Tesis sobre el tema "Landslides inventary"

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.

LiDAR (Light Detection and Ranging) elevation data were collected in the Panther Creek Watershed, Yamhill County, Oregon in September and December, 2007, March, 2009 and March, 2010. LiDAR derived images from the March, 2009 dataset were used to map pre-historic, historic, and active landslides. Each mapped landslide was characterized as to type of movement, head scarp height, slope, failure depth, relative age, and direction. A total of 153 landslides were mapped and 81% were field checked in the study area. The majority of the landslide deposits (127 landslides) appear to have had movement in the past 150 years. Failures occur on slopes with a mean estimated pre-failure slope of 27° ± 8°. Depth to failure surfaces for shallow-seated landslides ranged from 0.75 m to 4.3 m, with an average of 2.9 m ± 0.8 m, and depth to failure surfaces for deep-seated landslides ranged from 5 m to 75m, with an average of 18 m ± 14 m. Earth flows are the most common slope process with 110 failures, comprising nearly three quarters (71%) of all mapped deposits. Elevation changes from two of the successive LiDAR data sets (December, 2007 and March, 2009) were examined to locate active landslides that occurred between the collections of the LiDAR imagery. The LiDAR-derived DEMs were subtracted from each other resulting in a differential dataset to examine changes in ground elevation. Areas with significant elevation changes were identified as potentially active landslides. Twenty-six landslides are considered active based upon differential LiDAR and field observations. Different models are used to estimate landslide susceptibility based upon landslide failure depth. Shallow-seated landslides are defined in this study as having a failure depth equal to less than 4.6 m (15 ft). Results of the shallow-seated susceptibility map show that the high susceptibility zone covers 35% and the moderate susceptibility zone covers 49% of the study area. Due to the high number of deep-seated landslides (58 landslides), a deep-seated susceptibility map was also created. Results of the deep-seated susceptibility map show that the high susceptibility zone covers 38% of the study area and the moderate susceptibility zone covers 43%. The results of this study include a detailed landslide inventory including pre-historic, historic, and active landslides and a set of susceptibility maps identifying areas of potential future landslides.

Developing detailed landslide inventory maps of prehistoric landslides is essential to interpret the frequency and conditions under which slopes have failed. When coupled with age estimates, landslide inventories can yield better predictions for future slope failures, thereby improving hazard assessments and increasing chances for mitigation. Developing proxies for landslide age is an important area of research, but age dating prehistoric landslides can be challenging due to sparse datable organic material within landslide deposits, and to time or access constraints. In this thesis, surface roughness of the landslide deposit is used to construct a best-fit age-roughness model that quantitatively assigns age based on smoothing of the deposit with time for landslides in the Green River Valley (GRV), located in King County, Washington. Hillslopes in the valley are composed of glacial sediments and are prone to failure caused by three main triggers: over steepening caused by lateral migration of the Green River, Holocene climatic change (precipitation and temperature), and seismicity (Cascadia Subduction Zone and the Seattle Fault). We examine the distribution of landslides in the GRV using high-resolution lidar data and find a threshold relief of approximately 60 m corresponds to landslide locations. Four dated samples with ages ranging from 492 to 0 cal. BP defined age-roughness models that showed 44 to 51 of the 61 mapped landslides occurred from 5000 to 100 cal. BP, after the climate changed to cooler and wetter conditions. These 61 landslides, on average, decrease in age as you move upstream, consistent with upstream migration of a knickzone. From these age-roughness models the GRV has a recurrence interval of one landslide every 38 years since 1000 cal. BP (26 landslides/1000 years), which has implications for managing landslide hazards.

Landslides, in their various forms, are a common hazard in mountainous terrain, especially in seismically active areas and regions of high rainfall. The West Coast region of New Zealand is dissected by many active faults, experiences frequent earthquakes and in many locations annual rainfall exceeds ten meters. Consequently, landslides are widespread in the region and since European settlement began, have been responsible for 27 deaths, along with frequent damages to road and rail infrastructure, settlements and agricultural land. This study identifies areas that are susceptible to rainfall triggered landslides in the West Coast region. To achieve this, a landslide susceptibility map was produced using bivariate statistics and the analytical hierarchy process. It has an accuracy that predicts 80% of all the landslides in the top 40% of the susceptibility scores on the map. As part of this process, 3221 rainfall triggered landslides and 522 earthquake (or other trigger) triggered landslides have been mapped and digitised into a Geographic Information System. In parallel with this, a descriptive historical catalogue of 1987 landslides has been compiled from the available sources. These new tools provide decision-makers with an enhanced means of managing landslide hazards in the West Coast region. In order to avoid misinterpretation the study has been carried out in compliance with the “Guidelines for landslide susceptibility, hazard and risk zoning for land use planning”, which was published in 2008 by the Joint Technical Committee on Landslides and Engineered Slopes. The tools developed in this thesis represent a fundamental step in land-use planning and set-up of landslide hazard management in the West Coast region.

