environment. Investigators have for long attempted to estimate landslide hazard to determine where, when, and how destructive landslides are expected to be in an area. This information is useful to design landslide mitigation strategies, and to reduce landslide risk and societal and economic losses. In the geomorphology literature, most attempts at predicting the occurrence of populations of landslides rely on the observation that landslides are the result of multiple interacting, conditioning and triggering factors. Here, we propose a novel Bayesian modelling framework for the prediction of space-time landslide occurrences of the slide type caused by weather triggers. We consider log-Gaussian cox processes, assuming that individual landslides stem from a point process described by an unknown intensity function. We tested our prediction framework in the Collazzone area, Umbria, Central Italy, for which a detailed multi-temporal landslide inventory spanning 1941-2014 is available together with lithological and bedding data. We tested five models of increasing complexity. Our most complex model includes fixed effects and latent spatio-temporal effects, thus largely fulfilling the common definition of landslide hazard in the literature. We quantified the spatio-temporal predictive skill of our model and found that it performed better than simpler alternatives. We then developed a novel classification strategy and prepared an intensity-susceptibility landslide map, providing more information than traditional susceptibility zonations for land planning and management. We expect our novel approach to lead to better projections of future landslides, and to improve our collective understanding of the evolution of landscapes dominated by mass-wasting processes under geophysical and weather triggers

Evaluation of environmental parameters in logistic regression models for landslide susceptibility mapping

The aim of this study was to determine how well the landslide susceptibility parameters, obtained by data-dependent statistical models, matched with the parameters used in the literature. In order to achieve this goal, 20 different environmental parameters were mapped in a well-studied landslide-prone area, the Asarsuyu catchment in northwest Turkey. A total of 4400 seed cells were generated from 47 different landslides and merged with different attributes of 20 different environmental causative variables into a database. In order to run a series of logistic regression models, different random landslide-free sample sets were produced and combined with seed cells. Different susceptibility maps were created with an average success rate of nearly 80%. The coherence among the models showed spatial correlations greater than 90%. Models converged in the parameter selection peculiarly, in that the same nine of 20 were chosen by different logistic regression models. Among these nine parameters, lithology, geological structure (distance/density), landcover-landuse, and slope angle were common parameters selected by both the regression models and literature. Accuracy assessment of the logistic models was assessed by absolute methods. All models were field checked with the landslides resulting from the 12 November 1999, Kaynasli Earthquake (Ms = 7.2)

Lur labainketen analisirako hurbilketa metodologikoa eskala erregionalean: Datuen bilketa, suszeptibilitate modeloak eta euri prezipitazioen atalaseak. Gipuzkoako Lurralde Historikoan aplikatua (Euskal Herria).

227 p.Lurraldearen zonazioa lur labainketak jasotzeko aukeren arabera, suszeptibilitate mapen bitartez hain zuzen ere, hauek eragindako kalteak arindu eta mehatxua eta arrisku maila ebaluatu ahal izateko oinarrizko pausoa da. Tesi honek bide-orri baten definizioa aurkezten du, hutsetik abiatuta, lurraldearen suszeptibilitate mapen garapenerako eskala erregionalean. Helburua ikuspegi metodologiko eguneratu bat zehaztea da, prozeduraren pauso bakoitzean hartutako erabakia zientifikoki justifikatuak eta onartua izan daitezen. Hainbat esperimentu eta aplikazio gauzatzeko Gipuzkoako Probintzia hautatu da (1980 km2) . Ezaugarri eta izaera desberdineko hainbat aldagai independente, mota eta iturri desberdineko lur labainketa inbentarioak eta metodo ezagun nahiz metodo berritzaileekin