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hazard zonation</title> <meta name="description" content="Search results for: landslide hazard zonation"> <meta name="keywords" content="landslide hazard zonation"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="landslide hazard zonation"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 728</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: landslide hazard zonation</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">728</span> Landslide Hazard Zonation and Risk Studies Using Multi-Criteria Decision-Making and Slope Stability Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ankit%20Tyagi">Ankit Tyagi</a>, <a href="https://publications.waset.org/abstracts/search?q=Reet%20Kamal%20Tiwari"> Reet Kamal Tiwari</a>, <a href="https://publications.waset.org/abstracts/search?q=Naveen%20James"> Naveen James</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In India, landslides are the most frequently occurring disaster in the regions of the Himalayas and the Western Ghats. The steep slopes and land use in these areas are quite apprehensive. In the recent past, many landslide hazard zonation (LHZ) works have been carried out in the Himalayas. However, the preparation of LHZ maps considering temporal factors such as seismic ground shaking, seismic amplification at surface level, and rainfall are limited. Hence this study presents a comprehensive use of the multi-criteria decision-making (MCDM) method in landslide risk assessment. In this research, we conducted both geospatial and geotechnical analysis to minimize the danger of landslides. Geospatial analysis is performed using high-resolution satellite data to produce landslide causative factors which were given weightage using the MCDM method. The geotechnical analysis includes a slope stability check, which was done to determine the potential landslide slope. The landslide risk map can provide useful information which helps people to understand the risk of living in an area. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landslide%20hazard%20zonation" title="landslide hazard zonation">landslide hazard zonation</a>, <a href="https://publications.waset.org/abstracts/search?q=PHA" title=" PHA"> PHA</a>, <a href="https://publications.waset.org/abstracts/search?q=AHP" title=" AHP"> AHP</a>, <a href="https://publications.waset.org/abstracts/search?q=GIS" title=" GIS"> GIS</a> </p> <a href="https://publications.waset.org/abstracts/117006/landslide-hazard-zonation-and-risk-studies-using-multi-criteria-decision-making-and-slope-stability-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/117006.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">192</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">727</span> Geospatial Multi-Criteria Evaluation to Predict Landslide Hazard Potential in the Catchment of Lake Naivasha, Kenya</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdel%20Rahman%20Khider%20Hassan">Abdel Rahman Khider Hassan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes a multi-criteria geospatial model for prediction of landslide hazard zonation (LHZ) for Lake Naivasha catchment (Kenya), based on spatial analysis of integrated datasets of location intrinsic parameters (slope stability factors) and external landslides triggering factors (natural and man-made factors). The intrinsic dataset included: lithology, geometry of slope (slope inclination, aspect, elevation, and curvature) and land use/land cover. The landslides triggering factors included: rainfall as the climatic factor, in addition to the destructive effects reflected by proximity of roads and drainage network to areas that are susceptible to landslides. No published study on landslides has been obtained for this area. Thus, digital datasets of the above spatial parameters were conveniently acquired, stored, manipulated and analyzed in a Geographical Information System (GIS) using a multi-criteria grid overlay technique (in ArcGIS 10.2.2 environment). Deduction of landslide hazard zonation is done by applying weights based on relative contribution of each parameter to the slope instability, and finally, the weighted parameters grids were overlaid together to generate a map of the potential landslide hazard zonation (LHZ) for the lake catchment. From the total surface of 3200 km² of the lake catchment, most of the region (78.7 %; 2518.4 km²) is susceptible to moderate landslide hazards, whilst about 13% (416 km²) is occurring under high hazards. Only 1.0% (32 km²) of the catchment is displaying very high landslide hazards, and the remaining area (7.3 %; 233.6 km²) displays low probability of landslide hazards. This result confirms the importance of steep slope angles, lithology, vegetation land cover and slope orientation (aspect) as the major determining factors of slope failures. The information provided by the produced map of landslide hazard zonation (LHZ) could lay the basis for decision making as well as mitigation and applications in avoiding potential losses caused by landslides in the Lake Naivasha catchment in the Kenya Highlands. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20making" title="decision making">decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=geospatial" title=" geospatial"> geospatial</a>, <a href="https://publications.waset.org/abstracts/search?q=landslide" title=" landslide"> landslide</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-criteria" title=" multi-criteria"> multi-criteria</a>, <a href="https://publications.waset.org/abstracts/search?q=Naivasha" title=" Naivasha"> Naivasha</a> </p> <a href="https://publications.waset.org/abstracts/80613/geospatial-multi-criteria-evaluation-to-predict-landslide-hazard-potential-in-the-catchment-of-lake-naivasha-kenya" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80613.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">206</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">726</span> Application and Verification of Regression Model to Landslide Susceptibility Mapping</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Masood%20Beheshtirad">Masood Beheshtirad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Identification of regions having potential for landslide occurrence is one of the basic measures in natural resources management. Different landslide hazard mapping models are proposed based on the environmental condition and goals. In this research landslide hazard map using multiple regression model were provided and applicability of this model is investigated in Baghdasht watershed. Dependent variable is landslide inventory map and independent variables consist of information layers as Geology, slope, aspect, distance from river, distance from road, fault and land use. For doing this, existing landslides have been identified and an inventory map made. The landslide hazard map is based on the multiple regression provided. The level of similarity potential hazard classes and figures of this model were compared with the landslide inventory map in the SPSS environments. Results of research showed that there is a significant correlation between the potential hazard classes and figures with area of the landslides. The multiple regression model is suitable for application in the Baghdasht Watershed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landslide" title="landslide">landslide</a>, <a href="https://publications.waset.org/abstracts/search?q=mapping" title=" mapping"> mapping</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20model" title=" multiple model"> multiple model</a>, <a href="https://publications.waset.org/abstracts/search?q=regression" title=" regression"> regression</a> </p> <a href="https://publications.waset.org/abstracts/25864/application-and-verification-of-regression-model-to-landslide-susceptibility-mapping" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25864.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">325</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">725</span> Landslide Hazard a Gigantic Problem in Indian Himalayan Region: Needs In-Depth Research to Minimize Disaster</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Varun%20Joshi">Varun Joshi</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20S.%20Rawat"> M. S. Rawat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Indian Himalayan Region (IHR) is inherently fragile and susceptible to landslide hazard due to its extremely weak geology, highly rugged topography and heavy monsoonal rainfall. One of the most common hazards in the IHR is landslide, and this event is particularly frequent in Himalayan states of India i.e. Jammu & Kashmir, Himachal Pradesh, Uttarakhand, Sikkim, Manipur and Arunachal Pradesh. Landslides are mostly triggered by extreme rainfall events but the incidence increases during monsoon months (June to September). Natural slopes which are otherwise stable but they get destabilized due to anthropogenic activities like construction of various developmental activities and deforestation. These activities are required to fulfill the developmental needs and upliftment of societal status in the region. Landslides also trigger during major earthquakes and reported most observable and damaging phenomena. Studies indicate that the landslide phenomenon has increased many folds due to developmental activities in Himalayan region. Gradually increasing and devastating consequences of landslides turned into one of the most important hydro-geological hazards in Himalayan states especially in Uttarakhand and Sikkim states of India. The recent most catastrophic rainfall in June 2013 in Uttarakhand lead to colossal loss of life and property. The societal damage due to this incident is still to be recovered even after three years. Sikkim earthquake of September 2011 is witnessed for triggering of large number of coseismic landslides. The rescue and relief team faced huge problem in helping the trapped villagers in remote locations of the state due to road side blockade by landslides. The recent past incidences of landslides in Uttarakhand, as well as Sikkim states, created a new domain of research in terms of understanding the phenomena of landslide and management of disaster in such situation. Every year at many locations landslides trigger which force dwellers to either evacuate their dwelling or lose their life and property. The communication and transportation networks are also severely affected by landslides at several locations. Many times the drinking water supply disturbed and shortage of daily need household items reported during monsoon months. To minimize the severity of landslide in IHR requires in-depth research and developmental planning. For most of the areas in the present study, landslide hazard zonation is done on 1:50,000 scale. The land use planning maps on extensive basis are not available. Therefore, there is a need of large-scale landslide hazard zonation and land use planning maps. If the scientist conduct research on desired aspects and their outcome of research is utilized by the government in developmental planning then the incidents of landslide could be minimized, subsequent impact on society, life and property would be reduced. Along with the scientific research, there is another need of awareness generation in the region for stake holders and local dwellers to combat with the landslide hazard, if triggered in their location. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=coseismic" title="coseismic">coseismic</a>, <a href="https://publications.waset.org/abstracts/search?q=Indian%20Himalayan%20Region" title=" Indian Himalayan Region"> Indian Himalayan Region</a>, <a href="https://publications.waset.org/abstracts/search?q=landslide%20hazard%20zonation" title=" landslide hazard zonation"> landslide hazard zonation</a>, <a href="https://publications.waset.org/abstracts/search?q=Sikkim" title=" Sikkim"> Sikkim</a>, <a href="https://publications.waset.org/abstracts/search?q=societal" title=" societal"> societal</a>, <a href="https://publications.waset.org/abstracts/search?q=Uttarakhand" title=" Uttarakhand"> Uttarakhand</a> </p> <a href="https://publications.waset.org/abstracts/63038/landslide-hazard-a-gigantic-problem-in-indian-himalayan-region-needs-in-depth-research-to-minimize-disaster" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63038.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">251</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">724</span> Landslide Hazard Zonation Using Satellite Remote Sensing and GIS Technology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ankit%20Tyagi">Ankit Tyagi</a>, <a href="https://publications.waset.org/abstracts/search?q=Reet%20Kamal%20Tiwari"> Reet Kamal Tiwari</a>, <a href="https://publications.waset.org/abstracts/search?q=Naveen%20James"> Naveen James</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=weighted%20overlay%20method" title="weighted overlay method">weighted overlay method</a>, <a href="https://publications.waset.org/abstracts/search?q=GIS" title=" GIS"> GIS</a>, <a href="https://publications.waset.org/abstracts/search?q=landslide%20hazard%20zonation" title=" landslide hazard zonation"> landslide hazard zonation</a>, <a href="https://publications.waset.org/abstracts/search?q=remote%20sensing" title=" remote sensing"> remote sensing</a> </p> <a href="https://publications.waset.org/abstracts/116966/landslide-hazard-zonation-using-satellite-remote-sensing-and-gis-technology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/116966.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">133</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">723</span> Site Investigations and Mitigation Measures of Landslides in Sainj and Tirthan Valley of Kullu District, Himachal Pradesh, India</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Laxmi%20Versain">Laxmi Versain</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20S.%20Banshtu"> R. S. Banshtu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Landslides are found to be the most commonly occurring geological hazards in the mountainous regions of the Himalaya. This mountainous zone is facing large number of seismic turbulences, climatic changes, and topography changes due to increasing urbanization. That eventually has lead several researchers working for best suitable methodologies to infer the ultimate results. Landslide Hazard Zonation has widely come as suitable method to know the appropriate factors that trigger the lansdslide phenomenon on higher reaches. Most vulnerable zones or zones of weaknesses are indentified and safe mitigation measures are to be suggested to mitigate and channelize the study of an effected area. Use of Landslide Hazard Zonation methodology in relative zones of weaknesses depend upon the data available for the particular site. The causative factors are identified and data is made available to infer the results. Factors like seismicity in mountainous region have closely associated to make the zones of thrust and faults or lineaments more vulnerable. Data related to soil, terrain, rainfall, geology, slope, nature of terrain, are found to be varied for various landforms and areas. Thus, the relative causes are to be identified and classified by giving specific weightage to each parameter. Factors which cause the instability of slopes are several and can be grouped to infer the potential modes of failure. The triggering factors of the landslides on the mountains are not uniform. The urbanization has crawled like ladder and emergence of concrete jungles are in a very fast pace on hilly region of Himalayas. The local terrains has largely been modified and hence instability of several zones are triggering at very fast pace. More strategic and pronounced methods are required to reduce the effect of landslide. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=zonation" title="zonation">zonation</a>, <a href="https://publications.waset.org/abstracts/search?q=LHZ" title=" LHZ"> LHZ</a>, <a href="https://publications.waset.org/abstracts/search?q=susceptible" title=" susceptible"> susceptible</a>, <a href="https://publications.waset.org/abstracts/search?q=weightages" title=" weightages"> weightages</a>, <a href="https://publications.waset.org/abstracts/search?q=methodology" title=" methodology"> methodology</a> </p> <a href="https://publications.waset.org/abstracts/52736/site-investigations-and-mitigation-measures-of-landslides-in-sainj-and-tirthan-valley-of-kullu-district-himachal-pradesh-india" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52736.