Made available in DSpace on 2014-06-11T19:26:15Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-02-04Bitstream added on 2014-06-13T18:29:47Z : No. of bitstreams: 1 benessiuti_mf_me_bauru.pdf: 4336666 bytes, checksum: b38250d3f308f9ca935e1e148d3fa7a0 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / A região das nascentes do ribeirão Guaratinguetá, localizada no contraforte da Serra da Mantiqueira, Vale do Paraíba, tem sido intensamente modificada por ações antrópicas criando condições que favorecem os movimentos de massa, princiapalmente devido à supressão da mata nativa. Estas ações, somada ao aumento a intensidade de chuvas sobre uma complexa geologia da região, têm potencializado os escorregamentos translacionais, de modo que foram registradas mais de 40 ocorrências, nas chuvas do final de 2008 e início de 2009. Neste contexto, as proposta desta dissertação é de identificar os mecanismos que geram essas instabilidades através da avaliação das características geotécnicas de dois escorregamentos característicos na bacia do ribeirão Guaratinguetá. Para isso, as atividades envolveram ensaios de laboratório e de campo. No laboratório foram realizados ensaios para a caracterização completa das amostras, ensaios de sucção, para determinação das curvas características, e ensaios de cisalhamento direto, para determinação dos parâmetros de resistência. No campo, foram determinadas as propriedades hidráulicas através do permeâmetro de Guelph e a resistência à penetração dos horizontes utilizando o Penetrômetro Dinâmico de Cone. O estudo dos possíveis processos de identificação de instabilidade foi realizado a partir de retro-análises dos dois escorregamentos estudados, através do software SLOPE/W, da GeoSlope, e de simulações de cenários, através do modelo matemático Shalstab. Nestas análises, foram consideradas diferentes hipóteses relativas à presença de água no subsolo, onde foram verificados os respectivos fatores de segurança. Os resultados das retro-análises indicam coerência entre as superfícies previstas e observadas no campo, para a condição de solo saturado acima da superfície de ruptura e solo na umidade residual... / The land degradation process as consequences of deforestation and farming activities at the northem part of the Guaratinguetá creek watershed, Paraíba Valley, is compromising the environmental balance of the region traduced by increase in the numbers of shallow landslides occurring during rain seasons. In summer 2009, more than 40 shallow landslides occurred during an intense rainfall with serious consequence for the local population. In this context, the purpose of this dissertation is to understand the mechanism that triggered the soil movement based on geotechnical investigation of two landslides in the Guaratinguetá creek watershed. The geotechnical profiles of two landslides and the hydraulic parameters were determined by field tests using Dynamic Cone Penetrometer and Guelph Permeameter. In laboratory, physical and mechanical soil properties were determined. The shear strength parameters were obtained by direct shear tests on undisturbed speciments for three initial gravimetric water contents (residual, natural and saturated). The instability process was inferrred by back-analysing these two landslides using the SLOPE/W, GeoSlope, and simulating scenarios using SHALSTAB model. These analyses took into account the physical properties and the shear strength parameters of the solis for different water contents. The predicted slip surfaces were in agreement with the observed ones when the analyses considered the soil parameters above the slip surface as saturated and the soil parameters below the slip surface as in residual water content condition. The susceptibility map using SHALSTAB were then carried out for the soil parameters for satured condition. The influence of the vegetation (root strength) was inserted in the analyses by a scale factor based onn Algebra Map Technique. The validation of the applied methodology was verified by crossing the predicted unstable... (Complete abstract click electronic access below)

Made available in DSpace on 2014-06-11T19:32:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2004-04-14Bitstream added on 2014-06-13T19:02:49Z : No. of bitstreams: 1 araujo_pc_dr_rcla.pdf: 6448977 bytes, checksum: a417ef7a09cc4dcb465b4c84dfc411b9 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Os escorregamentos são os principais processos ligados à dinâmica externa, que estão em desenvolvimento nas escarpas da Serra do Mar, o que tem despertado grande interesse científico e motivado o desenvolvimento de trabalhos visando o entendimento de seus mecanismos, pois estão intimamente relacionados a situações de risco. Contemplando as mais variadas formas de abordagens, os trabalhos desenvolvidos nessa região tem um ponto em comum: As análises, em sua grande maioria, são feitas através de modelos analógicos, que utilizam medidas diretas e apresentam resultados qualitativos. No presente trabalho, apresenta-se uma abordagem quantitativa que utiliza recursos da geotecnologia para gerar mapas de suscetibilidade a escorregamentos através do método pesos das evidências (WOFE), baseado em probabilidade condicional ou Bayesiana. Esse método é utilizado para medir as relações espaciais entre eventos já ocorridos e os mapas de evidências