batera ikuspegi desberdinak jorratu dira, azkenean lan honek aurkezten dituen ondorioak lortzeko.Emaitzen arabera, inferentzia geomorfologikoaren beharra azpimarratu daiteke estatistikoki gidatutako arauen arabera aldagai independenteen hautaketa egiterako orduan, hala nola, aldagai kategorikoen transformatzea aldagai jarraietan suszeptibilitate-modeloak garatzerako orduan onuragarria dela ere ondorioztatu da. Gainera, lur labainketen suszeptibilitate modeloak kalibratzeko ikuskatutako eremu efektiboaren erabilera positiboa dela frogatu da, lur labainketen inbentarioa landa lanaren bitartez eskuratu den kasuetan. Bestalde, malda unitateen erabilerak lurralde unitate bezala, ohikoak diren pixel unitateak izan beharrean, landa laneko inbentario batek ezarri dezakeen ziurgabetasuna arintzeko ahalmena erakutsi du.Horretaz gain, lur labainketak gertatzeko beharrezko prezipitazio atalasa definitzeko algoritmo baten aplikazioak ikerketa eremu berberean, aurreikuspenak egiteko beharrezkoa den informazioa erakutsi du, alerta goiztiar sistema baterantz aurreratzen joateko dauden aukerak goraipatuz

Indirect impact of landslide hazards on transportation infrastructure

This thesis examines the indirect impact of natural hazards on infrastructure networks. It addresses several key themes and issues for hazard assessment, network modelling and risk assessment using the case study of landslides impacting the national road network in Scotland, United Kingdom. The research follows four distinct stages. First, a landslide susceptibility model is developed using a database of landslide occurrences, spatial data sets and logistic regression. The model outputs indicate the terrain characteristics that are associated with increased landslide potential, including critical slope angles and south westerly aspects associated with increased rates of solar irradiance and precipitation. The results identify the hillslopes and road segments that are most prone to disruption by landslides and these indicate that 40 % (1,700 / 4,300 km) of Scotland s motorways and arterial roads (i.e. strategic road network) are susceptible to landslides and this is above previous assessments. Second, a novel user-equilibrium traffic model is developed using UK Census origin-destination tables. The traffic model calculates the additional travel time and cost (i.e. indirect impacts) caused by network disruptions due to landslide events. The model is applied to calculate the impact of historic scenarios and for sets of plausible landslide events generated using the landslide susceptibility model. Impact assessments for historic scenarios are 29 to 83 % greater than previous, including £1.2 million of indirect impacts over 15 days of disruption at the A83 Rest and Be Thankful landslide October 2007. The model results indicate that the average impact of landslides is £64 k per day of disruption, and up to £130 k per day on the most critical road segments in Scotland. In addition to identifying critical road segments with both high impact and high susceptibility to landslides, the study indicates that the impact of landslides is concentrated away from urban centres to the central and north-west regions of Scotland that are heavily reliant on road and haulage-based industries such as seasonal tourism, agriculture and craft distilling. The third research element is the development of landslide initiation thresholds using weather radar data. The thresholds classify the rainfall conditions that are most commonly associated with landslide occurrence in Scotland, improving knowledge of the physical initiation processes and their likelihood. The thresholds are developed using a novel optimal-point threshold selection technique, high resolution radar and new rain variables that provide spatio-temporally normalised thresholds. The thresholds highlight the role of the 12-day antecedent hydrological condition of soils as a precursory factor in controlling the rain conditions that trigger landslides. The new results also support the observation that landslides occur more frequently in the UK during the early autumn and winter seasons when sequences or clustering of multiple cyclonic-storm systems is common in periods lasting 5 to 15 days. Fourth, the three previous elements are combined to evaluate the landslide hazard of the strategic road segments and a prototype risk assessment model is produced - a catastrophe model. The catastrophe model calculates the annual average loss and aggregated exceedance probability of losses due to the indirect impact of landslides in Scotland. Beyond application to cost-benefit analyses for landslide mitigation efforts, the catastrophe model framework is applicable to the study of other natural hazards (e.g. flooding), combinations of hazards, and other infrastructure networks