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">196</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">722</span> Geological Structure as the Main Factor in Landslide Deployment in Purworejo District Central Java Province Indonesia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hilman%20Agil%20Satria">Hilman Agil Satria</a>, <a href="https://publications.waset.org/abstracts/search?q=Rezky%20Naufan%20Hendrawan"> Rezky Naufan Hendrawan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Indonesia is vulnerable to geological hazard because of its location in subduction zone and have tropical climate. Landslide is one of the most happened geological hazard in Indonesia, based on Indonesia Geospasial data, at least 194 landslides recorded in 2013. In fact, research location is placed as the third city that most happened landslide in Indonesia. Landslide caused damage of many houses and wrecked the road. The purpose of this research is to make a landslide zone therefore can be used as one of mitigation consideration. The location is in Bruno, Porworejo district Central Java Province Indonesia at 109.903 – 109.99 and -7.59 – -7.50 with 10 Km x 10 Km wide. Based on geological mapping result, the research location consist of Late Miocene sandstone and claystone, and Pleistocene volcanic breccia and tuff. Those landslide happened in the lithology that close with fault zone. This location has so many geological structures: joints, faults and folds. There are 3 thrust faults, 1 normal faults, 4 strike slip faults and 6 folds. This geological structure movement is interpreted as the main factor that has triggered landslide in this location. This research use field data as well as samples of rock, joint, slicken side and landslide location which is combined with DEM SRTM to analyze geomorphology. As the final result of combined data will be presented as geological map, geological structure map and landslide zone map. From this research we can assume that there is correlation between geological structure and landslide locations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=geological%20structure" title="geological structure">geological structure</a>, <a href="https://publications.waset.org/abstracts/search?q=landslide" title=" landslide"> landslide</a>, <a href="https://publications.waset.org/abstracts/search?q=Porworejo" title=" Porworejo"> Porworejo</a>, <a href="https://publications.waset.org/abstracts/search?q=Indonesia" title=" Indonesia "> Indonesia </a> </p> <a href="https://publications.waset.org/abstracts/1960/geological-structure-as-the-main-factor-in-landslide-deployment-in-purworejo-district-central-java-province-indonesia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1960.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">286</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">721</span> Exploring the Capabilities of Sentinel-1A and Sentinel-2A Data for Landslide Mapping</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ismayanti%20Magfirah">Ismayanti Magfirah</a>, <a href="https://publications.waset.org/abstracts/search?q=Sartohadi%20Junun"> Sartohadi Junun</a>, <a href="https://publications.waset.org/abstracts/search?q=Samodra%20Guruh"> Samodra Guruh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Landslides are one of the most frequent and devastating natural disasters in Indonesia. Many studies have been conducted regarding this phenomenon. However, there is a lack of attention in the landslide inventory mapping. The natural condition (dense forest area) and the limited human and economic resources are some of the major problems in building landslide inventory in Indonesia. Considering the importance of landslide inventory data in susceptibility, hazard, and risk analysis, it is essential to generate landslide inventory based on available resources. In order to achieve this, the first thing we have to do is identify the landslides' location. The presence of Sentinel-1A and Sentinel-2A data gives new insights into land monitoring investigation. The free access, high spatial resolution, and short revisit time, make the data become one of the most trending open sources data used in landslide mapping. Sentinel-1A and Sentinel-2A data have been used broadly for landslide detection and landuse/landcover mapping. This study aims to generate landslide map by integrating Sentinel-1A and Sentinel-2A data use change detection method. The result will be validated by field investigation to make preliminary landslide inventory in the study area. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=change%20detection%20method" title="change detection method">change detection method</a>, <a href="https://publications.waset.org/abstracts/search?q=landslide%20inventory%20mapping" title=" landslide inventory mapping"> landslide inventory mapping</a>, <a href="https://publications.waset.org/abstracts/search?q=Sentinel-1A" title=" Sentinel-1A"> Sentinel-1A</a>, <a href="https://publications.waset.org/abstracts/search?q=Sentinel-2A" title=" Sentinel-2A"> Sentinel-2A</a> </p> <a href="https://publications.waset.org/abstracts/94105/exploring-the-capabilities-of-sentinel-1a-and-sentinel-2a-data-for-landslide-mapping" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94105.