Landslide Science and Practice

India is now housing 17% of the world’s population. Landslides are an increasing concern in India due to the rapid population expansion in hilly and mountainous terrain. Landslides affect vast areas within India, in particular in the Himalayan chain in the North and Eastern part of the country and the Western Ghats in the Southwest. The Geological Survey of India (GSI) has been designated as agency responsible for landslide inventory, susceptibility and hazard assessment. Until recently their landslide susceptibility assessment was based on a heuristic approach using fixed weights or ranking of geofactors, following guidelines of the Bureau of Indian Standards (BIS). However, this method is disputed as it doesn’t provide accurate results.

This paper gives an overview of recent research on how the existing methods for landslide inventory, susceptibility and hazard assessment in India could be improved, and how these could be used in (semi)quantitative risk assessment. Due to the unavailability of airphotos in large parts of India, satellite remote sensing data has become the standard data input for landslide inventory mapping. The National Remote Sensing Center (NRSC) has developed an approach using semi-automatic image analysis algorithms that combine spectral, shape, texture, morphometric and contextual information derived from high resolution satellite data and DTMs for the preparation of new as well as historical landslide inventories. Also the use of existing information in the form of maintenance records, and other information to generate event-based landslide inventories is presented. Event-based landslide inventories are used to estimate the temporal probability, landslide density and landslide size distribution.

Landslide susceptibility methods can be subdivided in heuristic, statistical and deterministic methods. Examples are given on the use of these methods for different scales of analysis. For medium scales a method is presented to analyze the spatial association between landslides and causal factors, including those related to structural geology, to select the most appropriate spatial factors for different landslide types, and integrate them using a combination of heuristic and multivariate methods. For transportation corridors a method is presented for quantitative hazard and risk assessment based on a nearly complete landslide database. Deterministic methods using several dynamic slope-hydrology and slope stability models have been applied to evaluate the relation between landuse changes and slope stability.

The susceptibility maps can be combined with the landslide databases to convert them into hazard maps which are subsequently used in (semi) quantitative risk assessment at different scales of analysis.

Through combining new technologies and traditional mapping techniques, the British Geological Survey (BGS) has developed a novel, multi-stage methodology for landslide mapping. 3-D aerial photograph interpretation, variable-perspective 3-D topographic visualisation and field mapping with digital data capture are being used to map the UK’s landslides. The resulting ESRI ArcGIS polygons are published on BGS 1:50,000 geological maps and as digital data products. Data collected during mapping are also uploaded directly into the National Landslides Database maintaining a systematic, nationally-uniform landslide inventory. Repeat monitoring of selected landslides using terrestrial LIDAR and dGPS allows the database to be frequently updated and the proactive Landslide Response Team means that new landslide events can be mapped within days, if not hours, of their occurrence. The long-term aim is to apply this methodology throughout the UK, providing a wealth of data for scientific research and hazard assessment. This methodology is also suitable for application in an international context.

Historically, large rock slope failures impacting into a fjord and causing a several tens of metre high displacement wave have been one of the natural hazards in Norway claiming most lives. In the last 7 years, the Geological Survey of Norway has implemented a systematic mapping approach to characterize unstable rock slopes prone to catastrophic failures, so that future events can be recognized beforehand and society can adapt to the hazard. Systematic mapping has been carried out in three countries and more than 285 unstable slopes have been found. Of these sites, 62 are monitored periodically and 4 have been characterized as high risk objects with continuous monitoring systems installed. In order to classify the likelihood of a future event, rock slope mapping of each object includes the analyses of slide kinematic, velocity of the slide accompanied with other indicators of slide activity and an analysis of recurrence of previous events along the slope.

Landslide inventories, usually including digital inventory maps and linked alphanumeric attributes, are the most important input for further landslide zoning. However, to allow landslide susceptibility, hazard and risk assessment the inventory databases should contain information on the location of landslide phenomena, types, history, state of activity, magnitude or size, causal factors and the damage caused. Yet, in Europe it is not known which national (or regional) landslide databases contain all this information, and thus allow landslide risk assessment. Therefore this study presents a review of existing national landslide databases in Europe together with a number of regional databases, and proposes improvements in agreement with the EU Soil Thematic Strategy, and with INSPIRE Directive.

Replies received to a detailed questionnaire learned that currently 22 out of 37 contacted European countries have a national landslide database. Six other countries only have regional databases. In total the databases contain so far more than 642,000 landslides. About half of the databases contain less than 50% of all landslides in the country and also information on landslide history, triggering factor and consequences is generally only available for less than 25% of the landslides in the databases. A positive observation is that 60% of the databases are updated at least once a year or after a major event. The spatial data are almost always collected with traditional methods such as field surveys, and analysis of aerial photographs and historical records. 67% of the databases use a classification system adapted from Cruden and Varnes (Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Turner AK, Schuster RL (eds) Landslides, investigation and mitigation, Special Report 247: Transportation Research Board. National Research Council, National Academy Press, Washington, DC, pp 36–71), so it should be possible to define a limited number of major landslide types and activity classes to be used in all databases. Other problems with regard to interoperability and harmonisation are due to differences in language, the absence of a digital database where spatial and alphanumeric information is linked (the case for 58% of the databases), and the restricted accessibility.

The landslide inventory is an essential tool for working with landslides and related preventive and remedial measures in practice, and for the development of landslide susceptibility, hazard or risk maps. In Lower Austria, the regional Geological Survey has been developing its landslide inventory since 1953. In 2000 a digital version replaced the paper archive. For every geological or geotechnical report issued by the Survey the inventory is consulted. In 2007–2008 a pilot project was set up to produce the first landslide susceptibility maps. Three contracted organizations presented their proposals for the map design, using a heuristic approach, on the example of 12 selected municipalities. The results and the advantages as well as drawbacks of the method are discussed.

Damages related to landslides triggered by extreme rainfall in southern Poland in 1997 pointed to a vital need for an improved system of data acquisition, natural hazard awareness building and developing mitigation measures. After several years of struggle and compelled changes in legislative acts, a national landslide inventory project was launched in 2008. This project, known as the Landslide Counteracting System (SOPO in Polish) is meant to provide support in the field of environmental protection and public safety as well as mass movement mitigation. The end-users of the project are administrative bodies, environmental protection inspectorates as well as non-governmental organizations acting in the area of constructing works, transportation, estate and property trade and education-research activities. The first stages of the project implementation involved pilot surveying and database testing and were followed by a systematic landslide inventory, starting from the most threatened municipalities in the Polish flysch Carpathians. Over 12,000 landslide bodies have been already recorded in the Polish Carpathians. The updated landslide prone areas in examined municipalities are unquestionable advantages of the project but this outcome was not appreciated by local communities, property owners or policy makers.

The paper shows the results of geomorphological and engineering-geological investigations carried out along the north-western coast of the Island of Malta, with special emphasis on landslides. Field surveys and aerial-photo interpretation allowed the recognition, identification and mapping of a series of landslides of different type and size, some of which showing evidence of activity. Coastal instability in the studied area is deeply controlled by structural factors, such as tectonic and stratigraphic ones. The research envisaged a multidisciplinary approach, which also included landslide monitoring in specific sites which were selected for detailed investigations, owing to the peculiarity of the instability processes occurring and for the related hazard and risk conditions. The paper outlines the research phases and the results achieved which proved to be fruitful thanks to the application of different methodologies for the study of coastal landslides. Particular attention has been paid to rock spreading phenomena, which are widespread along the north-western coast of Malta due to the superimposition of limestones over clayey terrains.

Slope deformations represent the most dangerous exogenous geodynamic phenomenon in the Slovak Western Carpathians. Over about five decades of systematic inventory of slope deformations almost 22,000 slope deformations covering an area of 2,575,912km

2

were registered; they pose either damage or threat for 5.25% of the area of the Slovak Republic. In the year 2010 we evidenced numerous new or reactivated landslides throughout Slovakia, generated by excessive precipitation in the late spring. This situation led to a number of emergency situations in the municipalities and the geologists from the State Geological Institute of Dionýz Štúr (SGIDŠ) carried out inventory and assessment of extent and magnitude of evolved slope deformations. For the first time in the history of systematic inventory of geological phenomena in Slovakia we made use of very precise, “scaleless” levelling of the slope deformations in the territory morphology based on GNSS technology.

Landslides represent a major threat to human life, property, buildings, infrastructure and natural environments in most mountainous and hilly regions of the world. The purpose of this work is to present the results of the analysis carried out by ISPRA on main landslide events and available databases in Europe. The major landslide phenomena occurred in Europe have been collected from the analysis of global disaster databases. For the period 2003–2010, 112 major landslides were recorded. These events, which often occurred at multiple sites for the same triggering factor, claimed a total of 152 fatalities and damaged or destroyed several buildings and transportation infrastructure.

Measurements of ground deformation with millimetric accuracy and the reconstruction of the history of deformations in the last 20 years with Persistent Scatterer techniques have a high potential for landslides studies. In this work we analyze pro and cons of PSI techniques to update the Italian Inventory of Landslides (IFFI) using data from ERS 1/2 (1992–2001) and RADARSAT (2003–2010) satellites. The study area is located in North-Western Italy and belongs to three regions: Piemonte, Lombardia and Liguria.

An important part of landslide research is the interpretation and delineation of landslides, which has increasingly been based on high-resolution satellite images in recent years. Using pre- and post-event FORMOSAT-2 satellite images as the data sources, this study presents a new method that combines four change detection techniques for mapping shallow landslides triggered by typhoons in Taiwan. The four techniques are normalized differential vegetation index (NDVI), spectral angle, principal component analysis, and independent component analysis. We applied the Multiple Change Detection (MCD) technique to map landslides triggered by typhoons. Comparisons were then made between MCD results with landslide inventory maps compiled by using a single index (NDVI). Comparison results show that MCD can perform better than a single index in dealing with old landslides and landslides with non-homogeneous spectral responses. MCD is also able to detect small landslides, which are often missed by visual analysis. Additionally, landslide maps prepared by MCD include runout features of sediment deposits from debris flows. A relatively fast processing chain, MCD is expected to become a useful new tool for emergency management after a typhoon event, which occurs on average four to five times a year in Taiwan.