A landslide inventory was conducted for the Redland and Estacada Quadrangles of western Oregon using LiDAR DEMs. Many of these landslides were field verified. In total, 957 landslides were mapped using LiDAR whereas previously, only 228 landslides were believed to exist in the study area based on SLIDO information. In Milo McIver State Park, 41 landslides were mapped using LiDAR. SLIDO indicated only three landslides present within the park. A sequence of seven terraces of the Clackamas River is mapped in Milo McIver State Park. Landslides in the park predominantly occur between these terraces. Soils studied from representative areas within landslide complexes and terrace surfaces help to formulate a soil chronosequence for the study area. The youngest soils, Entisols, develop in less than 1,600 years, Inceptisols between 1,600-10,000 years, and the oldest soils, Alfisols, develop in at least 10,000 years. Classifications of soil profiles netted ten Alfisols (mainly on upper terraces), 49 Inceptisols, and 20 Entisols (reactivated slides in the complexes). The soils are predominantly ML soils and have Loam and Silt Loam textures. Results of spectral analysis, carried out on the LiDAR DEMs, indicate that the spectral character of landslides changes with age. However, applying statistical tools such as the Kolmogorov-Smirnov test (K-S test) and cluster analysis suggest that it is not possible to use spectral analysis to determine the relative age of failed surfaces. The K-S test showed that the spectral character among landslides varies widely. Cluster analysis resulted groupings not based on age or terrain type. The result of the cluster analysis illustrates that it may not be realistic to use a single cutoff, which separates failed terrain from unfailed, in the spectral distributions to analyze an entire region. In all, the results of the spectral analysis were not conclusive. Individual landslides, not complexes, should be used in future studies, since complexes have slides that are continually reactivating. The landslides were also too young to display very much differentiation in age based on soils and spectral analysis. Essentially, a similar study should be conducted using individual landslides with a large age range for more conclusive results.

La création d’inventaires de glissements de terrain sert de base à l’évaluation quantitative de l’aléa et à la gestion du risque. Les cartes d’inventaires de mouvements gravitaires sont produites en utilisant des méthodes conventionnelles (campagnes de mesures de terrain, interprétation visuelle de photographies aériennes) et par des techniques de télédétection plus innovantes. Une des techniques les plus prometteuses pour la détection et la cartographie des glissements de terrain fait appel à la mesure de la déformation du sol par interférométrie radar satellitaire (InSAR). Cette thèse est consacrée à la constitution d’un inventaire multi-dates à partir de données multi-sources (incluant les données InSAR) en vue d’évaluer de façon quantitative l’aléa glissement de terrain. Les méthodes associent l’analyse de produits d’Observation de la Terre et des modélisations statistiques pour la caractérisation de l’aléa dans la vallée de l’Ubaye, une région rurale et montagneuse des Alpes du Sud. Elles ont été développées à l’échelle du versant (1:5.000-1:2.000) et à l’échelle régionale (1:25.000- 1:10.000). Pour la création des inventaires, cette étude propose une interprétation combinée de séries temporelles d’images SAR, de photographies aériennes, de cartes géomorphologiques, de rapports historiques et de campagnes de terrain. A l’échelle locale, une méthodologie d'interprétation guidée par la géomorphologie et utilisant l’InSAR a été proposée pour identifier les champs de déplacement des glissements de terrain et mesurer leur évolution. A l’échelle régionale, la distribution spatio-temporelle des glissements de terrain a été caractérisée et l’aléa a été calculé à partir des probabilités d’occurrence spatiale et temporelle pour une intensité donnée des phénomènes. L’occurrence spatiale est estimée grâce à un modèle multivarié (régression logistique). L’occurrence temporelle des mouvements gravitaires est évaluée grâce à un modèle de probabilité de Poisson permettant de calculer la probabilité de dépassement (incluant ou non un seuil de surface) pour plusieurs périodes de retour. Plusieurs unités d'analyse spatiale ont été utilisées pour la modélisation ; les résultats démontrent clairement leur influence sur les résultats. L’analyse de l’aléa a été réalisée sur quelques cas spécifiques. Des relations entre les (ré)activations de glissements de terrain et les facteurs déclenchants sont proposées
The analysis of landslide inventories is the basis for quantitative hazard assessment. Landslide inventory maps are prepared using conventional methods (field surveys, visual interpretation of aerial photographs) and new remote sensing techniques. One of the most promising techniques for landslide detection and mapping is related to the measurement of the ground deformation by satellite radar interferometry (InSAR).This doctoral thesis is dedicated to the preparation of a multi-date inventory, from multi-source data, including InSAR, for a quantitative assessment of landslide hazard. The methods associate the analysis of Earth Observation products and statistical modelling for the characterization of landslide hazard in a rural and mountainous region of the South French Alps. They have been developed at the slope (1:5000-1:2000) and the regional (1:25.000-1:10.000) scales. For the creation of a multi-date inventory, this study developed a combined interpretation of time series of SAR images, aerial photographs, geomorphological maps, historical reports and field surveys. At the slope-scale, a geomorphologically-guided methodology using InSAR was proposed to identify landslide displacement patterns and measure their kinematic evolution. At regional scale, spatio-temporal distribution of landslides is characterised and hazard is assessed by computing spatial and temporal probabilities of occurrence for a given intensity of the phenomena. The spatial occurrence is evaluated using a multivariate model (logistic regression). The temporal occurrence of landslide is estimated with a Poisson probability model to compute exceedance probabilities for several return periods. Different mapping units were used in the modelling, and their influence on the results is discussed. Analysis of landslide hazard is then proposed for some particular hotspots. Relationships between landslide (re)activations and triggering factors are envisaged