associados aos condicionantes desses eventos. Um pressuposto importante desse método é a independência condicional entre as evidências, sendo sua avaliação feita através dos métodos estatísticos qui-quadrado e teste global. O método proposto foi aplicado em uma área do Município de São Sebastião, litoral norte do Estado de São Paulo, utilizando mapas com padrões binários. A obtenção dos mapas binários obedeceu ao critério de contraste máximo, que é a medida de correlação espacial entre os escorregamentos e as evidências. A avaliação dos resultados obtidos indica que a abordagem utilizada apresenta potencial para aplicação em estudos sobre suscetibilidade a escorregamentos e avaliações sobre risco, em função do uso de probabilidade condicional. / Landslide is the main process linked to external dynamic that take place in the Mar Mountain Range (Serra do Mar) escarpments. It has been of great scientific interest and has motivated researches that aim the comprehension of its mechanisms. The approaches have been diversified, but with a common sense: the analyses are mainly made through analogical models, using direct measurements and showing qualitative results. Alternatively, this work shows a quantitative approach, using geotechnology resorts that give raise to landslides susceptibility maps through the weights of evidence method (WOFE). This method, based in the conditional or bayesian probability, is useful to measure the spatial correlations among events and evidence maps, which are selected as factors that influence the occurrence of these events. The conditional independence between the evidence maps is an important purpose of the WOFE method, and the evaluation is made through the overall test and chi-square statistic methods. The method was applied in an area of the São Sebastião County, in the North Coast of the São Paulo State, Brazil, using binary maps. The binary maps were the result of the reclassification using the maximum contrast criterion, which is the measurement of the spatial correlation between landslides and evidences. The evaluation of the results show that the approach presents potential for application in studies on landslide susceptibility and evaluations on risk, based of the use of conditional probability.

Orientador: Paulina Setti Riedel / Banca: Ardemirio de Barros Silva / Banca: Arlei Benedito Macedo / Banca: Ricardo Vedovello / Banca: Iandara Alves Mendes / Resumo: Os escorregamentos são os principais processos ligados à dinâmica externa, que estão em desenvolvimento nas escarpas da Serra do Mar, o que tem despertado grande interesse científico e motivado o desenvolvimento de trabalhos visando o entendimento de seus mecanismos, pois estão intimamente relacionados a situações de risco. Contemplando as mais variadas formas de abordagens, os trabalhos desenvolvidos nessa região tem um ponto em comum: As análises, em sua grande maioria, são feitas através de modelos analógicos, que utilizam medidas diretas e apresentam resultados qualitativos. No presente trabalho, apresenta-se uma abordagem quantitativa que utiliza recursos da geotecnologia para gerar mapas de suscetibilidade a escorregamentos através do método "pesos das evidências" (WOFE), baseado em probabilidade condicional ou Bayesiana. Esse método é utilizado para medir as relações espaciais entre eventos já ocorridos e os mapas de evidências associados aos condicionantes desses eventos. Um pressuposto importante desse método é a independência condicional entre as evidências, sendo sua avaliação feita através dos métodos estatísticos qui-quadrado e teste global. O método proposto foi aplicado em uma área do Município de São Sebastião, litoral norte do Estado de São Paulo, utilizando mapas com padrões binários. A obtenção dos mapas binários obedeceu ao critério de contraste máximo, que é a medida de correlação espacial entre os escorregamentos e as evidências. A avaliação dos resultados obtidos indica que a abordagem utilizada apresenta potencial para aplicação em estudos sobre suscetibilidade a escorregamentos e avaliações sobre risco, em função do uso de probabilidade condicional. / Abstract: Landslide is the main process linked to external dynamic that take place in the Mar Mountain Range (Serra do Mar) escarpments. It has been of great scientific interest and has motivated researches that aim the comprehension of its mechanisms. The approaches have been diversified, but with a common sense: the analyses are mainly made through analogical models, using direct measurements and showing qualitative results. Alternatively, this work shows a quantitative approach, using geotechnology resorts that give raise to landslides susceptibility maps through the "weights of evidence" method (WOFE). This method, based in the conditional or bayesian probability, is useful to measure the spatial correlations among events and evidence maps, which are selected as factors that influence the occurrence of these events. The conditional independence between the evidence maps is an important purpose of the WOFE method, and the evaluation is made through the overall test and chi-square statistic methods. The method was applied in an area of the São Sebastião County, in the North Coast of the São Paulo State, Brazil, using binary maps. The binary maps were the result of the reclassification using the maximum contrast criterion, which is the measurement of the spatial correlation between landslides and evidences. The evaluation of the results show that the approach presents potential for application in studies on landslide susceptibility and evaluations on risk, based of the use of conditional probability. / Doutor