The occurrence, impacts and dynamics of debris flows in Brazil

Among the landslide types, debris flows represent a greater hazard to society due to their high destruction potential. In Brazil, debris-flow studies are still incipient when compared to other hydrogeomorphic processes and a good understanding of their dynamics is fundamental to supporting hazard and risk assessment studies. In particular, determining the spatialization of events and the extent of the impacts that the phenomenon represents in the country is crucial to supporting targeted and more in-depth studies. In this context, the main objectives of this thesis are to assess the societal impact of debris flows in Brazil and to propose a methodology that aims at reducing the potential damage that future events can cause in susceptible regions. A detailed post-event characterization of a debris-flow event is also conducted, as it is a fundamental step to understanding the phenomenon’s dynamics and can further support the proposal of the hazard assessment methodology. To determine the societal impact of debris flows, a catalogue of events that have caused fatalities and/or economic losses between 1920 and 2021 was created, which supported the debris-flow Mortality Rate (MR) calculation and the application of the so-called F-N Curves (Frequency of events vs. Number of Fatalities). In total, 45 debris-flow events were documented in the considered period, having caused more than 5,773 fatalities and 5.4 billion USD in economic losses. The city of Cubatão (state of São Paulo) shows the highest number of recorded events in the considered period (9), consolidating the status as the most debris-flow prone region in the country. A multi-step hazard assessment is, then, proposed using Cubatão as the test-site, based on the combination of Logistic Regression (LR) analysis, numerical simulation and rainfall back-analysis. The LR results highlight that rainfall is the main influencing factor in debris-flow initiation in the region and indicate the catchments more susceptible to the phenomenon. The simulation results, performed in the catchments indicated by the LR, show that the average runout distance in the region is 470 m, with an average peak flow height of 5 m and a peak velocity of 23 m s-1, according to the calibration based on two past debris-flow events. These results are comparable to the debris-flow event of February 2017 that occurred in the Pedra Branca catchment (Guaratuba, state of Paraná), in which a detailed post-event geomorphological characterization was conducted to estimate the event’s magnitude. The Guaratuba event was of a large-sized stony debris flow, with a total magnitude of 120,195 m3, a peak flow heigh of 7 m and a peak velocity of 26.5 m s-1. Debris-flow events both in Cubatão and Guaratuba are generally triggered by short duration (200 mm) precipitation, with return periods that vary from 3 to 15 years. Five levels of hazard (very low to very high) are, then, proposed in our hazard assessment method, based mainly on the 48-h accumulated rainfall, flow properties (height, velocity) and the spatial analysis of the elements (infrastructures, houses, etc.) at hazard. In Cubatão, industrial and residential areas in the projected debris-flow route generally exhibit the highest overall hazard levels, as many were developed in the depositional area of the phenomenon and near fluvial courses, where associated floods and flash floods may occur. As pointed out by recent studies, an increase in the frequency of extreme precipitation events is projected in the Serra do Mar region and when the general short return period of the debris-flow triggering rainfall is considered (105 m3) events