Contact relations, and bedrock and overburden characteristics for approximately 8100 ha of the upper Canyon Creek basin, Skamania County, Washington, have been assessed in order to determine the causes and extent of failures and to assign slope failure susceptibilities to the area. The study area is located in the western Cascade Range on land administered by the Gifford Pinchot National Forest. Clear-cutting over the past 30 years has impacted between 50% to 80% of the study area. The total surface area occupied by failure deposits (198.6 ha) is less than 2.5% of the study area. Failures occur by one of seven processes, in decreasing order of abundance: rockfall (53.6%), rock avalanche (25.3%), slumps (15.6%), streambank failures (3.4%), soil and debris slips (1%), snow avalanches (debris falls) (1%), and translational slides (0.1%). Integrity of the bedrock is primarily influenced by jointing characteristics, in particular: dilation, orientation and continuity. Groundwater is an important constituent in the failure of fragmental igneous bedrock, but has very little impact in inducing failure in compact igneous bedrock. Areas underlain by fragmental igneous bedrock have a proportionally greater number of translational and rotational failures. With increasing compact igneous bedrock content, small volume rockfall failures become more predominant. Sixteen to twenty percent of the roadbed surfaces in the study area are experiencing some type of failure. Up to 99 percent of roadbed failures are confined to the roadfill prism. Failure due to degradation of the subgrade is rarely obseived. Arcuate and sliver-like cracks, offsets, sinkholes, concentrations of potholes, broad slumps and chute formation in the roadfill are indicators of failure. Ditches without culverts, or with poorly placed, damaged or leaking culverts, result in oversaturation and piping within the fill which may lead to failure of the road. The potential for slope failure is assigned a rating of low, moderate or high. These ratings are based on a qualitative assessment of the impact of various factors on the factor of safety, through their ability to reduce the cohesion and friction of affected rock and soil masses. Low susceptibility areas cover approximately 10 percent of the area (810 ha). Slopes are less than 3.5 degrees. Nearly 70 percent of the study area can be classified as moderately susceptable (5670 ha). Slopes in these areas range up to the natural angle of repose. The high susceptibility category covers areas with near vertical slopes, continuous rockfall, previous failures or strong indications of potential failure. These areas cover about 20 percent of the basin ( 1620 ha) and include areas of actual failure and adjacent areas which have not failed but possess similar bedrock, cultural and groundwater characteristics.

In recent years, rapid mass movements such as debris flow and debris avalanches resulted in a significant impact on Norwegian society and economy. The need for dispelling the uncertainty inherent in landslide risk assessment has encouraged the development of hazard and susceptibility maps. Different statistically-based modelling methods, in combination with geographic information systems (GIS), have been extensively used to ascertain landslide susceptibility in quantitative terms. This thesis proposes a bivariate statistical method (Weights of Evidence) for assessing the spatial proneness of debris flows within Førde and Jølster municipalities (Western Norway), where emphasis is put on the critical conditions of initiation. Since no feasible landslide database could be exploited for susceptibility mapping at medium scale, this thesis addressed the realisation of a new inventory. By coupling pre-existing data from remote sensing and field observations, circa 1100 debris flow initiation areas were outlined and differentiated in four categories with geomorphological repeatable features. Simple topography-based parameters such as slope, upslope contributing area, curvature and roughness were used to find significant statistical differences between the initiation areatypes. Moreover, they were employed together with other thematic maps as informative layers for landslide modelling. In order to test the model fitting performance, the ROC curves method is used in this thesis. The evaluation of different discretization schemes and combinations of the above-mentioned variables led to individuate models with different performances in terms of success rates. The best model is obtained by using only a combination of slope, flow accumulation and elevation (82% true positive rate), while the manual adjustment of the classification scheme did not lead to significant improvements.