Landslide inventory maps are essential for geomorphological studies, and to evaluate landslide hazard, vulnerability, and risk. Landslide maps, including geomorphological, event, seasonal, and multi-temporal inventory maps, are prepared using different techniques. We present the results of an experiment aimed a testing the possibility of using very high resolution, stereoscopic satellite images to map rainfall induced shallow landslides. Three landslide inventory maps were prepared for the Collazzone study area, Umbria, Italy. Two of the maps were prepared through the visual interpretation of stereoscopic satellite images and cover the periods January to March 2010, and March to May 2010. The third inventory map shows landslides occurred in the period January to May 2010, and was obtained through reconnaissance field surveys. We describe the statistics of landslide area for the three inventories, and compare quantitatively two of the landslide maps.

Light Detection and Ranging (LiDAR) and its wide range of derivative products have become a powerful tool in landslide research, particularly for landslide identification and landslide inventory mapping. In contrast to the many studies that use expert-based analysis of LiDAR derivatives to identify landslides, only few studies, all pixel-based, have attempted to develop computer-aided methods for extracting landslides from LiDAR. So far, it has not been tested whether object-oriented analysis (OOA) could be an alternative. Therefore, this study focuses on the application of OOA using LiDAR derivatives such as slope gradient, curvature, and difference in elevation (2m resolution). More specifically, the focus is on the possible use for segmentation and classification of slow-moving landslides in densely vegetated areas, where spectral data do not allow accurate landslide inventory mapping. The test areas are the Flemish Ardennes (Belgium) and Vorarlberg (Austria). In a first phase, a relatively qualitative procedure based on expert-knowledge and basic statistical analysis was developed for a test area in the Flemish Ardennes. The procedure was then applied without further modification to a validation area in the same region. The results obtained show that OOA using LiDAR derivatives allows recognition and characterization of profound morphologic properties of deep-seated landslides, because approximately 70% of the landslides of an expert-based inventory were also included in the object-oriented inventory. For mountain areas with bed rock outcrops like Vorarlberg, on the other hand, it is more difficult to create a transferable model.

There is a strong possibility that environmental change (whether climate or land use) will be manifest as changes in the size-frequency distribution of landslides in Maily-Say Valley, Kyrgyzstan. The evolution of the landslide activity over the past 50 years has been analysed on the basis of five landslide inventories of 1962, 1984, 1996, 2002 and 2007. Their size-frequency analyses show that both the number and size of unstable slopes are increasing from 1962 (162 objects) to 2007 (208 objects) and the power-law exponent is decreasing over time. This might indicate that there is an evolution in size probably corresponding to an increase of landslide-related hazards. Remote sensing and spatial analysis through the image subtraction method based on NDVI allowed an accurate detection of new sliding activation in that area. Another aim is to evaluate if and how Data Mining, with its wide range of tools, may support automatic landslide recognition.

Landslide inventory maps can benefit from the contribution of remote sensing technologies. We exploit PSI (Persistent Scatterer Interferometry) data extracted from ERS1/2 and RADARSAT-1 satellite images acquired in the intervals 1992–2001 and 2003–2010 respectively, for the detection and mapping of landslide ground displacements at regional scale. We propose a PSI-based procedure, based on the exploitation of activity matrices and intensity scales, combining the information coming from available pre-existing inventories and PSI average velocities. We apply this approach on the test area of Northern Calabria (Southern Italy), extended 4,410km

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and extensively affected by landslide hazard, finally updating and improving the landslide inventory of this area and assessing the spatial distribution, state of activity and intensity of 1,196 landslides, corresponding to 4.3% of the whole investigated territory.

The Aosta Valley (NW-Italy) is an alpine region where debris flows frequently occur, interacting with human activities and structures. For a best debris flow hazard assessment, research and mapping activities have been organized. First, aerial photo-interpretation and DEMs analyses were performed at a regional scale to inventory alluvial fans. Second, data on debris flow events have been collected from different sources, such as bibliographic and historical data, municipality hazard maps and drainage basin technical studies. For each event photo-interpretation and geomorphologic analyses have been performed to validate historical data and finally GIS statistical analysis have been carried out. The analysis led to the identification of about 200 single events, thus successfully upgrading a regional database on natural instabilities. Collected data allowed improvements to local knowledge on debris flows, through the recognition of multiple events in the same alluvial fan. Estimation of temporal occurrences led to more precise hazard assessment, useful for proper land planning.

Arpa Piemonte is in charge of the maintenance of the framework about the hydrogeological instability of the Piemonte region. One of the main goal of working package B2 of the ALCOTRA European Project RISKNAT is focused to improve the knowledge of the SIFRAP (the landslide inventory of Piedmont region), in particular on the more serious phenomena where detailed examination is needed. The update is mainly carried out by the integration of different kind of data in order to obtain an effective knowledge of phenomena: detailed morphological analysis, carried out mainly by air-photo interpretation and some aimed field survey, are coupled with the outcome of the monitoring system of Arpa Piemonte. Thanks to the found of RISKNAT project also space borne radars data are available: in 2010, we covered an Alpine area of about 13,000km

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using data sets from Canadian RADARSAT satellite, covering the time span from 2002 to 2009. The survey was made using a newly patented processing algorithm (the SqueeSAR™) and identified more than 2 millions PS. Also a previous in coverage was made over the entire region (~25,000km

2

) using data sets from ERS-1 and ERS-2 radar satellites, covering the time span from 1992 to 2001. The main activity is now pointed out to analyse and integrate together all these different data in order to obtain meaningful landslides interpretations and an efficient way to make available all data to citizen and regional authorities.

This paper provides an overview of the on-going research project from the Institute of Geography at the National Autonomous University of Mexico (UNAM) that seeks to conduct multi-temporal landslide inventories and produce landslide susceptibility maps by using Geographic Information Systems (GIS). The Río Chiquito-Barranca del Muerto watershed on the southwestern flank of Pico de Orizaba volcano in Mexico is selected as a case–control study area. First, the project aims to derive a landslide inventory map from a representative sample of landslides using aerial photography and field work. Next, Multiple Logistic Regression (MLR) is used to examine the relation between landsliding and several independent variables (elevation, slope, contributing area, land use, geology, and terrain curvature) to create the susceptibility map. Finally, the model is compared with the reality expressed by the inventory map. In this study, the results of the landslide inventory and susceptibility mapping techniques are presented and discussed.

Multi-temporal analysis of space-borne radar images through Persistent Scatterer Interferometry (PSI) is exploited for detecting and mapping slope instability at basin scale in the south-western part of the province of Messina, hit by the intense storm events on October 1st 2009. Available PSI data provide estimates of yearly deformation velocity, referred to both historical (1992–2001; ERS images) and recent (2003–2009; ENVISAT images) scenarios. PSI techniques have recently demonstrated their suitability for the analysis of extremely to very slow moving landslides, and their complementarity with field campaigns, at both regional and local scales, allowing spatial and temporal characterization of the detected phenomena. Coupling and integrating deformation measurements extracted by means of SqueeSAR technique, thematic maps and optical data enabled to identify 26 sites (

hotspot mapping

), characterized by high hydro-geological hazard related to the occurrence of pre-event, extremely to very slow moving landslides.

Preliminary results of landslide mapping in the City of Zagreb (Croatia), obtained in the frame of the Japanese-Croatian scientific project, are presented in this paper. The aim of this research is to develop a method for landslide delineation in order to enable land use officials to implement this data to create more useful measures for landslide risk management. Selected landslides in the hilly zone of Mt. Medvednica were identified visually using LiDAR bare-earth DEMs. The results of data analysis will be implemented to perform a more comprehensive study of landslides in the entire pilot area (total area is 180km

2

).

Studies related to natural hazards have become an extremely important issue among the geoscientists for the last few decades. Particularly after the mid 1980s, developments in computer technology, GIS (Geographic Information Systems), and RS (Remote Sensing) have provided rapid and detailed analysis of different natural hazards such as landslides, earthquakes, floods, and so on, in larger areas. Combined with field observations, these analyses may provide important knowledge in assessing natural hazards. Landslides are one of the most destructive parts in natural hazards. Similar to many countries in the world, Turkey, a landslide suffering country, faces this problem. In Turkey, landslides are of great importance among the natural hazards, and the Western Black Sea region is one of the major landslide prone areas. For this reason, in this study, we selected an area in the Western Black Sea region, in order to investigate the usage of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite imagery in preparing landslide inventory maps. For this purpose, two- and-three dimensional visual image interpretation was performed at different scales varying from 1:15,000 to 1:50,000. Particularly VNIR (Visible Near Infrared) bands of the ASTER images were used in the analyses. Field studies were also carried out in the study area to map landslides and to compare different landslide inventories. Based on the analyses, it was revealed that the best method to prepare landslide inventory maps by visual interpretation was found as stereoscopic (three dimensional) image analysis at 1:15,000 scale. ASTER Level 3A data were used to create stereo images, RGB (433) in other words ASTER 3N (Nadir) and 3B (Backward) bands can be used to produce stereo images. The smallest mapped landslide was determined as 58,885m

2

, covering approximately 262 pixels. As a result of the assessments, it is considered that ASTER satellite imagery can successfully be used in regional and medium scale landslide inventory studies.