are likely to occur in the next decade in the portions of the mountain range located in the states of São Paulo and Paraná. This thesis, therefore, is a contribution to better understanding the dynamics of debris flows in Brazil and is a step towards the prevention of future disasters.Unter den Rutschungsarten stellen Murgänge aufgrund ihres hohen Zerstörungspotentials eine größere Gefahr für die Gesellschaft dar. In Brasilien sind Murgangstudien im Vergleich zu anderen hydrogeomorphen Prozessen noch am Anfang und ein gutes Verständnis ihrer Dynamik ist essentiell für die Erstellung von Gefahren- und Risikobewertungsstudien. Insbesondere ist die Bestimmung des Ausmaßes der Auswirkungen, die das Phänomen in einer Region oder einem Land darstellt, von wesentlicher Bedeutungfür gezielte und eingehendere Studien. In diesem Zusammenhang besteht das Hauptziel dieser Arbeit darin, die gesellschaftlichen Auswirkungen von Murgängen in Brasilien zu bewerten und eine Methodik vorzuschlagen, die darauf abzielt, den potenziellen Schaden zu verringern, den zukünftige Ereignisse in anfälligen Regionen verursachen können. Eine detaillierte Nachuntersuchung eines Murgangereignisses wird ebenfalls durchgeführt, da dies ein grundlegender Schritt zum Verständnis der Dynamik des Phänomens ist und den Vorschlag der Gefahrenbewertungsmethodik weiter unterstützen kann. Um die gesellschaftlichen Auswirkungen von Murgängen zu bestimmen, wurde ein Katalog von Ereignissen erstellt, die zwischen 1920 und 2021 Todesopfer und/oder wirtschaftliche Schäden verursacht haben, was die Berechnung der Murgangmortalitätsrate (MR) und die Anwendung der sogenannten F-N unterstützten Kurven (Häufigkeit von Ereignissen vs. Anzahl Todesfälle) ermöglicht. Insgesamt wurden im betrachteten Zeitraum 45 Murgangereignisse dokumentiert, die mehr als 5.773 Todesopfer und 5,4 Milliarden US-Dollar an wirtschaftlichen Schäden verursachten. Die Stadt Cubatão (Bundesstaat São Paulo) weist die meisten Ereignisse auf und festigt damit ihren Status als die am stärksten von Murgängen bedrohte Region des Landes. Daher wird eine mehrstufige Gefährdungsbeurteilung vorgeschlagen und am Beispiel von Cubatão getestet, basierend auf einer Kombination von logistischer Regressionsanalyse (LR), numerischer Simulation und Niederschlagsrückanalyse. Die LR-Ergebnisse verdeutlichen, dass Niederschlag der Haupteinflussfaktor bei der Entstehung von Murgängen in der Region ist und zeigen die Einzugsgebiete, die für das Phänomen in der Region anfälliger sind. Die Simulationsergebnisse von zwei Murgangereignissen, die in diesen Einzugsgebieten durchgeführt wurden, zeigen, dass die durchschnittliche Auslaufstrecke in der Region 470 m beträgt, mit einer durchschnittlichen Fließhöhe von 5 m und einer Spitzengeschwindigkeit von 23 m s-1. Diese Ergebnisse sind vergleichbar mit dem Murgangereignis vom Februar 2017 im Einzugsgebiet von Pedra Branca (Guaratuba, Bundesstaat Paraná), bei dem eine detaillierte geomorphologische Charakterisierung nach dem Ereignis durchgeführt wurde, um das Ausmaß des Ereignisses abzuschätzen. Bei dem Guaratuba-Ereignis handelte es sich um einen großen steinigen Schuttstrom mit einer Gesamtgröße von 120.195 m3, einem Spitzenabfluss von 2.146,7 m3 s-1 und einer Spitzengeschwindigkeit von 26,5 m s-1. Murgangereignisse in Cubatão und Guaratuba wurden durch Niederschläge von kurzer Dauer ( 200 mm) mit Wiederkehrperioden von 3 bis 15 Jahren ausgelöst. Fünf Gefahrenstufen (sehr gering bis sehr hoch) werden dann in unserer Gefahrenbewertungsmethode vorgeschlagen, die hauptsächlich auf den Niederschlägen über 48 Stunden und Strömungseigenschaften basiert. In Cubatão weisen Industrie- und Wohngebiete in der prognostizierten Murgangroute im Allgemeinen die höchsten Gesamtgefahrenstufen auf, da diese sich überwiegend im Ablagerungsgebiet des Phänomens und in der Nähe von Flussläufen befinden, wo damit verbundene Überschwemmungen und Sturzfluten auftreten können. Wie neuere Studien zeigen, wird in der Region Serra do Mar eine Zunahme der Häufigkeit extremer Niederschlagsereignisse prognostiziert; unter Berücksichtigung der allgemein kurzen Wiederkehrperiode ( 105 m3) im nächsten Jahrzehnt in Teilen der Bergkette in den Bundesstaaten São Paulo und Paraná auftreten. Diese Arbeit