Landslide hazard and risk are growing as a consequence of climate change and demographic pressure. Land‐use planning represents a powerful tool to manage this socio‐economic problem and build sustainable and landslide resilient communities. Landslide inventory maps are a cornerstone of land‐use planning and, consequently, their quality assessment represents a burning issue. This work aimed to define the quality parameters of a landslide inventory and assess its spatial and temporal accuracy with regard to its possible applications to land‐use planning. In this sense, I proceeded according to a two‐steps approach. An overall assessment of the accuracy of data geographic positioning was performed on four case study sites located in the Italian Northern Apennines. The quantification of the overall spatial and temporal accuracy, instead, focused on the Dorgola Valley (Province of Reggio Emilia). The assessment of spatial accuracy involved a comparison between remotely sensed and field survey data, as well as an innovative fuzzylike analysis of a multi‐temporal landslide inventory map. Conversely, long‐ and short‐term landslide temporal persistence was appraised over a period of 60 years with the aid of 18 remotely sensed image sets. These results were eventually compared with the current Territorial Plan for Provincial Coordination (PTCP) of the Province of Reggio Emilia. The outcome of this work suggested that geomorphologically detected and mapped landslides are a significant approximation of a more complex reality. In order to convey to the end‐users this intrinsic uncertainty, a new form of cartographic representation is needed. In this sense, a fuzzy raster landslide map may be an option. With regard to land‐use planning, landslide inventory maps, if appropriately updated, confirmed to be essential decision‐support tools. This research, however, proved that their spatial and temporal uncertainty discourages any direct use as zoning maps, especially when zoning itself is associated to statutory or advisory regulations.

Landslide hazard and risk are growing as a consequence of climate change and demographic pressure. Land‐use planning represents a powerful tool to manage this socio‐economic problem and build sustainable and landslide resilient communities. Landslide inventory maps are a cornerstone of land‐use planning and, consequently, their quality assessment represents a burning issue. This work aimed to define the quality parameters of a landslide inventory and assess its spatial and temporal accuracy with regard to its possible applications to land‐use planning. In this sense, I proceeded according to a two‐steps approach. An overall assessment of the accuracy of data geographic positioning was performed on four case study sites located in the Italian Northern Apennines. The quantification of the overall spatial and temporal accuracy, instead, focused on the Dorgola Valley (Province of Reggio Emilia). The assessment of spatial accuracy involved a comparison between remotely sensed and field survey data, as well as an innovative fuzzylike analysis of a multi‐temporal landslide inventory map. Conversely, long‐ and short‐term landslide temporal persistence was appraised over a period of 60 years with the aid of 18 remotely sensed image sets. These results were eventually compared with the current Territorial Plan for Provincial Coordination (PTCP) of the Province of Reggio Emilia. The outcome of this work suggested that geomorphologically detected and mapped landslides are a significant approximation of a more complex reality. In order to convey to the end‐users this intrinsic uncertainty, a new form of cartographic representation is needed. In this sense, a fuzzy raster landslide map may be an option. With regard to land‐use planning, landslide inventory maps, if appropriately updated, confirmed to be essential decision‐support tools. This research, however, proved that their spatial and temporal uncertainty discourages any direct use as zoning maps, especially when zoning itself is associated to statutory or advisory regulations.