Studies related to natural hazards have become an extremely important issue among the geoscientists for the last few decades. Particularly after the mid 1980s, developments in computer technology, GIS (Geographic Information Systems), and RS (Remote Sensing) have provided rapid and detailed analysis of different natural hazards such as landslides, earthquakes, floods, and so on, in larger areas. Combined with field observations, these analyses may provide important knowledge in assessing natural hazards. Landslides are one of the most destructive parts in natural hazards. Similar to many countries in the world, Turkey, a landslide suffering country, faces this problem. In Turkey, landslides are of great importance among the natural hazards, and the Western Black Sea region is one of the major landslide prone areas. For this reason, in this study, we selected an area in the Western Black Sea region, in order to investigate the usage of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite imagery in preparing landslide inventory maps. For this purpose, two- and-three dimensional visual image interpretation was performed at different scales varying from 1:15,000 to 1:50,000. Particularly VNIR (Visible Near Infrared) bands of the ASTER images were used in the analyses. Field studies were also carried out in the study area to map landslides and to compare different landslide inventories. Based on the analyses, it was revealed that the best method to prepare landslide inventory maps by visual interpretation was found as stereoscopic (three dimensional) image analysis at 1:15,000 scale. ASTER Level 3A data were used to create stereo images, RGB (433) in other words ASTER 3N (Nadir) and 3B (Backward) bands can be used to produce stereo images. The smallest mapped landslide was determined as 58,885m

2

, covering approximately 262 pixels. As a result of the assessments, it is considered that ASTER satellite imagery can successfully be used in regional and medium scale landslide inventory studies.

Studies related to natural hazards have become an extremely important issue among the geoscientists for the last few decades. Particularly after the mid 1980s, developments in computer technology, GIS (Geographic Information Systems), and RS (Remote Sensing) have provided rapid and detailed analysis of different natural hazards such as landslides, earthquakes, floods, and so on, in larger areas. Combined with field observations, these analyses may provide important knowledge in assessing natural hazards. Landslides are one of the most destructive parts in natural hazards. Similar to many countries in the world, Turkey, a landslide suffering country, faces this problem. In Turkey, landslides are of great importance among the natural hazards, and the Western Black Sea region is one of the major landslide prone areas. For this reason, in this study, we selected an area in the Western Black Sea region, in order to investigate the usage of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite imagery in preparing landslide inventory maps. For this purpose, two- and-three dimensional visual image interpretation was performed at different scales varying from 1:15,000 to 1:50,000. Particularly VNIR (Visible Near Infrared) bands of the ASTER images were used in the analyses. Field studies were also carried out in the study area to map landslides and to compare different landslide inventories. Based on the analyses, it was revealed that the best method to prepare landslide inventory maps by visual interpretation was found as stereoscopic (three dimensional) image analysis at 1:15,000 scale. ASTER Level 3A data were used to create stereo images, RGB (433) in other words ASTER 3N (Nadir) and 3B (Backward) bands can be used to produce stereo images. The smallest mapped landslide was determined as 58,885m

2

, covering approximately 262 pixels. As a result of the assessments, it is considered that ASTER satellite imagery can successfully be used in regional and medium scale landslide inventory studies.

Studies related to natural hazards have become an extremely important issue among the geoscientists for the last few decades. Particularly after the mid 1980s, developments in computer technology, GIS (Geographic Information Systems), and RS (Remote Sensing) have provided rapid and detailed analysis of different natural hazards such as landslides, earthquakes, floods, and so on, in larger areas. Combined with field observations, these analyses may provide important knowledge in assessing natural hazards. Landslides are one of the most destructive parts in natural hazards. Similar to many countries in the world, Turkey, a landslide suffering country, faces this problem. In Turkey, landslides are of great importance among the natural hazards, and the Western Black Sea region is one of the major landslide prone areas. For this reason, in this study, we selected an area in the Western Black Sea region, in order to investigate the usage of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite imagery in preparing landslide inventory maps. For this purpose, two- and-three dimensional visual image interpretation was performed at different scales varying from 1:15,000 to 1:50,000. Particularly VNIR (Visible Near Infrared) bands of the ASTER images were used in the analyses. Field studies were also carried out in the study area to map landslides and to compare different landslide inventories. Based on the analyses, it was revealed that the best method to prepare landslide inventory maps by visual interpretation was found as stereoscopic (three dimensional) image analysis at 1:15,000 scale. ASTER Level 3A data were used to create stereo images, RGB (433) in other words ASTER 3N (Nadir) and 3B (Backward) bands can be used to produce stereo images. The smallest mapped landslide was determined as 58,885m

2

, covering approximately 262 pixels. As a result of the assessments, it is considered that ASTER satellite imagery can successfully be used in regional and medium scale landslide inventory studies.

Studies related to natural hazards have become an extremely important issue among the geoscientists for the last few decades. Particularly after the mid 1980s, developments in computer technology, GIS (Geographic Information Systems), and RS (Remote Sensing) have provided rapid and detailed analysis of different natural hazards such as landslides, earthquakes, floods, and so on, in larger areas. Combined with field observations, these analyses may provide important knowledge in assessing natural hazards. Landslides are one of the most destructive parts in natural hazards. Similar to many countries in the world, Turkey, a landslide suffering country, faces this problem. In Turkey, landslides are of great importance among the natural hazards, and the Western Black Sea region is one of the major landslide prone areas. For this reason, in this study, we selected an area in the Western Black Sea region, in order to investigate the usage of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite imagery in preparing landslide inventory maps. For this purpose, two- and-three dimensional visual image interpretation was performed at different scales varying from 1:15,000 to 1:50,000. Particularly VNIR (Visible Near Infrared) bands of the ASTER images were used in the analyses. Field studies were also carried out in the study area to map landslides and to compare different landslide inventories. Based on the analyses, it was revealed that the best method to prepare landslide inventory maps by visual interpretation was found as stereoscopic (three dimensional) image analysis at 1:15,000 scale. ASTER Level 3A data were used to create stereo images, RGB (433) in other words ASTER 3N (Nadir) and 3B (Backward) bands can be used to produce stereo images. The smallest mapped landslide was determined as 58,885m

2

, covering approximately 262 pixels. As a result of the assessments, it is considered that ASTER satellite imagery can successfully be used in regional and medium scale landslide inventory studies.

Studies related to natural hazards have become an extremely important issue among the geoscientists for the last few decades. Particularly after the mid 1980s, developments in computer technology, GIS (Geographic Information Systems), and RS (Remote Sensing) have provided rapid and detailed analysis of different natural hazards such as landslides, earthquakes, floods, and so on, in larger areas. Combined with field observations, these analyses may provide important knowledge in assessing natural hazards. Landslides are one of the most destructive parts in natural hazards. Similar to many countries in the world, Turkey, a landslide suffering country, faces this problem. In Turkey, landslides are of great importance among the natural hazards, and the Western Black Sea region is one of the major landslide prone areas. For this reason, in this study, we selected an area in the Western Black Sea region, in order to investigate the usage of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite imagery in preparing landslide inventory maps. For this purpose, two- and-three dimensional visual image interpretation was performed at different scales varying from 1:15,000 to 1:50,000. Particularly VNIR (Visible Near Infrared) bands of the ASTER images were used in the analyses. Field studies were also carried out in the study area to map landslides and to compare different landslide inventories. Based on the analyses, it was revealed that the best method to prepare landslide inventory maps by visual interpretation was found as stereoscopic (three dimensional) image analysis at 1:15,000 scale. ASTER Level 3A data were used to create stereo images, RGB (433) in other words ASTER 3N (Nadir) and 3B (Backward) bands can be used to produce stereo images. The smallest mapped landslide was determined as 58,885m

2

, covering approximately 262 pixels. As a result of the assessments, it is considered that ASTER satellite imagery can successfully be used in regional and medium scale landslide inventory studies.

Studies related to natural hazards have become an extremely important issue among the geoscientists for the last few decades. Particularly after the mid 1980s, developments in computer technology, GIS (Geographic Information Systems), and RS (Remote Sensing) have provided rapid and detailed analysis of different natural hazards such as landslides, earthquakes, floods, and so on, in larger areas. Combined with field observations, these analyses may provide important knowledge in assessing natural hazards. Landslides are one of the most destructive parts in natural hazards. Similar to many countries in the world, Turkey, a landslide suffering country, faces this problem. In Turkey, landslides are of great importance among the natural hazards, and the Western Black Sea region is one of the major landslide prone areas. For this reason, in this study, we selected an area in the Western Black Sea region, in order to investigate the usage of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite imagery in preparing landslide inventory maps. For this purpose, two- and-three dimensional visual image interpretation was performed at different scales varying from 1:15,000 to 1:50,000. Particularly VNIR (Visible Near Infrared) bands of the ASTER images were used in the analyses. Field studies were also carried out in the study area to map landslides and to compare different landslide inventories. Based on the analyses, it was revealed that the best method to prepare landslide inventory maps by visual interpretation was found as stereoscopic (three dimensional) image analysis at 1:15,000 scale. ASTER Level 3A data were used to create stereo images, RGB (433) in other words ASTER 3N (Nadir) and 3B (Backward) bands can be used to produce stereo images. The smallest mapped landslide was determined as 58,885m

2

, covering approximately 262 pixels. As a result of the assessments, it is considered that ASTER satellite imagery can successfully be used in regional and medium scale landslide inventory studies.

Studies related to natural hazards have become an extremely important issue among the geoscientists for the last few decades. Particularly after the mid 1980s, developments in computer technology, GIS (Geographic Information Systems), and RS (Remote Sensing) have provided rapid and detailed analysis of different natural hazards such as landslides, earthquakes, floods, and so on, in larger areas. Combined with field observations, these analyses may provide important knowledge in assessing natural hazards. Landslides are one of the most destructive parts in natural hazards. Similar to many countries in the world, Turkey, a landslide suffering country, faces this problem. In Turkey, landslides are of great importance among the natural hazards, and the Western Black Sea region is one of the major landslide prone areas. For this reason, in this study, we selected an area in the Western Black Sea region, in order to investigate the usage of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite imagery in preparing landslide inventory maps. For this purpose, two- and-three dimensional visual image interpretation was performed at different scales varying from 1:15,000 to 1:50,000. Particularly VNIR (Visible Near Infrared) bands of the ASTER images were used in the analyses. Field studies were also carried out in the study area to map landslides and to compare different landslide inventories. Based on the analyses, it was revealed that the best method to prepare landslide inventory maps by visual interpretation was found as stereoscopic (three dimensional) image analysis at 1:15,000 scale. ASTER Level 3A data were used to create stereo images, RGB (433) in other words ASTER 3N (Nadir) and 3B (Backward) bands can be used to produce stereo images. The smallest mapped landslide was determined as 58,885m

2

, covering approximately 262 pixels. As a result of the assessments, it is considered that ASTER satellite imagery can successfully be used in regional and medium scale landslide inventory studies.