Empirically-based models of landslide distribution and susceptibility are currently the most commonly used approach for mapping probabilities of landslide initiation and analyzing their association with natural and anthropogenic environmental factors. In general, these models statistically estimate susceptibility based on the predisposition of an area to experience a landslide given a range of environmental factors, which may include land use, topography, hydrology and other spatial attributes. Novel statistical approaches include the generalized additive model (GAM), a non-parametric regression technique, which is used in this study to explore the relationship of landslide initiation to topography, rainfall and forest land cover and logging roads on Vancouver Island, British Columbia. The analysis is centered on an inventory of 639 landslides of winter 2006/07. Data sources representing potentially relevant environmental conditions of landslide initiation are based on: terrain analysis derived from a 20-m CDED digital elevation model; forest land cover classified from Landsat TM scenes for the summer before the 2006 rainy season; geostatistically interpolated antecedent rainfall patterns representing different temporal scales of rainfall (a major storm, winter and annual rainfall); and the main lithological units of surface geology. In order to assess the incremental effect of these data sources to predict landslide susceptibility, predictive performances of models based on GAMs are compared using spatial cross-validation estimates of the area under the ROC curve (AUROC), and variable selection frequencies are used to determine the prevalence of non-parametric associations to landslides. In addition to topographic variables, forest land cover (e.g., deforestation), and logging roads showed a strong association with landslide initiation, followed by rainfall patterns and the very general lithological classification as less important controls of landscape-scale landslide activity in this area. Annual rainfall patterns are found not to contribute significantly to model prediction improvement and may lead to model overfitting. Comparisons to generalized linear models (i.e., logistic regression) indicate that GAMs are significantly better for modeling landslide susceptibility. Overall, based on the model predictions, the most susceptible 4% of the study area had 29 times higher density of landslide initiation points than the least susceptible 73% of the study area (0.156 versus 0.005 landslides/km2).

Empirically-based models of landslide distribution and susceptibility are currently the most commonly used approach for mapping probabilities of landslide initiation and analyzing their association with natural and anthropogenic environmental factors. In general, these models statistically estimate susceptibility based on the predisposition of an area to experience a landslide given a range of environmental factors, which may include land use, topography, hydrology and other spatial attributes. Novel statistical approaches include the generalized additive model (GAM), a non-parametric regression technique, which is used in this study to explore the relationship of landslide initiation to topography, rainfall and forest land cover and logging roads on Vancouver Island, British Columbia. The analysis is centered on an inventory of 639 landslides of winter 2006/07. Data sources representing potentially relevant environmental conditions of landslide initiation are based on: terrain analysis derived from a 20-m CDED digital elevation model; forest land cover classified from Landsat TM scenes for the summer before the 2006 rainy season; geostatistically interpolated antecedent rainfall patterns representing different temporal scales of rainfall (a major storm, winter and annual rainfall); and the main lithological units of surface geology. In order to assess the incremental effect of these data sources to predict landslide susceptibility, predictive performances of models based on GAMs are compared using spatial cross-validation estimates of the area under the ROC curve (AUROC), and variable selection frequencies are used to determine the prevalence of non-parametric associations to landslides. In addition to topographic variables, forest land cover (e.g., deforestation), and logging roads showed a strong association with landslide initiation, followed by rainfall patterns and the very general lithological classification as less important controls of landscape-scale landslide activity in this area. Annual rainfall patterns are found not to contribute significantly to model prediction improvement and may lead to model overfitting. Comparisons to generalized linear models (i.e., logistic regression) indicate that GAMs are significantly better for modeling landslide susceptibility. Overall, based on the model predictions, the most susceptible 4% of the study area had 29 times higher density of landslide initiation points than the least susceptible 73% of the study area (0.156 versus 0.005 landslides/km2).