The heavy precipitation event of November 3-8, 2006 dropped over 60 cm of rain onto the bare southern slopes of Mount St. Helens and generated debris flows in eight of the sixteen drainages outside the 1980 debris avalanche zone. Debris flows occurred on the upper catchments of the Muddy River, Shoestring Glacier, Pine Creek, June Lake, Butte Camp Dome, Blue Lake, Sheep Creek, and South Fork Toutle River. Debris flows were clustered on the west and south-east sides of the mountain. Of the eight debris flows, three were initiated by landslides, while five were initiated by headward or channel erosion. Six debris flows were initiated in deposits mapped as Holocene volcaniclastic deposits, while two were in 1980 pyroclastics on andesite flows. The largest (~975,000 m2) and longest (~8,900 m) debris flow was initiated by landslides in the upper South Fork Toutle River Drainage. The average debris flow initiation zone elevation was 1,750 m, with clusters around 1,700 m and 2,000 m elevation. The lower cluster is associated with basins that host modern or historic glaciers, while the upper is possibly associated with recent pyroclastic deposits. Upper drainages with debris flows averaged 41% slopes steeper than 33 degrees, while those without debris flows averaged 34%. The upper basins with debris flows averaged 6% snow and ice cover, 21% consolidated bedrock, and 74% unconsolidated deposits. Basins without debris flows averaged 3% snow and ice cover, 27% bedrock, and 67% unconsolidated deposits. Drainages with debris flows averaged an 89% loss of glacier area between 1998 and 2009, while those without debris flows lost 68%. Further comparing glacier coverage during that period found that only five of ten glaciers still existed in 2009. On average, the glaciers had reduced in area by 67%, decreased in length by 36%, and retreated by an average of 471 m during that period. Basin attributes were measured or calculated in order to construct a predictive debris flow model based on that of Pirot (2010) using multiple logistic regression. The most significant factors were the percentage of slopes steeper than 33 degrees, unconsolidated deposits in the upper basin, and average annual rainfall. These factors predicted the 2006 debris flows with an accuracy of 94% in a debris flow susceptibility map for Mount St. Helens.

Landslide dams result from the complex interaction, not yet totally understood, between river and slope dynamics. The study of past landslide dams and their consequences has acquired a significant relevance for forecasting and preventing their induced hydraulic risk on lives and property. The main aim of this thesis was the study of the landslide dam phenomenon and design a useful and easy tools to assess the damming risk with spatial planning purpose. The research started from the geomorphologic investigation of the Italian landslide dams and setting up an archive, updating previous studies on the same topic in smaller areas (Pirocchi, 1991; Ermini, 2000; Pacino, 2002), and integrating it through a careful literature review and cartographic and aerial photos interpretation. The collected data represents the wider example of systematic inventory in Italy, with almost three hundreds of cases selected from the Alps to the Southern Apennines, in Sicily. The research includes landslide dams occurred along the Cordillera Blanca mountain range, in Peru, to study the same phenomenon in a very different geographical, climatic and tectonic settings. A morphological analysis of the collected data was performed to identify morphometric parameters that best define the formation process of a blockage. This analysis confirmed the validity of schematizations already developed by previous authors and new morphometric indexes, useful for forecasting and planning purposes, were proposed. In particular, encouraging result came from the formulation of the Morphological Obstruction Index (MOI) that allowed to perform a reliable analysis of dam formation and provided a good estimator to forecast a landslide blocking a river, from a geomorphic analysis. In order to prevent part of the damages and suffer lower consequences related to landslide dam occurrence, an useful and practical tool was proposed, to predict which areas have a higher damming susceptibility and where preventive measures should be focused. Therefore a simple GIS methodology, useful as a forecasting and planning tool, was developed. This easy methodology, used on the Arno River basin, was able to assess with few data the damming predisposition, connected to existing landslides, and the probability of obstruction, by new landslides along a river network.