Studies related to natural hazards have become an extremely important issue among the geoscientists for the last few decades. Particularly after the mid 1980s, developments in computer technology, GIS (Geographic Information Systems), and RS (Remote Sensing) have provided rapid and detailed analysis of different natural hazards such as landslides, earthquakes, floods, and so on, in larger areas. Combined with field observations, these analyses may provide important knowledge in assessing natural hazards. Landslides are one of the most destructive parts in natural hazards. Similar to many countries in the world, Turkey, a landslide suffering country, faces this problem. In Turkey, landslides are of great importance among the natural hazards, and the Western Black Sea region is one of the major landslide prone areas. For this reason, in this study, we selected an area in the Western Black Sea region, in order to investigate the usage of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite imagery in preparing landslide inventory maps. For this purpose, two- and-three dimensional visual image interpretation was performed at different scales varying from 1:15,000 to 1:50,000. Particularly VNIR (Visible Near Infrared) bands of the ASTER images were used in the analyses. Field studies were also carried out in the study area to map landslides and to compare different landslide inventories. Based on the analyses, it was revealed that the best method to prepare landslide inventory maps by visual interpretation was found as stereoscopic (three dimensional) image analysis at 1:15,000 scale. ASTER Level 3A data were used to create stereo images, RGB (433) in other words ASTER 3N (Nadir) and 3B (Backward) bands can be used to produce stereo images. The smallest mapped landslide was determined as 58,885m

2

, covering approximately 262 pixels. As a result of the assessments, it is considered that ASTER satellite imagery can successfully be used in regional and medium scale landslide inventory studies.

A large landslide formed at Maierato (Vibo Valencia, Southern Italy) on February 15, 2010, when rapid failure occurred after several days of preliminary movements. The present paper covers: (1) identification of the landslide mechanism and triggering factors, (2) slope stability back-analysis using a finite-element-based shear strength reduction method, and (3) mapping of the landslide susceptibility on the basis of the main geological and hydrogeological controlling factors. The aim of the paper is to explain the mechanism of occurrence of the February 2010 landslide, in order to assess the landslide susceptibility in the whole urban area of Maierato, and then to propose risk mitigation actions.

The multidisciplinary approach (geological and geomorphological studies, structural analysis, geoelectrical and seismic surveys, borehole data) utilized in this research allowed the definition of a reliable geological model of the Torrio landslide, one of the largest mass movements of the whole Northern Apennines occurring in the Aveto valley (Emilia-Romagna Region) and that determined the inclusion of the Torrio old villages in the “List of inhabited centres to be transferred”. The results indicate that the Torrio mega-landslide is actually composed by three superposed main landslide bodies characterized by different genetic mechanisms, timing of emplacement and state of activity, but all showing deep sliding surfaces (from 30–40 m up to 250 m). This study represents a considerable improvement for the objective of achieving the landslide risk assessment mapping of the territory surrounding the Torrio inhabited centre, according to the Emilia-Romagna Region legislation.

The granitic deposit of the upper Val Ferret was shown in 1980 to result from a large September 1717 rock avalanche. A huge volume of rock and ice travelled onto the Triolet Glacier>7 km downvalley. Boulder accumulations and irregular ridges spread out over a distance of 2 km on the valley floor terminate with an arcuate front. A 2009 reconstruction with radiocarbon dating proposed a smaller lateral extension of the landslide on the valley floor preserving Lateglacial moraines, but cosmogenic exposure dating questions it. Consistency of

10

Be dates suggests that the deposit results from the 1717 rock avalanche, with a rock volume>10×10

6

m

3

, and a likely similar ice volume. The importance of rock avalanches has to be emphasised to help to prevent risk in inhabitated valleys. Even for the recent period, the contribution of cosmogenic exposure dating to geomorphological analysis of complex landform assemblages is valuable.

This paper provides geomorphological and geotechnical observations on the amplification of the destructive behaviour of rock falls on rocky slopes in the Anaga massif (Tenerife Island, Spain) covered with soils rich in organic matter, within a high rainfall regime. The soil organic matter would be the determinant factor of this process, because it would reduce the soil strength as a result of overcoming the liquid limit during heavy rains. Thus the soil could develop a semi-fluid consistency, triggering a more efficient sliding of the blocks of rock along the slope and, hence, amplifying the destructive effect of the rock falls. Other potential determinant factor would be that the soil fine fraction could undergo a sudden change in its microfabric related to the dynamic load caused by the rock fall, similar to the mechanism described to explain the landslides developed in clayey soils.

This project is reliant upon the use of remote sensing for the detection and delineation of landslides. Therefore optical satellite images, such as medium resolution ASTER, and high resolution SPOT 5, will be combined with topographic data to analyse the landslide prone areas. The specific objectives are to generate a landslide inventory distinguishing between different landslide types, and to use this map for GIS based spatial landslide hazard modelling in the Toktogul region of Kyrgyzstan. The project steps include: (1) detection and mapping of landslides at different scales using high resolution imagery and DEM data to generate a GIS landslide inventory database for the area, (2) ground truthing of this landslide inventory using field reconnaissance, (3) integrating morphological, lithological, structural, land use, hydrological and seismic data within a GIS environment (DEM data from SPOT will form an important component of this dataset), and (4) derivation of statistical landslide hazard models through the integration of the landslide inventory with the GIS datasets. The results will be shown in the form of landslide inventory maps including a GIS database at various scales and a landslide hazard model showing landslide prone areas and distinguishing different hazard levels. Consequently, these mapping results will be used to assist in making rational decisions regarding local evacuation plans in areas susceptible to slope failure.

Since Skempton presented his theory of residual strength in clay soils in 1964 (with a consolidation of ideas in 1985), a huge body of results for the residual strength of many clays has been published. Nowhere is this more marked than in Britain. The datasets available have been derived from a variety of methods, including back analysis, laboratory tests on natural and reconstituted soils. Laboratory tests have included tests with broadly unlimited deformation (e.g. ring shear tests), tests on sampled shear surfaces, tests with slip surfaces pre-formed mechanically in the laboratory, and tests on undisturbed specimens (for example, reversal tests in the shear box). This paper concentrates on the results from back-analyses.

It has been observed (for example, by Bromhead, Ibsen (2004) Bedding-controlled coastal landslides in Southeast Britain between Axmouth and the Thames Estuary. Landslides 1(2):131–141) that very many of the landslides investigated around the South and East coasts of England are compound landslides with extensive sub-horizontal basal shear surfaces in locations that conform to the bedding. In some strata (e.g. Barton et al. (2006) The slip surface in the D zone of the Barton Clay. QJEGH 39(4):357–370) the basal shear occurs in a thin stratum of noticeably higher plasticity than above or below. It has also been observed that similar bedding control is exerted on the position of compound landslide basal shear surfaces in inland landslides, most noticeably in connection with failures of cut slopes for transportation infrastructure (roads and railways). Experience suggests that the results from a back-analysis are dominated by the properties of these strata where the bedding-controlled basal shear surface constitutes a significant fraction of the total length.

The paper presents an analysis of the data from published back analyses, supplemented with some of the more reliable laboratory testing that has been specifically recorded as being on samples from bedding-controlled basal shear surfaces, and compares datasets from a number of stiff fissured over-consolidated clays of very different ages. Inferences are drawn from these results about the mode of formation of what are taken to be sedimentologically-controlled weak horizons occurring throughout the geological record.

Landslides in volcanic mountainous terrains covered by poorly consolidated materials are common in Mexico. This investigation illustrates the landslides and geomorphologic changes of debris flow deposits in the town of Santa Cruz Pueblo Nuevo, State of Mexico, by using a multicriteria analysis in Geographic Information Systems (GIS) to obtain a potential hazard map.

The volcano has the fourth-highest elevation in Mexico (4,662 m a.s.l.) and it is in the geologic province of the Transmexican Volcanic Belt in the center of Mexico. The volcano is prone to landslides due to its loose vulcanoclastic sediments that are dragged by the streams and torrents during the rainy season. The basin extends from the rim of the volcano to the foothills at an altitude of 2,850 m a.s.l.

Unstable areas are mainly along first-order tributary streams and meander bends developed on lahars, pyroclastic flows, and pumice fall deposits whose stability has decreased in the basin. The unstable areas frequently create debris flows and debris slicing affecting the human settlements. On June 24, 1940, a large debris flow partially destroyed the town of Santa Cruz Pueblo Nuevo. Today, the town is settled in the alluvial fan of the old debris flows deposit. It is a highly probable that the town will be affected again by landslides and debris flows. As a prevention to future debris flow, have been constructed walls of containment (gabions) along the principal channel of the river La Ciénaga, nevertheless in every rainy season the gabions are saturated and frequently destroyed, which shows the intense activity of the remove gravitational processes.

In this paper we will present the overview of recent landslides in the Istria Peninsula, Croatia. The central area of the Istrian Peninsula is situated from the Trieste Bay in the west to the Učka Mountain in the east and is called Gray Istria according to gray colour of the Paleogene flysch sediments. Flysch rocks mostly consist of claystones, siltstones with intercalated calcareous sandstones and breccia-conglomerates. During the last two decades many small scale landslides occurred in the area. Based on field investigations conducted during remedial works designing, a data base of investigated landslides was established. Landslides in flysch slopes of Gray Istria are mostly rotational slides, falls and debris flows of small scale. The sliding surface is typically on the contact of the superficial deposits and flysch bedrock which is almost impermeable below the superficial deposits with low permeability. Due to the inconvenient geological conditions, long term intensive rainfall and anthropogenic influence mostly during road construction, the natural balance in the slope was disturbed, and instabilities occurred.