Orientador: George de Paula Bernardes / Banca: Eduardo Dell'Avanzi / Banca: Heraldo Luiz Giacheti / Resumo: A região das nascentes do ribeirão Guaratinguetá, localizada no contraforte da Serra da Mantiqueira, Vale do Paraíba, tem sido intensamente modificada por ações antrópicas criando condições que favorecem os movimentos de massa, princiapalmente devido à supressão da mata nativa. Estas ações, somada ao aumento a intensidade de chuvas sobre uma complexa geologia da região, têm potencializado os escorregamentos translacionais, de modo que foram registradas mais de 40 ocorrências, nas chuvas do final de 2008 e início de 2009. Neste contexto, as proposta desta dissertação é de identificar os mecanismos que geram essas instabilidades através da avaliação das características geotécnicas de dois escorregamentos característicos na bacia do ribeirão Guaratinguetá. Para isso, as atividades envolveram ensaios de laboratório e de campo. No laboratório foram realizados ensaios para a caracterização completa das amostras, ensaios de sucção, para determinação das curvas características, e ensaios de cisalhamento direto, para determinação dos parâmetros de resistência. No campo, foram determinadas as propriedades hidráulicas através do permeâmetro de Guelph e a resistência à penetração dos horizontes utilizando o Penetrômetro Dinâmico de Cone. O estudo dos possíveis processos de identificação de instabilidade foi realizado a partir de retro-análises dos dois escorregamentos estudados, através do software SLOPE/W, da GeoSlope, e de simulações de cenários, através do modelo matemático Shalstab. Nestas análises, foram consideradas diferentes hipóteses relativas à presença de água no subsolo, onde foram verificados os respectivos fatores de segurança. Os resultados das retro-análises indicam coerência entre as superfícies previstas e observadas no campo, para a condição de solo saturado acima da superfície de ruptura e solo na umidade residual... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The land degradation process as consequences of deforestation and farming activities at the northem part of the Guaratinguetá creek watershed, Paraíba Valley, is compromising the environmental balance of the region traduced by increase in the numbers of shallow landslides occurring during rain seasons. In summer 2009, more than 40 shallow landslides occurred during an intense rainfall with serious consequence for the local population. In this context, the purpose of this dissertation is to understand the mechanism that triggered the soil movement based on geotechnical investigation of two landslides in the Guaratinguetá creek watershed. The geotechnical profiles of two landslides and the hydraulic parameters were determined by field tests using Dynamic Cone Penetrometer and Guelph Permeameter. In laboratory, physical and mechanical soil properties were determined. The shear strength parameters were obtained by direct shear tests on undisturbed speciments for three initial gravimetric water contents (residual, natural and saturated). The instability process was inferrred by back-analysing these two landslides using the SLOPE/W, GeoSlope, and simulating scenarios using SHALSTAB model. These analyses took into account the physical properties and the shear strength parameters of the solis for different water contents. The predicted slip surfaces were in agreement with the observed ones when the analyses considered the soil parameters above the slip surface as saturated and the soil parameters below the slip surface as in residual water content condition. The susceptibility map using SHALSTAB were then carried out for the soil parameters for satured condition. The influence of the vegetation (root strength) was inserted in the analyses by a scale factor based onn Algebra Map Technique. The validation of the applied methodology was verified by crossing the predicted unstable... (Complete abstract click electronic access below) / Mestre

The purpose of this study is to evaluate and to compare the results of bivariate statistical analysis conducted with three different data sets in Geographical Information Systems (GIS) based landslide susceptibility mapping applied to the Devrek region. The data sets are created from the seed cells of crowns and flanks, only crowns, and only flanks of the landslides by using 10 different parameters of the study area. To increase the data dependency of the analysis, all parameter maps are classified into equal frequency classes based directly on the percentile divisions of each seed cells data set. The resultant maps of the landslide susceptibility analysis indicate that all data sets produce acceptable results. In each seed cell data set analysis, elevation, lithology, slope, aspect and drainage density parameters are found to be the most contributing factors in landslide occurrences. The results of the three data sets are compared by Seed Cell Area Index (SCAI). This comparison shows that the crowns data set produces the most accurate and successful landslide susceptibility map of the study area.