by Wong, Tak-yee Tammy.
Thesis (M.Phil.)--Chinese University of Hong Kong, 1995.
Includes bibliographical references (leaves 170-178).
ABSTRACT --- p.i-iii
ACKNOWLEDGEMENTS --- p.iv-v
TABLE OF CONTENTS --- p.vi-x
LIST OF FIGURES --- p.xi-xii -
LIST OF PLATES --- p.xiii-ix
LIST OF TABLES --- p.x-xii
Chapter CHAPTER I: --- INTRODUCTION --- p.1
Chapter 1.1 --- Introduction --- p.1
Chapter 1.2 --- Research Questions --- p.5
Chapter 1.3 --- Study Significance --- p.7
Chapter 1.4 --- Organization of the Thesis --- p.8
Chapter CHAPTER II: --- LITERATURE REVIEW --- p.10
Chapter 2.1 --- Introduction --- p.10
Chapter 2.2 --- Nature of Landslides --- p.10
Chapter 2.2.1 --- Landslide Classification --- p.10
Chapter 2.2.2 --- Morphometry of Landslides --- p.12
Chapter 2.2.3 --- Factors Affecting Landslide Occurrence --- p.16
Chapter 2.2.3.1 --- Gradient --- p.19
Chapter 2.2.3.2 --- Slope Shape --- p.21
Chapter 2.2.3.3 --- Aspect --- p.22
Chapter 2.2.3.4 --- Vegetation --- p.24
Chapter 2.2.3.5 --- Drainage --- p.26
Chapter 2.2.3.6 --- Precipitation/Seismicity --- p.26
Chapter 2.2.3.7 --- Lithology and Geological Influences --- p.28
Chapter 2.2.3.8 --- Regolith --- p.29
Chapter 2.2.3.8.1 --- Hydrological Properties of Soils --- p.29
Chapter 2.2.3.8.2 --- Engineering Properties of Soils --- p.30
Chapter 2.3 --- Data Sources for Landslide Studies --- p.31
Chapter 2.3.1 --- Aerial Photo Interpretation (API) --- p.32
Chapter 2.3.2 --- Remote Sensing --- p.34
Chapter 2.3.3 --- Field Survey --- p.35
Chapter 2.3.4 --- Subsurface Investigation --- p.36
Chapter 2.4 --- Landslide Studies in Hong Kong --- p.36
Chapter 2.5 --- Applications of GIS on Landslide Studies --- p.38
Chapter 2.5.1 --- Major Data in GIS for Landslide Studies --- p.39
Chapter 2.5.1.1 --- Triangulated Irregular Network (TIN) as a Representation of Surface --- p.39
Chapter 2.5.2 --- Applications --- p.42
Chapter 2.5.2.1 --- Inventory --- p.43
Chapter 2.5.2.2 --- Landslide Hazard Assessment --- p.43
Chapter 2.5.2.2.1 --- Statistical Modeling --- p.46
Chapter 2.5.2.2.2 --- Physical Processes or Three- Dimensional Modeling --- p.50
Chapter 2.6 --- Suggestions for Future Research Directions --- p.51
Chapter CHAPTER III: --- STUDY AREA --- p.54
Chapter 3.1 --- Location and Choice of Study Area --- p.54
Chapter 3.2 --- Climatic Aspects --- p.56
Chapter 3.3 --- Geological Aspects --- p.62
Chapter 3.3.1 --- General Information of GASP V --- p.62
Chapter 3.3.2 --- Rock Types Specific to the Two Sites Chosen --- p.63
Chapter 3.3.2.1 --- Volcanic Units - Repulse Bay Formation --- p.65
Chapter 3.3.2.2 --- Sedimentary Units - Port Island Formation (PI) --- p.65
Chapter 3.4 --- Geomorphological Aspects --- p.66
Chapter 3.4.1 --- General Information of GASP V --- p.66
Chapter 3.5 --- Erosion and Stability --- p.67
Chapter 3.6 --- Vegetation --- p.67
Chapter 3.7 --- Summary --- p.70
Chapter CHAPTER IV: --- DATABASE CONSTRUCTION AND MANIPULATION --- p.71
Chapter 4.1 --- Data Collection --- p.73
Chapter 4.1.1 --- Aerial Photo Interpretation (API) --- p.73
Chapter 4.1.1.1 --- Landslip Inventory --- p.75
Chapter 4.1.2 --- Field Techniques --- p.78
Chapter 4.1.2.1 --- Slope Failure/Deposit Field Survey sheet --- p.78
Chapter 4.1.2.2 --- Collection of Landslide Data --- p.79
Chapter 4.1.3 --- Collection of Existing Data --- p.80
Chapter 4.1.3.1 --- 1:5000 Topographic Maps --- p.80
Chapter 4.1.3.2 --- Terrain Classification --- p.81
Chapter 4.1.3.3 --- WWF Vegetation Database --- p.85
Chapter 4.2 --- Data Input and Conversion --- p.86
Chapter 4.2.1 --- Digitizing of Data --- p.87
Chapter 4.2.1.1 --- Landslip Capture in Stereocord --- p.87
Chapter 4.2.1.2 --- Data Conversion --- p.94
Chapter 4.2.1.2.1 --- Topographic Maps - Scanning and Vectorization --- p.94
Chapter 4.3 --- Data Editing --- p.94
Chapter 4.3.1 --- Line Cleaning for Landslide Coverage --- p.96
Chapter 4.3.2 --- Line Cleaning and Height Tagging for Topographic Map --- p.96
Chapter 4.3.3 --- Editing on Terrain Classification Map --- p.97
Chapter 4.4 --- Database Construction --- p.97
Chapter 4.4.1 --- Data Base Design --- p.97
Chapter 4.4.1.1 --- Graphical Data Base --- p.98
Chapter 4.4.1.2 --- Attribute Data Base --- p.99
Chapter 4.4.2 --- Creation of a Triangulated Irregular Network (TIN) --- p.104
Chapter 4.5 --- Data Preparation and Pre-analysis Manipulation --- p.105
Chapter 4.5.1 --- Extraction of Terrain Variables from TIN --- p.105
Chapter 4.5.1.1 --- TIN'S Derived Variable - Elevation --- p.105
Chapter 4.5.1.2 --- TIN'S Derived Variable - Gradient --- p.107
Chapter 4.5.1.3 --- TIN'S Derived Variable - Orientation --- p.109
Chapter 4.5.1.4 --- TIN's Derived Variable - Dimensions (surface distance) of Landslides --- p.109
Chapter 4.5.1.5 --- Micro-DEM and Profile --- p.109
Chapter 4.5.1.6 --- Weighting Method Adopted in Calculating the Gradient and Orientation of Primary Depletion Scar --- p.110
Chapter 4.5.2 --- Data Preprocessing --- p.110
Chapter 4.6 --- Summary --- p.114
Chapter CHAPTER V: --- STATISTICAL ANALYSIS OF LANDSLIDE DISTRIBUTION --- p.115
Chapter 5.1 --- Sampling --- p.116
Chapter 5.1.1 --- Sampling Frame --- p.116
Chapter 5.1.1.1 --- Simple Random Point Sampling --- p.117
Chapter 5.1.1.2 --- Stratified Random Point Sampling --- p.117
Chapter 5.2 --- Comparison of the Two Study Areas --- p.119
Chapter 5.3 --- Statistical Analyses of Landslip Variables --- p.123
Chapter 5.3.1 --- Gradient (TIN) and Elevation --- p.124
Chapter 5.3.2 --- "Aspect, Geological Materials, Gradient, Terrain Component, Erosion & Instability, and Vegetation" --- p.126
Chapter 5.3.2.1 --- Aspect --- p.127
Chapter 5.3.2.2 --- Geological Materials --- p.130
Chapter 5.3.2.3 --- Gradient --- p.132
Chapter 5.3.2.4 --- Terrain Component --- p.137
Chapter 5.3.2.5 --- Erosion and Instability --- p.140
Chapter 5.3.2.6 --- WWF Vegetation --- p.140
Chapter 5.3.3 --- Result of the Partial Model --- p.145
Chapter 5.4 --- Logistic Regression Model --- p.147
Chapter 5.4.1 --- Landslide Probability Mapping --- p.154
Chapter 5.4.2 --- Testing the Model Output --- p.157
Chapter 5.5 --- Summary --- p.161
Chapter CHAPTER VI: --- CONCLUSIONS --- p.162
Chapter 6.1 --- Summary of Findings --- p.162
Chapter 6.2 --- Limitations of the Study --- p.163
Chapter 6.3 --- Recommendations for Further Studies --- p.166
BIBLOGRAPHY --- p.167
APPENDICES
"APPENDIX I Draft 3.3 slope failure/deposit field survey sheet (King, 1994a)"
"APPENDIX II Landslide/deposit field description sheet (King, 1994b)"
"APPENDIX III Hourly rainfall (mm) record at N05 in September 26-27，1993 (Source: Special Projects Division, Geotechnical Engineering Office, Civil Engineering Department)"
"APPENDIX IV Hourly rainfall (mm) record at R23 in September 1993 (Source: Hydrometeorology Section, Royal Observatory, Hong Kong,1993)"
"APPENDIX V Hourly rainfall (mm) record at R31 in September 1993 (Source: Hydrometeorology Section, Royal Observatory, Hong Kong,1993)"