Many tropical mountain regions experience rapid land cover change and natural hazards like landslides. In this work, landslide controlling factors in two Andean catchments with different land cover dynamics were analysed using rare event logistic regression with replications. Our results show that topographical factors alone cannot explain the observed landsliding pattern. We suggest that major changes in soil properties and hydrology after deforestation play a role in accelerating landslide activity.

Disrupted vegetation is often used as an indicator for landslide activity in forested regions. The extraction of irregular trees from airborne laser scanning data remains problematic because of low quality of observed data and paucity of field data validation. We obtained high density airborne LiDAR (HDAL) data with 180 points m

−2

for characterizing tree growth anomalies caused by landslides in the Barcelonnette region, the Southern French Alps. HDAL allowed the mapping of a complex landslide and its three kinematic zones. The TreeVaW method detecting trees from the HDAL data and determined their position and height, while the SkelTre-skeletonization method extracted the tree inclination. The tree growth anomalies are parameterized by tree height dissimilarities and tree inclinations. These parameters were successfully extracted from the HDAL and compared with field data. We revealed that the distribution of LiDAR-derived tree growth anomalies was statistically different for landslide areas as compared to stable areas.

Landslide susceptibility assessment at different scales and in different physiographic environments requires quantitative information on multiple thematic environmental data. Information on bedding attitude proves necessary to define the structural and geological setting of an area. In this study, we developed a procedure to obtain bedding attitude data exploiting aerial photo-interpretation and a GRASS GIS script. Results show that our procedure provides bedding attitude information in good agreement with data acquired during field surveys. We foresee the possibility to generate dense spatial distributions of bedding attitude data, useful for spatial interpolation and landslide susceptibility assessments.

Aiming at improving the knowledge on the source areas of shallow landslides, this research deals with the geotechnical characterization of the debris slope cover of arenaceous formations, by means of low cost dynamic penetration tests (Dynamic Probing – DP).

The knowledge of strength parameters of this material is fundamental to understand the triggering mechanisms of the shallow landslides. Therefore, in order to determine the typical values of relative density (D

R

) and internal friction angle (φ′), many tests were performed and the results of 132 Dynamic Probing tests, 74 Standard Penetration Tests (SPT) and 14 laboratory shear tests, were analysed. The comparison between the φ′ values obtained by DP tests with those resulting from direct shear tests evidenced a good linear correlation. This confirmed the satisfactory and repeatable results of DP tests. Therefore, Dynamic Probing can be an effective, simple, practical and inexpensive tool for the geotechnical characterization of hazardous slopes.

The identification and quantitative study of important geological discontinuities, like those related to large landslides constitutes a paramount problem, which claims for a careful, detailed and, if possible, quantitatively based geomorphologic analysis. Numerical geomorphic analyses represent an interesting approach to these studies, allowing for a detailed and pretty accurate identification of hidden topographic anomalies that may be related to large landslides or other hidden geological structures. Geomorphic numerical analyses herein presented, are performed on the digital elevation model, based on the 2D discrete wavelet transform. This analysis is applied to a case study related to the middle-south Apennine at the front of the Apennine, whereas a really large deep-seated large landslide has been previously identified on the base of different geomorphic analysis. Finally, the analysis emphasizes some peculiar aspect of the buried front of the Apennine, which can potentially bias the landslide.

From studies of orthophotos and through field work, a complex deformation pattern has been recognized in the Lyngen area, Troms, Norway. The area is among the most alpine in Norway and contains a strong clustering of rock slope failures. The rock slope failures are characterized by two different deformation styles, and the difference in style is geographically separated by a fjord and valley lineament. Field studies suggest that two directions of tension oriented almost perpendicular to each other, utilize pre-existing brittle to brittle/ductile fabrics inherited from much older deformation events. The NE-SW direction of tension is parallel to the average displacement vector pointing down-dip along inherited faults. This vector is gravitationally controlled. The NW-SE displacement vector trends strike-parallel along the inherited faults. The presence of the latter appears to be confined geographically.

This work was aimed to highlight the spatial relationships between large-scale gravitational phenomena and tectonic uplifted structures in the area between Enza river valley and Taro river valley in the Northern Apennines. The structural-tectonic map of the investigated area and the inventory map of the large landslides and DSGSDs were made. The analysis of the structural map highlighted the existence of antiforms with axes roughly SE-NW. The comparison between the large landslides and the antiforms has shown that a spatial relationship between large complex landslides (earth/rock slides – earth flows) and positive geological structures exists.

Landslide inventories, their accuracy and the stored information are of major importance for landslide susceptibility modelling. Working on the scale of a province (Lower Austria with about 10,000 km

2

) challenges arise due to data availability and its spatial representation. Furthermore, previous studies on existing landslide inventories showed that only few inventories can be used for statistical susceptibility modelling. In this study two landslide inventories and their resulting susceptibility maps are compared: the Building Ground Register (BGR) of the Geological Survey of Lower Austria and an inventory that was mapped on the basis of a high resolution LiDAR DTM. This analysis was performed to estimate minimum requirements on landslide inventories to allow for deriving reliable susceptibility maps while minimizing mapping efforts. Therefore a consistent landslide inventory once from the BGR and once from the mapping was compiled. Furthermore, a logistic regression model was fitted with randomly selected points of each landslide inventory to compare the resulting maps and validation rates. The resulting landslide susceptibility maps show significant differences regarding their visual and statistical quality. We conclude that the application of randomly selected points in the main scarp of the mapped landslides gives satisfactory results.

Landslide susceptibility maps are key tools for land use planning, management and risk mitigation. The Landslide susceptibility map of Italy, scale 1:1,000,000 is being realized by using the Italian Landslide Inventory –

Progetto IFFI

and a set of contributing factors, such as surface parameters derived from 20 to20 m DEM, lithological map obtained from the geological map of Italy 1:500,000, and land use map (Corine Land Cover 2000). These databases have been subjected to a quality analysis with the aim of assessing the completeness, homogeneity and reliability of data, and identifying representative areas which may be used as training and test areas for the implementation of landslide susceptibility models. In order to implement the models, physiographic domains of homogeneous geology and geomorphology have been identified, and landslides have been divided into three main classes in order to take into account specific sets of conditioning factors: (a) rockfalls and rock-avalanches; (b) slow mass movements, (c) debris flows. The modelling tests performed with different techniques (Discriminant Anaysis, Logistic Regression, Bayesian Tree Random Forest) provided good results, once applied with the appropriate selection of training and validations sets and with a significant number of statistical units.

In the context of the European Soil Thematic Strategy, and the formulation of a draft of a European framework directive devoted to the sustainable use of soil, landslides are recognized as one of the eight soil threats requiring harmonized spatial hazard assessments over the EU territory. The general framework for such assessments consists of a nested geographical approach based on “Tiers”, where a low-resolution (1:1 Million) evaluation (“Tier 1”) using already available pan-European datasets should enable the delineation of priority areas requiring more detailed assessments with additional data (“Tier 2”). In this contribution, we present new developments in the elaboration of a “Tier 1” generic landslide susceptibility evaluation based on a heuristic modelling approach exploiting the most important landslide conditioning factors. Extensive landslide locations available at small spatial scales have been collected and harmonized over the EU territory to be used for input parameter specification and model calibration, evaluation and classification. Since the analyzed area is highly complex in terms of climato-physiographic conditions controlling landslide occurrences, a preliminary landslide terrain differentiation is proposed consisting of eight calibration zones where specific predictor class weights have been allocated through a heuristic indexing approach. The spatially combined preliminary pan-European susceptibility estimate classifies 13 % of the EU territory as prone to landslides, thus requiring more detailed, quantitative inventory-based susceptibility evaluations (“Tier 2”).

Information on landslide susceptibility and hazard at the national scale is of fundamental importance for the design and implementation of risk management policies and the prioritarization of the allocation of resources. Lack of such information in Europe and the implementation of the European Union’s Thematic Strategy for Soil Protection (Commission of the European Communities, Thematic strategy for soil protection. COM(2006)231 final. Brussels, 2006a; Commission of the European Communities, Proposal for a Directive of the European Parliament and of the Council establishing a framework for the protection of soil and amending directive 2004/35/EC. COM(2006)232 final. Brussels, 2006b) let to an initiative of

JRC

(

Joint Research Centre

, European Commission) to setup a European

Landslide Expert Group

in order to identify the areas in Europe where landslides are likely to occur. In this context, this work presents the method developed for the creation of the ‘Tier 1’ landslide susceptibility map for France at a 1:1M scale, where susceptibility is defined as the spatial probability of occurrence of an event. The method is applied by differentiating three categories of landslide types, namely slides, falls and flows. More specifically, the method combines a weighting-rating procedure of both factors and classes of factors using a spatial-multi-criteria evaluation technique (SMCE) and an objective calibration of the weights based on statistics on the distribution of observed landslides per slope angle, lithology and landcover classes. The quality of the nation-scale map is evaluated with references (1) to the French landslide inventory map BDMvT, and (2) to regional or local susceptibility maps available in the literature or created for planning purposes.

Norway is prone to a variety of different landslide types. Despite this fact, inferior efforts have been undertaken to establish a national overview of which areas can be considered safe and which have a potential landslide hazard. As a consequence, many municipalities have allowed construction of buildings and infrastructure in landslide hazardous areas. In 2007, Geological Survey of Norway initiated a project to develop susceptibility maps for rock-fall and snow avalanche, on the basis of a 25 × 25 m digital terrain model covering the whole country. The GIS algorithms were developed in a consensus driven approach involving universities, research institutes, consultancies and several public authorities. The produced maps aim to raise awareness of possible landslide hazards in municipality land-use planning.

