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On 17 November 2000 a major landslide occurred on the slopes of Mount Mangart in the upper Posocje region, Slovenia, as a direct consequence of extreme rainfall and assortment of several inconvenient circumstances. A research group was established immediately after the event to find possible causes of the landslide and monitor its consequences. As a part of these attempts also remote sensing and integration of remotely sensed data to GIS was used. In the paper usefulness of satellite images as one of the most convenient data source in natural hazard observation is demonstrated. Satellite images were acquired within the “Space and Major Disaster” Charter, started just a few weeks before the event by the European Space Agency, the Centre National d’Etudes Spatiales and the Canadian Space Agency. Advanced image processing was performed carefully to analyze various aspects of the event. Before and after radar images were used to detect soil moisture and…

On 17 November 2000 a major landslide occurred on the slopes of Mount Mangart in the upper Posocje region, Slovenia, as a direct consequence of extreme rainfall and assortment of several inconvenient circumstances. A research group was established immediately after the event to find possible causes of the landslide and monitor its consequences. As a part of these attempts also remote sensing and integration of remotely sensed data to GIS was used. In the paper usefulness of satellite images as one of the most convenient data source in natural hazard observation is demonstrated. Satellite images were acquired within the “Space and Major Disaster” Charter, started just a few weeks before the event by the European Space Agency, the Centre National d’Etudes Spatiales and the Canadian Space Agency. Advanced image processing was performed carefully to analyze various aspects of the event. Before and after radar images were used to detect soil moisture and…

Landslides are severe environmental hazards in mountains areas. Nowadays, the threat of landslides to public safety has become more pronounced as a result of the burgeoning development in landslide-prone areas, the increase of deforestation in hilly areas, and the increase of regional precipitation caused by global climate change.
Traditional landslide risk assessment requires immense physical power to assemble different in-situ data such as identification of landslide location, land-cover classification and surface geometry. Such traditional data collection technique is very time consuming, and thus impossible to be applied for the regional scale assessment.
Remote sensing techniques, therefore, are the solutions for providing fast and up-to-data landslide assessments. This thesis focuses on the applications of multispectral remotely sensed data for landslide recognition and landslide prediction. Wollongong of Australia was chosen as a test bed for these…

This study investigates and demonstrates the state of the art in remote sensing techniques for detailed landslide hazard assessment applicable to large areas. Since the most common methods of landslide hazard assessment using simple inventories and weighted overlays are heavily dependent on three-dimensional terrain visualization and analysis, stereo satellite images from the IKONOS Very High Resolution (VHR) sensor are used for this study. The DEMs created from IKONOS stereo images appear to be much more accurate and sensitive to micro-scale terrain features than a DEM created from digital contour data with a 2 m contour interval. Pan-sharpened stereo IKONOS images permit interpretation of recent landslides as small as 2–3 m in width as well as relict landslides older than 50 years. A cost–benefit analysis comparing stereo air photo interpretation with stereo satellite image interpretation suggests that stereo satellite…

Collecting information on landslide occurrence and activity over wide areas is a crucial task for landslide hazard assessment. Field techniques, despite being very precise, are usually not sufficient to achieve this goal, since they mostly provide point-based measurements. Mainly because of its synoptic view and its capability for repetitive observations, optical (visible-infrared) remotely sensed imagery acquired at different dates and at high spatial resolution can be considered as an effective complementary tool for field techniques to derive such information. An image-processing method to map and monitor landslide activity using multitemporal optical imagery is proposed. The method entails automatic change detection of suitably pre-processed (geometrically registered and radiometrically normalised) sequential images, followed by thresholding into landslide-related change pixels. Subsequent filtering based on the degree of rectangularity of regions can also be…

Almost all preparatory and triggering causal factors are well set in place in the case of Philippines to make its sloping terrains vulnerable to landslides; the history of landslide occurrences stands as foolproof evidence. A review of the past events however indicates that rainfall has, inter alia, been offering the triggering effect to cause most of the devastating landslides. A number of such landslides have occurred in the Southern Leyte province of Philippines causing considerable loss of life and damage to properties. Facilitating towards managing the associated landslide risk in Southern Leyte it was aimed at delineating the areas that are prone to rain-triggered landslides. The SINMAP model which combines a mechanistic slope stability model with a steady-state hydrology model was employed in way accomplishing this, much needed, task. Elevation data in the form of a raster GIS layer was the main input for the model. Mapping of past landslide initiation points…

Large landslides are one of the main natural hazards in Kyrgyzstan. Because of the high number of landslides and their relative inaccessibility in mountainous terrain the potential of satellite remote sensing in combination with GIS-based analysis has been investigated in the frame of a collaboration with the Ministry of Emergency and Environment (MEE) in Kyrgyzstan. Emphasis is put on the development of multi-temporal remote sensing techniques to support landslide inventories and characterisation of main terrestrial factors preconditioning landslides on a regional scale. The database consists of Landsat-TM, stereoscopic MOMS-2P and radar (ERS-1/2) satellite imagery. MOMS-2P and ERS-1/2 data allowed the generation of high-resolution Digital Elevation Models (DEM). The derived relief parameters have been analysed in a GIS in combination with other information obtained from remote sensing data, thematic maps and field observation for a spatially differentiated…

The aim of the research was to monitor and assess landslide hazards by remote sensing data processing and GIS spatial analysis. The automatic classification of remote sensing images pro-vides many useful land use information to combine in a GIS environment with other spatial factors influencing the occurrence of landslide.
The upper part of Susa Valley, in the Italian Western Alps, was chosen as test area because of a large variety of remote sensing data available by ISPRS WG VIII/2 with the aim to exchange infor-mation and experience in the field of geomatic techniques.
It is well known that the occurrence of landslides is controlled by a lot of morphological, geological, and human factors. We have chosen, regarding the available data, the following factors: acclivity, aspect, lithology, land use and precipitations. We have built up a mathematical predictive model enabling ac-tual/potential unstable slopes. It is a linear model where the hazard score depends…

This study investigates and demonstrates the state of the art in remote sensing techniques for detailed landslide hazard assessment applicable to large areas. Since the most common methods of landslide hazard assessment using simple inventories and weighted overlays are heavily dependent on three-dimensional terrain visualization and analysis, stereo satellite images from the IKONOS Very High Resolution (VHR) sensor are used for this study. The DEMs created from IKONOS stereo images appear to be much more accurate and sensitive to micro-scale terrain features than a DEM created from digital contour data with a 2 m contour interval. Pan-sharpened stereo IKONOS images permit interpretation of recent landslides as small as 2–3 m in width as well as relict landslides older than 50 years. A cost–benefit analysis comparing stereo air photo interpretation with stereo satellite image interpretation suggests that stereo satellite imagery is usually more cost-…

Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIS-based weighted linear combination method. First, six relevant landslide-controlling factors are derived from geospatial remote sensing data and coded into a GIS system. Next, continuous susceptibility values from low to high are assigned to each of the six factors. Second, a continuous scale of a global landslide susceptibility index is derived using GIS weighted linear combination based on each factor’s relative significance to the process of landslide occurrence (e.g., slope is the most important factor, soil types and soil texture are also primary-level parameters, while elevation, land cover types, and drainage density are secondary in importance). Finally,…