The Saint Lawrence Lowlands in eastern Canada contain extensive deposits of marine soils deposited in post-glacial seas during and following the retreat of the most recent continental glacier. These marine soils include silt and clay deposits known collectively as Champlain clay. When the pore fluid in these marine deposits has changed over time to a lower salinity, the clay can become very sensitive, or demonstrate substantial strength loss after reaching the peak strength with sufficient strain under undrained load conditions. Sensitive clay soils are subject to a peculiar type of very large landslide that typically involves great extents of nearly horizontal ground, usually occurring suddenly and without warning. These landslides tend to be described as “retrogressive” in the literature and practice, implying that they develop as a series of successive small failures that advance rearward until a final stable position is reached. The work of this thesis is organized into four different themes, with an overall objective of understanding the hazard and risk associated with large landslides in sensitive clay to linear infrastructure such as railways. The first theme, documented in Chapter 2, develops a number of spatial relationships between specific physiographic and geologic features and landslide occurrence or absence, as determined through air photo analysis and a review of the literature. The second theme, documented in Chapter 3, presents the construction of a digital database of large landslides in sensitive clay in eastern Canada, for the purposes of studying landslide susceptibility, hazard and risk. The third theme, documented in Chapters 4 and 5, presents and defends a novel mechanical model for development of these large landslides. This model suggests the landslides develop progressively, rather than retrogressively, and the science of fracture mechanics is employed to substantiate the model. The fourth theme, documented in Chapters 6 and 7, synthesizes the findings of the earlier themes and presents a methodology for estimating landslide susceptibility in Champlain clay. That approach is then extended to develop an understanding of the hazard. The concluding chapter extends that work to present an initial appreciation of landslide risk to railways.
Thesis (Ph.D, Geological Sciences & Geological Engineering) -- Queen's University, 2009-04-23 13:22:19.53