In this paper Geographic Information Systems (GIS) are applied to map the spatial zonation of mass movement susceptibility in national scale via artificial neural networks (ANN), and spatial statistical modelling that is, frequency ratio and Logistic Regression (LR). For this purpose 16 potential factors were identified to map mass movement susceptibility across Greece mainland. Among these, seven factors: elevation, slope, precipitation, geology, land cover, terrain forms and seismic acceleration, were ranked as the most important, applying susceptibility index (s

ij

) and standard deviation criterion. The output mass movement susceptibility map derived from (LR) model showed 85.33 % in prediction accuracy of the total area of Greece. Frequency ratio showed 71.62 % and ANN showed 60 %. According to the obtained results LR model is the most accurate, while the two other models gave reasonable results. Future work will focus on regional scale in order to refine the proposed models in landslide prone regions.

A new method for assessing landslide hazard was proposed and implemented in El Salvador. In this method hazard is defined as a conditional probability of failure due to rainfalls or earthquakes which are in turn dependent on the slope susceptibility.

Total probability was obtained considering probability and susceptibility functions for different slope failure mechanism, this is: coherent, disrupted slides, and flows; and using conditional probability for conditioned events. The application for El Salvador evaluated the landslide hazard for cells of 1 × 1 km; topographical, rainfall and seismicity data was obtained from the SNET in El Salvador.

Probability of failure for rainfall-induced and earthquake-induced landslides and total probability of failure was calculated for the whole country and spatial hazard distribution was plotted and hazard maps for each case were obtained. Hazard maps fit very well with rainfall-induced and earthquake-induced distribution of historical landslides in El Salvador and can be used as a risk management tool.

The large, deep-seated Gryfenbach landslide in Lauterbrunnen, Switzerland, endangers part of the village as well as the main entrance to the whole valley. A mass of about 25 million m

3

is situated at the left valley entrance and moves with an average of cm a year. In the steep frontal part of the sliding mass two large spontaneous landslides have been recorded (secondary processes). Following the abnormally intensive snowmelt in spring 1999 the movement increased 30-fold. Important infrastructures within the landslide were destroyed. A complicated monitoring system has been installed to understand the landslide’s behaviour and hazard potential in detail.

At the same time the authorities start to elaborate the hazard map of the valley. Through extensive field investigations, analyses of monitoring data and conclusions by analogy from other large landslides the relevant scenarios for the hazard assessment have been formulated. In 2003 the first draft of the hazard map existed GEOTEST AG (Technischer Bericht zur Gefahrenkarte Lauterbrunnen, Nr. 00063.5, Zollikofen (unpublished), 2003), see Fig. 10). In 2011 a revised hazard map has been published GEOTEST AG (Lauterbrunnen, Naturgefahren, Bericht zur Teilrevision Gefahrenkarte, Nr. 10151.01, Zollikofen (unpublished), 2011). This product is based on today’s hazard assessment methods. The paper focuses on the Swiss hazard assessment methodology, on the scenario definition of large, deep-seated landslides illustrated on the case study in the Lauterbrunnen valley.

Sri Lanka, is located in the Indian Ocean between northern latitudes of 5°51′ and 9°51′ and eastern longitudes of 79°40′ and 81°55′ approximately 24 km to the southeast of India. Sri Lanka occupies an area of nearly 65,000 sq km stretching to 435 km from North to South and 224 km from West and East.

The climate of Sri Lanka varies from semi-arid to mild temperature. The mountains located in the central part of the island are surrounded by low land that extends up to the shores. Those climatologic and morphological variations influence two monsoonal and inter-monsoonal periods. Country’s annual rainfall varies from 2,500 to over 5,000 mm in the south-western part of the island, while in the north-west and south-east, rainfall averages less than 1,250 mm annually. Mean annual temperature is 27 ° C in the lowlands of Sri Lanka and in the central highland with an altitude up to 400 m; the mean annual temperature is 15 ° C.

The excessive rainfall and varied climate has contributed to the land degradation, especially in the mountainous region of the country where rainfall is the major triggering factor of landslides. With the disastrous landslides that occurred in mid 1980s, the Government of Sri Lanka took the initiates of studying the landslide phenomena in the country and as a result about 70 % of the landslide prone districts have been mapped in terms of their landslide potential and general guidelines for construction and development have been prepared in order to reduce the landslide risk

http://www.nbro.gov.lk/web/index.php?option=com_content&view=article&id=168&Itemid=192&lang=en

(2011). Landslide early warning is issued for ensuring the safety of the people who live in the central highlands and the mountainous communities are being educated on the measures they can take to halt or reduce the landslide threat. Since recently, the country has also stepped into the mitigation of landslides that have imparted a threat on human settlements, public thoroughfares, public buildings etc. This paper provides an overview of Sri Lanka’s efforts in landslide risk reduction studies.

This study focuses on the comparison of different approaches for landslide susceptibility modelling and is part of the research project “MoNOE” (Method development for landslide susceptibility modelling in Lower Austria). The main objective of the project is to design a method for landslide susceptibility modelling for a large study area. For other objectives of the project we refer to Bell et al. (Proceedings of the 2nd world landslide forum, Rome, 3–7 Oct 2011, this volume). To reach the main objective, the two different statistical models “Weights of Evidence” and “Logistic Regression” are applied and compared. By using nearly the same input data in test areas it is possible to compare the capabilities of both methods. First results of the comparison indicate that in valleys and on south facing slopes the results are quite similar. In contrast, the analysis on north facing slopes shows differences. In the ongoing work the reasons for these differences will be analysed. Furthermore, attention will be paid to finding adequate validation methods for the two modelling approaches.

The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

This contribution proposes an approach to model regional landslide susceptibility, based on a supervised learning technique that mines fuzzy emerging patterns on a set of classified data. In our approach the training set contains positive and negative examples of areas, (i.e., slope units), affected or not affected by landslides. The fuzzy emerging patterns characterise the positive and the negative areas exploiting their ability to discriminate between the two classes. The approach consists first, in inducing a set of fuzzy rules, and then in reducing them by retaining those that identify fuzzy emerging patterns for the given training set. The fuzzy rules define the main characteristics of the slope units that are affected or not affected by landslides and are used to classify other slope units in the same region. The classification technique provides an estimate of the hesitation of the decision process, which is a measure of its ability to uniquely associate a slope unit to the susceptible or not susceptible class. In the paper we describe the approach and discuss the preliminary results.

Since the landslide is one of the repeated geological hazards and causes a terrible loss of life and properties in Korea, many different researches have been carried out to evaluate the hazard and the susceptibility of landslide. The physical landslide model has been suggested to evaluate the factor of safety in previous studies but the deterministic approach has been utilized. However, applying the deterministic model in regional study area can be difficult or impossible because of the difficulties in obtaining and processing of large spatial data sets. With limited site investigation data, uncertainties were inevitably involved with. Therefore, the probabilistic analysis method such as Monte Carlo simulation has been utilized in this study. The GIS based infinite slope stability model has been used to evaluate the probability of failure. The proposed approach has been applied to practical example. The study area in Pyeongchang-gun, Gangwon-do has been selected since the area has been experienced tremendous amount of landslide occurrence.

In Mexico, numerous GIS-based applications have been used to represent and assess slope stability. However, there is not a practical and standardized landslide mapping methodology under the GIS system. This work aims to illustrate a comprehensive methodology to characterize areas that are prone to slope instability. The Río Chiquito-Barranca del Muerto watershed on the southwestern flank of Pico de Orizaba volcano, the highest mountain in Mexico, was selected as study area. The study area has a combination of several contributing factors to landslides such as high rain fall during the wet season, rock types, high degree of weathering, and steep slopes.

The methodology encompasses three main stages of analysis to assess landslide hazards. The technique and its implementation in a GIS-based technology is presented and discussed.

Within the scope of the EU program INTERREG IV A (Italy/Austria), the project MassMove – with partners from the regional governments of Carinthia (Austria), and of Friuli Venezia Giulia and Veneto (Italy) – aims at establishing guidelines for the compilation of landslide susceptibility and hazard maps at regional and local scale. Project activities started December 2008; it will be concluded in November 2011.

A methodological approach for the susceptibility analysis and zoning, at medium scale, of hyperconcentrated flows is presented. The adopted procedure comprises the following steps: (1) collection of data useful to acquire detailed knowledge of the slope processes leading to flow-like mass movements in the site; (2) hyperconcentrated flow susceptibility analyses via heuristic and statistic procedures; (3) hyperconcentrated flow susceptibility zoning (1:25,000 scale) at a preliminary/intermediate level. The procedure is applied to the test site of Monte Albino, (southern Italy), which extends over an area of around 400 ha. The obtained results emphasize the potential of an approach which moves from preliminary to intermediate level of susceptibility zoning. The results also highlight the important role played by the combined use of different procedures, based on heuristic and statistical models, in defining a standardised criterion to be adopted in problems dealing with the analysis and zoning of susceptibility to hyperconcentrated flows.

A comprehensive inventory of the landslide risk in the Göta älv valley, Sweden, is conducted to limit consequences of climate change on society. Here we present an overview of the project and highlight key problems to be solved. Methodology developments and investigations are performed regarding mapping of quick clay, hydrological and meteorological conditions, erosion and risk analysis. Much of the knowledge and experience gained in the project can be implemented and used elsewhere, nationally and abroad.

Probability maps of landslide reactivation are presented for the Aiguettes landslide located in the southern French Alps based on results obtained with dendrogeomorphic analysis. Spatio-temporal activity was derived from tree-ring series of 223 disturbed trees. 355 growth disturbances were identified in the samples indicating 14 reactivation phases of the landslide body between 1898 and 2011. Probabilities of landslide reactivation were computed and illustrated using a Poisson distribution model. For example, in the toe, the probability increases from 0.28 for a 5-year period to 0.99 for a 100-year period. This method differs from conventional approaches, which have demonstrated to have limitations in the prediction of spatiotemporal reactivation of landslides. Based on extensive data and therefore allowing determination of quantitative probability maps of reactivation, this approach is considered a valuable tool for land managers in charge of protecting and forecasting people as well as for those responsible for land-use planning and management.