This thesis has examined the 30km long rail corridor through the Lower Buller Gorge, on the Stillwater Ngakawau Line, between SNL96 and 126km, using a landslide risk management approach. The project area is characterised by high annual rainfall (>2,000mm per year), and steep topography (slopes typically ≥20°) adjacent to the rail corridor. The track formation generally follows the natural contour near the base of the hillslope through the Lower Buller Gorge, and consequently involves many curves but relatively limited cut slopes into adjacent rock outcrops. The distance between the base of adjacent hillslopes and rail is frequently <2m horizontally. A variety of basement and Tertiary lithologies are present, including granite, breccias, indurated sandstone/mudstone, and limestone. The primary focus of this thesis has been on upslope-sourced landsliding onto the rail corridor, and on two short lengths (20m and 450m) that currently have a 25km/hour speed restriction imposed at Whitecliffs and Te Kuha respectively. Rainfall-induced and earthquake-generated landslide triggering mechanisms were examined in detail. A landslide inventory has been compiled to determine the characteristics and distribution of identified slope failures over time, and to establish any correlation with topography and geology. Sixty individual landslide events were identified since the line became fully operational in the 1940s, based on desktop reviews, and field inspections for more recent events. To reflect the presence of small magnitude landslide events, a project-specific logarithmic classification of landslides was adopted from <10m³ (very small volume) to ≥10,000m³ (very large volume). An absence of a higher proportion of ‘very small’ to ‘small’ landslide volumes (<100m³) in the inventory reflects incomplete reporting of these comparatively lower magnitude, but higher frequency, events. The establishment of a robust landslide inventory to document future events, in a consistent and readily accessible format, is required for continued monitoring and review of landslide risk management practices in the Lower Buller Gorge. Combining landslide inventory data and physical characteristics of the project area enabled the development of a qualitative landslide zonation map that assigned ‘high’, ‘high-moderate’, ‘moderate’ and ‘low’ landslide susceptibility classes. The principal area of slope instability above the rail corridor is 22.5km in length between SNL103.5 and 126.0km, associated predominantly with basement lithologies (Tuhua Granite; Hawks Crag Breccia; Greenland Group). The most frequently occurring landslides are shallow, typically less than 3m deep, translational failures triggered in regolith or colluvium materials. Rainfall-induced debris slides and flows are dominant, given the high annual rainfall and associated high frequency of high intensity or long duration rainfall events. Very small to medium landslides (<1,000m³) have the potential to impact the rail corridor with an average frequency of around one every two years, causing damage to infrastructure or affecting rail operations. Very large landslides (≥10,000m³) can be expected every 10 to 20 years based on a limited historical record. The narrow rail corridor and absence of sufficient catch areas above or adjacent to the rail causes continual operational challenges due to upslope-sourced landslide debris, and high susceptibility to slope failures, particularly west of SNL103.50km. Development of a rainfall-threshold for proactive inspection of the rail corridor is recommended, including the establishment of a rain gauge network through the Lower Buller Gorge. Earthquake-generated landslides significantly impacted the rail during the magnitude 7.1 Inangahua earthquake in 1968 and to a much lesser extent during the magnitude 6.1 Westport earthquake in 1991. The rail was not fully constructed through the Lower Buller Gorge at the time of the magnitude 7.8 Buller (Murchison) Earthquake in 1929, which generated widespread landsliding in the Buller and Nelson regions. Earthquake-generated landsliding can be expected through the Lower Buller Gorge from earthquakes of magnitude ≥6, and track inspection is recommended in the event of magnitude 5 or greater earthquakes. Detailed geological characterisation and mapping at Whitecliffs and Te Kuha was conducted, including a LiDAR survey at Whitecliffs that enabled visualisation of the ground surface without the interference of vegetation. The limestone outcrop at Whitecliffs comprises 60-70m high near-vertical cliffs with a well-established talus apron at