Tese de doutoramento, Geografia (Geografia Física), Universidade de Lisboa, Instituto de Geografia e Ordenamento do Território, 2014
This work aims to contribute to the knowledge of large-scale slope instability phenomena in the northern Rif Mountain, whose setting is presented in the first chapter. On a second chapter we analyse the topography of the Rif belt resorting to morphometric parameters extracted from digital terrain data. Our results indicate a concentration of surface uplift and tectonically induced drainage network incision along the Internai Domain and southern sector of the Ketama Unit, defining two zones of distinct deformation that are consistent with the transpression models for northern Africa. In the chapter 3 we study the frequency-size and spatial distribution of 3610 bedrock landslides (La> 0.01km2). lhe results show that while the precipitation related to humid climatic condition throughout the Quaternary has certainly favoured the triggering of very large landslides (>1km2 ) along the south-western sector of the mountain chain, the importance of deep-seated bedrock fracturing in close proximity to active tectonic structures and high relief sites clearly outlines the role of seismic ground acceleration in producing large-scale slope instability events. lhe fourth chapter constitutes a preliminary approach to study slope instability based on PSlnSAR technique. lhe velocity and density of persistent PSs was analyzed to refine the classification of the activity status of the inventoried landslides using the PSI-based matrix approach. Furthermore, we used Hotspot and Cluster analysis (PSI-HCA) in order to detect PSs clusters associated with slow gravitational movement. lhe comparison between the results that were obtained through the PSIHCA and PSI-based matrix approach confirm the capability of both methods to detect landslide activity. lhe final chapter focuses on a detailed study of a complex deep-seated landslide. Field data collection enabled the identification of paleoseismic activity in landslide triggering. Furthermore, according to Holocene climatic reconstructions, the age constrains for the landslide reactivations are placed during one of the driest and hottest phases of the Holocene, which suggests that slope deformation is decoupled from the Holocene climatic trends.
Fundação para a Ciência e a Tecnologia (FCT)

碩士
國立成功大學
環境工程學系碩博士班
100
The high mountains, steep slope, broken terrain and frequent earthquakes, together with the heavy rainfall during the rainy and typhoon seasons, cause more and more geohazards of landslides and debris, as well as a considerable loss of lives and properties in mountainous areas of Taiwan. To enhance the capability of disaster response and mitigation, remotely sensed imagery and geospatial information have been collected national-wide in the past two decades using a variety of multi-stage platforms and sensors. Among those spatial-information collected, the archive of Formosat-2 imagery provides high temporal-spatial resolution surface data of Taiwan during the past 7.5 years, and promising to be a key data for analyzing disaster-causing factors and establishing landslide hazard prediction models. Three study areas within the Gaoping River Basin were chosen in this work. By integrating various GIS data and spatial analysis approaches, a Landslide Susceptibility Index (LSI) evaluation method was developed base on the slope value, geological data and drainage orders. The pre- and post- event images of Typhoon Haitang (2005), Typhoon Sepat (2007), Typhoon Krosa (2007), Typhoon Kalmaegi (2007), Typhoon Fanapi (2010) and Nanmadol typhoon were obtained from the archive of Formosat-2 and processed to 2m resolution orthorectified images for landslide interpretation by the application of Formosat-2 Automatic Imager Processing System (F-2 AIPS). A new system combine expert and statistics that integrates all useful spatial information to assist the interpreters to determine the landslide areas quickly and accurately was employed to inventory the landslide data from the orthorectified images. The result indicates that the newly developed landslides account for 0.2~0.8% of the study areas while the landslide caused by Typhoon Haitang reaches the highest proportion (0.74%) among the six events. The LSI maps are built for three study areas and found to have good agreement with the landslide inventory results. Additionally, three regression model that determines the rainfall-duration threshold for triggering landslide was developed by analyzing the relationships between the event precipitation, LSI and the landslide inventory result, and hence was employed to build three regression models estimating the rainfall-duration threshold for different for different levels of LSI. Both of the cross-event and cross-region. This study encourages the use of our LSI evaluation method and the rainfall-duration threshold to generate a landslide hazard map for future slope disaster preventions.