Spatial information acquisition and analysis tools play a fundamental role to supplying the information necessary to produce landslide inventories, which represent the foundations for quantifying landslide hazard and vulnerability. In this frame, fundamental data are Digital Surface Models (DSMs) and Digital Elevation Models (DEMs).

The goal of this paper is just methodological, focused to illustrate the actual potentialities of DSMs generation from high resolution satellite Synthetic Aperture Radar (SAR) imagery with a radargrammetric stereo-mapping approach. The fundamental advantage of this approach is that it can work with just a couple of images (no matter for their coherence), which can be collected in a short time (half day to quite few days) thanks to the independence of satellite radar acquisition from weather (clouds), daylight and logistic constraints (as for airborne data collection).

The suite for the DSMs generation through the radargrammetric approach has been implemented in SISAR (Software per Immagini Satellitari ad Alta Risoluzione), a scientific software developed at the Geodesy and Geomatic Institute of the University of Rome “La Sapienza”. In order to demonstrate the radargrammetric mapping potentialities of high resolution SAR data, a test site was established in the area of Merano (Northern Italy), characterized by mixed morphology and land cover. The data available for the experiment were a COSMO-SkyMed SpotLight stereo pair and a LiDAR DEM, used as ground truth. An accuracy better than 3 m has been achieved in open areas and the implemented algorithm appears able to generate DSMs both over open and forested areas, where the accuracy is around 4 m.

Therefore, radargrammetric generation of DSMs from high resolution satellite SAR imagery appears a valuable tool to supply topographic information for landslide inventories at different scales.

Slope angles are a key parameter in estimating susceptibility to developing earth flows. In this paper, slope angles are used to estimate potential unstable areas in a pilot sector of the Benevento province in (Southern Italy).

Since the study area is characterized by a complex lithological setting, landslide distribution was analyzed within four-groups of homogeneous litho-technical sequences. Slope angle frequency distributions were obtained from a landslide sample in accordance with the Weibull probability density distribution function. Their analysis shows that the largest occurrence of landslides fall within an interval of slope angles ranging from 9° to 14°. As filed surveys confirm, the low frequency of instabilities on steeper slopes can be explained by a deficit of potentially involving materials, partially due to the presence of stony sequences. Consequently, the probability of failure was calculated only on slope angle ranges already affected by existing landslide phenomena.

The Emilia Romagna Region (RER) is probably one of the most landslide susceptible regions of the world, with ~24 % of the mountain sector covered by landslide accumulations. The regularly updated 1:10,000 Landslides Inventory Map (LIM), managed by the Regional Geological Survey, counts more than 70,000 landslides. Nowadays most land-use planning is based on LIM but this has several intrinsic shortcomings, mainly due to its scale and forecast significativity. This paper presents the methods we used to compile a detailed susceptibility map for the whole RER Apennines.

The triggering mechanism of the most common landslides phenomena in RER, disregarding of the subsequent evolution, is characterized by a first movements that may be described as “shallow phenomena” involving the upper part of the landslides (depletion areas). For this reasons we developed a model for the areas “outside” the LIM mapped landslides aimed to identify the triggering areas for future landslides. For this statistical analysis we used Bivariate Logistic Regression methods. As our aim was to predict triggering phenomena, we calibrated the model on the depletion areas, selected using a semi-automatic GIS procedure. The resulting map can be used for LIM verification and updating and adds it a forecast connotation useful for land use planning; nevertheless it has to be used by experienced users, for this purpose the model advantage and shortcomings will be discussed.

The principal aim of this study is to compare different landslide susceptibility zonation models for predicting areas prone to shallow landsliding using both physically distributed landslide models and artificial neural networks. Necessary geotechnical and hydrological parameters were obtained coupling sample laboratory analysis and in situ measures; soil thickness was estimated using an empirical model while distribution of rainfall intensity was analyzed by performing a spatial interpolation. The predictive capabilities of these models were finally evaluated using a threshold-independent quantitative method (the ROC plot).

We evaluated the landslide susceptibility in Sicily region (Italy) (25,000 km

2

) using a multivariate Logistic Regression model. The susceptibility model was implemented in a GIS environment by using ArcSDM (Arc Spatial Data Modeller) to develop spatial prediction models through regional datasets. A newly developed algorithm was used to automatically extract the scarp area from the whole landslide polygon. From the many susceptibility factors which influence landslide occurrence, on the basis of detailed analysis of the study area and univariate statistical analysis, the following factors were chosen: slope gradient, lithology, land cover, a curve number derived index and a pluviometric anomaly index. All the regression logistic coefficients and parameters were calculated using a selected landslide training dataset. Through the application of the logistic regression modelling technique the final susceptibility map was derived for the whole area. The results of the analysis were validated using an independent landslide dataset. On average, the 81 % of the area affected by instability and the 80 % of the area not affected by instability was correctly classified by the model.

Landslides threaten most parts of the provincial state of Lower Austria and cause damage to agricultural land, forests, infrastructure, settlements and people. Thus, the project “MoNOE” (Method development for landslide susceptibility modelling in Lower Austria) was initiated by the provincial government to tackle these problems and to reduce further damage by landslides. The main aim is to prepare landslide susceptibility maps for slides and rock falls and to implement these maps into the spatial planning strategies of the provincial state.

Landslide susceptibility maps are either prepared by statistical (for slides) or empirical or process-based (for rock falls) approaches. Final maps are combined to a single landslide susceptibility map and optimised for the end-users (spatial planners and local authorities). It shows that a difference exists between the best scientific maps and the best maps for spatial planning purposes. This involves questions about the best number of susceptibility classes, its thresholds and ideal colours.

We present the Geological Hazard Prevention Map of Catalonia 1:25,000 (MPRG25M), and in detail, the procedure carried out for landslide hazard determination. As a component of the Geoworks of the Geological Institut of Catalonia (IGC), the MPRG25M is a multi-hazard map at 1:25,000 scale conceived to be used for land use planning. It includes the representation of evidence, phenomena, susceptibility and natural hazards of geological processes. These are the processes generated by external geodynamics (such as slope, torrent, snow, coastal and flood dynamics) and internal (seismic) geodynamics. The information is displayed by different maps on each published sheet. The map is intended to enable government and individuals to have an overview of the territory with respect to geological hazards, identifying areas where it is advisable to carry out detailed studies in case of action planning.

ISPRA and Tuscany Region Administration recently funded a project aimed at assessing and mapping landslide hazard of the area of the n. 250 “Castelnuovo di Garfagnana” map (1:50,000 scale). The area includes the upper Serchio River basin (Tuscany, Italy) and exhibits peculiar geological and geomorphological features and severe climatic conditions, which cause high landslide hazard. The project proceeded as follows:

1:10,000 geomorphological survey and landslide inventory map;

Physical and mechanical properties of rocks (discontinuities, strength, rock mass classification) and soils (grain size, consistency);

GIS oriented organization of the spatial distribution of the considered factors;

GIS supported statistical analysis (spatial analysis, conditional and multivariate analyses, neural network technique);

Landslide hazard map, where landslide hazard is subdivided into five classes based on instability probability;

Final products: landslide hazard map at 1:50,000 scale, together with other related maps (landslide map, structural sketch, geotechnical sketch, isohyet map, etc.); explaining booklet; database.

Remote Sensing (RS) and Geographic Information System (GIS) play a significant role in landslide investigation, in terms of evaluation and analysis of specific landslide event from local to regional scale. It greatly assists in identifying vulnerable zones of future landslide occurrences, which is very important to those who settle in unstable slopes. Generation of regional to large scale landslide hazard zonation map is of great importance for developmental planning in North Eastern Region (NER) of India which falls in the high and medium to high category of the Global Landslide Susceptibility map. In addition to this, rugged and highly undulating topography of the eight states of NE India require serious concern on development of Landslide Early Warning System to reduce landslide related risk. NESAC, being the nodal agency for Space Applications in NER has taken up initiative in the same direction.

Many destructive debris flows hit several villages in the Peloritani Mountains area (Sicily, Italy) in October 2009. The collection of several types of spatial data, together with the landslides inventory, allowed the assessment of the landslide susceptibility by the application of two different bivariate techniques.

Furthermore, the susceptibility analysis allowed to state which classes within the different factors, have greater relevance in slope instability and afterwards if some of these can somehow be linked (with a short-medium term incidence) to some of the endogenic processes acting in the area (huge regional uplift, fault activity). Therefore we are able to propose a geomorphologic model of cyclic evolution of the relief in which the endogenic processes are directly linked to the superficial ones.

This work shows just some preliminary results of a greater study that involve the susceptibility analysis and its interpretation in a geodynamics perspective, for the whole southern Calabrian Arc.

The paper presents the results of landslide susceptibility maps elaboration for the Sibiciu, Panatau and Saratel basins (Buzau Carpathians and Subcarpathians, Romania) and the assessment of landslide displacements using extensometers in Romania. The landslide susceptibility maps were elaborated using the bivariate statistical analysis and the index of entropy. Observations concerning landslide displacements using extensometers were focused on two test sites located in the Ivanetu Summit (the Colti church area) and the Buzau Subcarpathians (Maguricea landslide). The system measurement from Maguricea landslide using optical fiber is the first system installed on a test site in Europe. The studies were elaborated in cooperation with Comenius University, Bratislava, Slovakia and the Public Works Research Institute, Tsukuba, Japan.

This paper presents the results of landslide susceptibility and landslide hazard mapping together with preliminary landslide risk studies on qualitative basis. The target area is situated in the south of Kyrgyzstan, Central Asia, in the valley of Mailuu-Suu River. There are several uranium waste tailings situated in the target area and there is the risk that landslide activity can result in an environment catastrophe through destruction of waste tailing and damming of river channel leading to flooding of radioactive material. For remediation measures and risk mitigation there is the need to have reliable estimates of landslide susceptibility and hazard in target area on local and regional scales.