the base, extending to the rail corridor. Three widely spaced open fractures sets are present at the top of Whitecliffs that propagate into the cliff-face. There has been no detectable movement on selected key fracture sets since monitoring commenced in 1993 and there is no confirmed evidence of large-scale cliff collapse during the 1968 Inangahua earthquake. Whitecliffs is not as susceptible to failure as other slopes inspected in the project area due to structural controls, primarily being the dipping of strata back into the cliff-face and widely space joint sets. Establishment of inspection protocols for earthquake events impacting the area, including real-time monitoring of selected fractures at Whitecliffs is recommended. A 2km-length corridor site model produced for Te Kuha demonstrated ‘high’ landslide susceptibility is not confined to slopes above the existing 450m speed restriction zone. Removal of the speed restrictions at Whitecliffs and Te Kuha can be considered, as the increased exposure time is not considered sufficient justification given the extent of other susceptible areas to landsliding affecting the Lower Buller Gorge rail corridor. The principal conclusion from this thesis project is that there is on-going risk to rail operations predominantly from shallow translational landsliding in regolith-colluvium materials. The majority of these will be generated by long-duration or intense rainfall events. Development of threshold-based methods for effective track management is recommended, including the establishment of a rain gauge network through the Lower Buller Gorge, and landslide inventory database. Site-specific engineering measures could be adopted, such as catch benches or avalanche-type shelters, where justified on a cost-benefit basis.

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.

Various biotic and abiotic agents are changing forests. Prolonged human activities substantially could cause not only different changes in forests but also could accelerate natural hazards in the Anthropocene. Despite several remote sensing-based research in forest changes, there is a need for a holistic study that could visualize different dimensions of anthropogenic-induced forest changes such as forest loss, forest fragmentation, and forest degradation. Besides, the effects of these changes require to be investigated in the natural hazards’ studies in forest regions. This research was accomplished for holistic assessing of long-term forest loss, forest fragmentation, and forest degradation induced by human activities such as sprawling residential areas and expanding road networks in northeast Iran. Moreover, it has investigated the significance of forest dynamics in analyzing of landslide susceptibility in the forest regions. The time series of Landsat data with the contribution of aerial photos were employed to investigate long-term forest changes in three spans from 1966 to 2016. The expansion of forest roads was extracted from a combination of satellite images and topographic maps. Both pixel– and object-based approaches were used for analyzing forest changes. The spatial autocorrelation indicators and spatial regression models were applied for visualizing patterns of forest changes and possible relationships between forest changes and the expansion of residential areas and road networks. Furthermore, the detection of old and new landslide events was accomplished through Sentinel-1 and -2 images and DEM derivatives using object-oriented random forest method. The significance of conditioning and triggering factors that control the susceptibility of protected and non-protected forests to landslides was explored using the object-based random forest approach as well. Key findings revealed that the expansion of residential areas and rural roads have increasingly heightened the rates of forest loss before 2000. However, the spatial patterns of forest dynamics were changed from forest loss to forest fragmentation and forest degradation– along with the expansion of forest and mine roads– since the 1980s. Although the topographic and hydrologic features were the top influential predictors that control the susceptibility of protected forests to landslides, the natural and anthropogenic triggers have obtained significant values in non-protected forests to the landslides as well; forest fragmentation and logging were the top features of anthropogenic triggers. This research verifies that influential variables are different either for detecting landslides or for assessing landslide susceptibility in different forest regions. The