trägt daher zum besseren Verständnis der Dynamik von Murgängen in Brasilien bei und ist ein Schritt zur Vermeidung zukünftiger Katastrophen.Entre os tipos de movimentos de massa, os fluxos de detritos representam um risco maior à sociedade devido ao seu alto potencial de destruição. No Brasil, os estudos de fluxos de detritos ainda são incipientes quando comparados a outros processos hidrogeomorfológicos e uma melhor compreensão da sua dinâmica é fundamental para subsidiar estudos de avaliação de perigos e riscos. A estimativa da extensão dos impactos que o fenômeno representa no país é, particularmente, fundamental para subsidiar estudos direcionados e mais aprofundados. Nesse contexto, os principais objetivos desta tese são de espacializar os eventos de fluxos de detritos e avaliar o impacto socioeconômico do fenômeno no Brasil, além de propor uma metodologia que tem como objetivo reduzir os danos potenciais que eventos futuros podem causar nas regiões mais suscetíveis. A caracterização detalhada pós-evento de um fluxo de detritos também é conduzida, uma vez que é um passo fundamental na compreensão da dinâmica do fenômeno e dá suporte à proposta de metodologia de avaliação de perigo. Para determinar o impacto socioeconômico dos fluxos de detritos, foi criado um banco de dados dos eventos que causaram fatalidades e/ou perdas econômicas entre 1920 e 2021, que serviu de base para o cálculo da Taxa de Mortalidade (TM) e a aplicação de Curvas F-N (Frequência de eventos vs. Número de Fatalidades). No total, 45 eventos de fluxo de detritos foram documentados no período considerado, causando mais de 5.773 mortes e US$ 5,4 bilhões em perdas econômicas. A cidade de Cubatão (SP) apresenta o maior número de eventos, consolidando-se como a região mais propensa a fluxos de detritos no país. Consequentemente, a proposta de uma metodologia de avaliação de perigo a fluxos de detritos em várias etapas é feita utilizando Cubatão como área piloto, que tem como base a combinação de análise de Regressão Logística (LR), simulação numérica e retro análise de eventos de chuva. Os resultados da LR destacam que a chuva é o principal fator de influência no início do fluxo de detritos na região, além de também indicarem as bacias mais suscetíveis ao fenômeno no local de estudo. Os resultados da simulação de fluxos de detritos nas bacias indicadas pelo LR mostram que a distância média de runout na região é de 470 m, com altura média do pico do fluxo de 5 m e velocidade de pico de 23 m s-1. Esses resultados são comparáveis ao evento de fluxo de detritos de fevereiro de 2017 que ocorreu na bacia hidrográfica de Pedra Branca (Guaratuba, estado do Paraná), no qual uma caracterização geomorfológica pós-evento detalhada foi realizada com o objetivo de estimar a magnitude do evento. O evento de Guaratuba foi um fluxo de detritos “rochoso” (stony debris flow) de grande porte, com magnitude total de 120.195 m3, altura do pico de vazão de 7 m e pico de velocidade de 26,5 m s-1. Os eventos de fluxo de detritos em Cubatão e Guaratuba são, de uma forma geral, desencadeados por precipitação de curta duração (200 mm), com períodos de retorno que variam de 3 a 15 anos. Cinco níveis de risco (muito baixo a muito alto) foram, então, propostos em nosso método de avaliação de perigo, baseado principalmente na chuva acumulada em 48 horas, propriedades cinemáticas do fluxo (altura de vazão, velocidade) e nos elementos no raio de perigo (infraestruturas, casas, etc.). As áreas industriais e residenciais na rota estimada de fluxo de detritos geralmente exibem os mais altos níveis de perigo geral na área piloto, uma vez que se desenvolveram na área de deposição do fenômeno e perto de cursos fluviais, onde podem ocorrer inundações e enxurradas associadas. Conforme apontado por estudos recentes, projeta-se um aumento na frequência de eventos extremos de precipitação na região da Serra do Mar e, quando se considera o curto período geral de retorno das chuvas desencadeadoras do fenômeno ( 105 m3) podem ocorrer na próxima década nas áreas consideradas nesta tese, localizadas na região da Serra do Mar paulista e paranaense. Esta tese, portanto, contribui para a melhor compreensão da dinâmica dos fluxos de detritos no Brasil e para a prevenção de futuros desastres