An attempt to assess the predictive power of the MSUE Conditional Method was made in landslide susceptibility zonation of the Milia Basin, Tuscany, Italy. A detailed geomorphological mapping, combined with aerial photographs analysis, enabled us to build two landslide inventories using a time scale. The landslides related to a period before 1975 were used to create the models, while those related to a period after 1975 were used to validate the models predictive power. Five time invariant factors maps were also developed in a GIS environment. Finally, the inventory landslides maps and the five landslide-related factor maps were processed using a model in a GIS environment. The procedure was applied separately to the most frequent landslides typologies and for each different combination of the five factors. The comparison between the distribution of landslides after 1975 and the predicted distribution derived from susceptibility models established the predictive power of each model.

In this paper a landslide risk assessment in the area of Aguas Calientes village (Machu Picchu, Cusco, Perù) is applied. A study carried out into a capacity building project (FORGEO) was focused on localising source areas and runout of debris flows triggered by heavy rainfall in the Alcamayo catchment and on assessing debris flow intensity. Starting from an inventory of several previous debris flows occurred in the area, an evaluation of the local predisposing parameters to these events was used as input for susceptibility and hazard GIS based analysis. Empirical formulas reported in the literature were adapted to the research area context to estimate the runout of potential events. An analysis of exposure of structures and infrastructures was also performed during the project and high residual risk conditions were found for the Aguas Calientes village. These results may aid local authorities involved in land use planning, management policies and landslide risk reduction.

On the 1st of March 2010 a heavy rainfall event triggered a devastating landslide in the Bududa region on the footslopes of Mount Elgon in eastern Uganda, destroying life and property. Earlier studies published in 2006 and 2007 looked at characteristics and causal factors of older landslides in the area based on a landslide inventory and a detailed digital terrain analysis. In addition, a landslide hazard assessment was conducted with the LAPSUS-LS landslide model identifying susceptible landslide triggering sites and scenarios of landslide erosion and deposition quantities and pathways. This paper revisits the earlier studies and assesses how accurately the recent landslide was predicted. In addition a revised landslide scenario for the near future is elaborated based on the critical rainfall threshold that triggered the recent landslide.

Mud and debris flows constitute a serious threat for several Italian regions as attested by recent several disasters attributable to such phenomena. The adoption of effective mitigation measures is complicated by the difficulty in predicting spatial and intensity features of future events.

This paper applies a practical application of debris/mud flows hazard assessment in the area of Messina province. The study was based on an inventory of several debris flows triggered by heavy rainfall occurred in the Giampilieri and Briga catchments after the event of October 1, 2009. Data elaboration was focused on mapping source areas and on assessing the runout of landslides and their intensity. An evaluation of the factors that make the area prone to these events was used as input for a GIS based hazard prediction model.

A procedure to select the controlling factors connected to the slope instability has been defined. It allowed to assess the landslide susceptibility in the Rio Beiro basin (about 10 km

2

) over the north-eastern area of the city of Granada (Spain). Field and remote (Google Earth

TM

) recognition techniques allowed to generate a landslide inventory consisting in 127 phenomena. Univariate tests, using both association coefficients and validation results of single parameter susceptibility models, allowed to select among 15 controlling factors the ones that resulted as good predictor variables; these have been combined for unique conditions analysis and susceptibility maps were finally prepared. In order to verify both the goodness of fit and the prediction skill of the susceptibility models, two different validation procedures were applied and compared. Both procedures are based on a random partition splitting of the landslide archive for producing a test and a training subset. The relative error, considered between the intersected target landslides by the different susceptibility classes, was used to estimate the predictive skill of the maps.

An application of GIS for landslide hazard assessment using multivariate statistical analysis, mapping, and the evaluation of the hazard maps is presented. The study area is the Changunarayan VDC (8.19 km

2

) located in the central region of Nepal and listed on the UNESCOs world heritage site in 1979 A.D., which is under pressure of high construction activities. Data used to construct the landslide hazard maps were obtained from published works, topographical and geological maps, satellite images and aerial photographs and other digital sources. To determine the factors and classes influencing land sliding, layers of topographic factors derived from a digital elevation model, geology, and landuse/land cover were analyzed and the results were used for hazard mapping. Hazard map of the study area shows 15.13 % area lies in the high hazard level, 53.87 % on moderate hazard level and 28.53 % in low hazard level.

This paper describes a method for analysis of various input parameters used in preparation of Landslide Hazard Zonation Maps. The method is based on the quantitative approach, which includes four Landslide Hazard Evaluation Factors grouped into four ranges of values. Since the various parameters are not equally important for estimation of Total Landslide Hazard Evaluation Factor (TLHEF), importance ratings are allocated to the different value ranges. Importance ratings for Lithological types (LT), Ground Water Level (GWL), Slope Angles (SA) and Soil Debris Cover (SDC) are defined using polynomial interpolation. With this procedure, each evaluation factor is related to the corresponding ratings using interpolation charts and equations. Based on the correlation between the adequate parameters and the rating, the Total Rating Hazard Evaluation Factor can be calculated.

Landslides form major natural hazards in hilly terrain in the area, and caused extensive damages to road, human dwellings and agricultural lands. There is still a great danger of further landslides in the region. Therefore, it is important to prepare a landslide susceptibility map of the region. In this study a landslide susceptibility map of Yadak-Tevil watershed was prepared using the Analytical Hierarchy Process (AHP) with the help of GIS. For this purpose, thematic layers including landslide inventory, lithology, distance from drainage, slope, slope aspect, and elevation were the main contributory factors to be considered for landslides susceptibility zonation. The landslide susceptibility map was classified into four different landslide susceptibility classes. The four landslide susceptibility classes are: low 16.13 % (33.50 km

2

), moderate 33.34 % (69.38 km

2

), high 33.00 % (68.68 km

2

), and very high 17.53 % (36.48 km

2

), respectively. Results of this study show that the AHP method is precise method for evaluation of landslide potential due to the use of binary comparison affecting factors and considering numerous factors for landslide evaluation at the same time in comparison to the other prevalent method.

The digital elevation models (classical DEM 5 and DEM 12.5), publically available in Slovenia, have been evaluated as a basis to prepare numerical square grids 5 × 5 m for 2D modeling of possible debris flows on torrential fans, using the model Flo-2D. Also recently available LiDAR data in their original resolution have been used, as well as their decreased resolution to the one of the numerical grid (e.g. 5 × 5 m). From our numerical results it seems obvious that the use of more precise LiDAR data over classical DEMs for numerical debris-flow modeling is fully justified. Better quality of input topographic data assures higher accuracy of results and therefore also accuracy of hazard maps produced in such a way. The LiDAR data promises better representation of torrential channels on torrential fans (narrow, deep channels) and computed results (velocities, depths) are generally better estimated. Using more precise data also increases computational times compared to using classical DEMs.

This article addresses performance evaluation routine for comparison of results of several different landslide susceptibility models. The study area is located on the NW slopes of Fruška Gora Mountain (Serbia). Five modelling methods were considered: Stability Index, Analytical Hierarchy Process (AHP), Fuzzy sets, Conditional Probability, and Support Vector Machines (SVM). In this respective order they gave more accurate spatial prediction of landslides. The performance of their “probabilistic” prediction is estimated by Receiver Operating Characteristics (ROC). Evaluation in ROC space is discussed in both quantitative – Area Under Curve (AUC) value, and qualitative manner – ROC curve trends. Finally, the article summarizes the advantages of the proposed ROC-based performance comparison.

Landslides are considered as a geological disaster that has an unfavourable effect on lives and properties, generating both direct and indirect economic and human losses every year. Compared to other geological disasters, landslides are considerably smaller in scale, more dispersed, but more disastrous in many cases.

The presented methodology is based on a case–event system, which uses spatial analysis functions and artificial intelligence techniques, to evaluate potential instability problems concerning natural or artificial slopes. The methodology allows the user to examine new cases or areas of interest and compares them to previously recorded cases of instability problems that occur in the research area. The effectiveness of the methodology is evaluated in Kimi, Euboea, Greece, an area experienced substantial landslide events, where a well documented database of previous studies existed.

The Himalayan mountain range, divided by deep and active thrusts, is a region of highly sensitive to tectonic stability. The Main Boundary Thrust (M.B.T.) defines the boundary of the Lesser Himalaya against Outer Himalaya. In this, an old landslide was reactivated during monsoon period in 1992 and the area is now experiencing frequent slides throughout the year affecting 50–60 ha of area. On an average 1–2 ha of land is being swept away every year in the area. The existence of Main Boundary Thrust (MBT), toe erosion by Nihal River, loading of slope crest (intensive settlement and agricultural processes and village path), regular and heavy water discharge in slided area, highly jointed rocks, low vegetation cover, high monsoonal precipitation and thin soil cover were found to be foremost causative factors. Major anthropogenic activity i.e. construction of ‘cart-track’ amid the critical slope had promoted vulnerability of the area. The land conservation measures adopted by Soil Conservation Department and Forest Department also proved futile. Rambans Plants (

agave americana

) and Chari hurbs (

Sorghum bicolor

) are being planted by the inhabitants for land conservation. Various recommendations are proposed.

Heavy rainfall often triggers shallow landslides (slope failures) in Japan. In addition, the Geographical Survey Institute (GSI) now provides digital elevation data and digital geological maps from the Geological Survey of Japan are also available. Hence using GIS, we analysed the distribution of heavy-rainfall induced shallow landslides at six locations (Fig. 1) in relation to slope gradient.

Results showed that shallow landslides are concentrated on slopes with gradients between 25° and 30°, regardless of the difference in bedrock geology at the six locations. The former suggests that the occurrence of shallow landslides depend on slope gradient rather than bedrock geology.