spatial-based regression models showed higher efficiency than the traditional regression model for modelling relationships between forest changes and anthropogenic- induced drivers; however, there was no priority between spatial models. Random forest algorithm demonstrated satisfactory accuracy for mapping of both old and new landslides and landslide susceptibility with higher accuracy in the protected forests. This research has investigated human-induced forest changes; however, other abiotic and biotic agents may cause these changes such as climate hazards, forest fires, insect outbreaks, pathogens, and other natural hazards that need to be explored in the future studies. / Verschiedene biotische und abiotische Faktoren verursachen Veränderungen im Wald. Dauerhafte menschliche Eingriffe im Anthropozän könnten nicht nur zu unterschiedlichen Typen von Veränderungen im Wald selbst führen, sondern auch bestehende Naturgefahren verstärken. Trotz verschiedener fernerkundungsgestützter Forschungsarbeiten zu Waldveränderungen besteht Bedarf an einer holistischen Studie, welche verschiedene Dimensionen anthropogen verursachter Waldveränderungen wie Waldverlust, Waldfragmentierung und Waldschädigung aufzeigen kann. Außerdem ist es notwendig, die Auswirkungen derartiger Veränderungen in Naturgefahrenstudien für Waldgebiete zu untersuchen. Ziel dieser Forschung war es, eine holistische Bewertung von langfristigem Waldverlust, Waldfragmentierung und Waldschädigung durchzuführen, die durch menschliche Aktivitäten wie Ausbreitung von Siedlungsgebieten und Ausbau von Straßennetzen im Nordosten des Iran verursacht werden. Darüber hinaus hat diese Forschungsarbeit die Bedeutung der Walddynamik in der Analyse von Rutschungsneigung innerhalb von Waldgebieten untersucht. Um langfristige Waldveränderungen in drei Intervallen zwischen 1966 und 2016 zu untersuchen, wurden Zeitreihen von Landsat-Daten und zusätzlich von Luftbildern verwendet. Die Erweiterung der Waldwege wurde aus einer Kombination von Satellitenbildern und topographischen Karten extrahiert. Für die Analyse von Waldveränderungen wurden sowohl pixel- als auch objektbasierte Ansätze verwendet. Räumliche Autokorrelationsindikatoren und räumliche Regressionsmodelle wurden eingesetzt, um Muster von Waldveränderungen und Zusammenhänge zwischen Waldveränderungen und der Erweiterung von Wohngebieten und Straßennetzen zu visualisieren. Darüber hinaus wurde die Erkennung alter und neuer Erdrutsche aus Sentinel-1 und -2 Bildern und DEM-Derivaten unter Verwendung der objektorientierten „Random Forest “-Methode durchgeführt. Ebenfalls mit dem objektbasierten „Random Forest “-Ansatz wurde die Bedeutung von Konditionierungs- und Auslösefaktoren untersucht, welche die Suszeptibilität einer Fläche für Erdrutsche in geschützten und nicht geschützten Wäldern kontrollieren. Die zentralen Erkenntnisse sind, dass die Ausbreitung von Siedlungsflächen und der Ausbau von Landstraßen die Waldverluste vor dem Jahr 2000 zunehmend erhöht haben. Mit dem Ausbau von Wald- und Bergbaustraßen änderten sich jedoch seit den 1980er Jahren die räumlichen Muster der Walddynamik von Waldverlust hin zu Waldfragmentierung und Walddegradierung. Obwohl die orographischen und hydrologischen Merkmale die wichtigsten Einflussfaktoren hinsichtlich Suszeptibilität für das Auftreten von Erdrutschen in Schutzwäldern waren, haben weitere natürliche und anthropogene Auslöser Signifikanz erreicht innerhalb der nicht geschützten Waldflächen: Holzeinschlag und Waldfragmentierung waren dabei die dominierenden anthropogenen Auslöser. Die Studie bestätigt zudem, dass die Parameter für die Erkennung von Erdrutschen und für die Beurteilung der Rutschungs-Suszeptibilität an die verschiedenen Waldgebiete anzupassen sind. In der Modellierung der Beziehung zwischen Waldveränderungen und anthropogenen Einflüssen zeigten räumlich basierte Regressionsmodelle eine höhere Effizienz als das traditionelle Regressionsmodell; allerdings gab es keine klare Priorität innerhalb der räumlichen Modelle. Der „Random Forest “-Ansatz zeigte eine zufriedenstellende Genauigkeit sowohl bei der Kartierung historischer Erdrutsche als auch in der Bestimmung der Rutschungs-Suszeptibilität. Dabei lag die erreichte Genauigkeit in den geschützten Waldgebieten höher. Diese Forschungsarbeit hat vom Menschen verursachte Waldveränderungen untersucht. Da jedoch auch andere abiotische und biotische Faktoren die geschilderten Veränderungen verursachen können, sind weitere Studien notwendig. Diese könnten z. B. Klimaparameter, Waldbrände, Insektenschädigung und andere Naturgefahren einschließen.