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">171</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">720</span> Automated Natural Hazard Zonation System with Internet-SMS Warning: Distributed GIS for Sustainable Societies Creating Schema and Interface for Mapping and Communication</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Devanjan%20Bhattacharya">Devanjan Bhattacharya</a>, <a href="https://publications.waset.org/abstracts/search?q=Jitka%20Komarkova"> Jitka Komarkova</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The research describes the implementation of a novel and stand-alone system for dynamic hazard warning. The system uses all existing infrastructure already in place like mobile networks, a laptop/PC and the small installation software. The geospatial dataset are the maps of a region which are again frugal. Hence there is no need to invest and it reaches everyone with a mobile. A novel architecture of hazard assessment and warning introduced where major technologies in ICT interfaced to give a unique WebGIS based dynamic real time geohazard warning communication system. A never before architecture introduced for integrating WebGIS with telecommunication technology. Existing technologies interfaced in a novel architectural design to address a neglected domain in a way never done before–through dynamically updatable WebGIS based warning communication. The work publishes new architecture and novelty in addressing hazard warning techniques in sustainable way and user friendly manner. Coupling of hazard zonation and hazard warning procedures into a single system has been shown. Generalized architecture for deciphering a range of geo-hazards has been developed. Hence the developmental work presented here can be summarized as the development of internet-SMS based automated geo-hazard warning communication system; integrating a warning communication system with a hazard evaluation system; interfacing different open-source technologies towards design and development of a warning system; modularization of different technologies towards development of a warning communication system; automated data creation, transformation and dissemination over different interfaces. The architecture of the developed warning system has been functionally automated as well as generalized enough that can be used for any hazard and setup requirement has been kept to a minimum. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=geospatial" title="geospatial">geospatial</a>, <a href="https://publications.waset.org/abstracts/search?q=web-based%20GIS" title=" web-based GIS"> web-based GIS</a>, <a href="https://publications.waset.org/abstracts/search?q=geohazard" title=" geohazard"> geohazard</a>, <a href="https://publications.waset.org/abstracts/search?q=warning%20system" title=" warning system"> warning system</a> </p> <a href="https://publications.waset.org/abstracts/5232/automated-natural-hazard-zonation-system-with-internet-sms-warning-distributed-gis-for-sustainable-societies-creating-schema-and-interface-for-mapping-and-communication" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5232.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">408</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">719</span> Climate Change and Landslide Risk Assessment in Thailand</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shotiros%20Protong">Shotiros Protong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The incidents of sudden landslides in Thailand during the past decade have occurred frequently and more severely. It is necessary to focus on the principal parameters used for analysis such as land cover land use, rainfall values, characteristic of soil and digital elevation model (DEM). The combination of intense rainfall and severe monsoons is increasing due to global climate change. Landslide occurrences rapidly increase during intense rainfall especially in the rainy season in Thailand which usually starts around mid-May and ends in the middle of October. The rain-triggered landslide hazard analysis is the focus of this research. The combination of geotechnical and hydrological data are used to determine permeability, conductivity, bedding orientation, overburden and presence of loose blocks. The regional landslide hazard mapping is developed using the Slope Stability Index SINMAP model supported on Arc GIS software version 10.1. Geological and land use data are used to define the probability of landslide occurrences in terms of geotechnical data. The geological data can indicate the shear strength and the angle of friction values for soils above given rock types, which leads to the general applicability of the approach for landslide hazard analysis. To address the research objectives, the methods are described in this study: setup and calibration of the SINMAP model, sensitivity of the SINMAP model, geotechnical laboratory, landslide assessment at present calibration and landslide assessment under future climate simulation scenario A2 and B2. In terms of hydrological data, the millimetres/twenty-four hours of average rainfall data are used to assess the rain triggered landslide hazard analysis in slope stability mapping. During 1954-2012 period, is used for the baseline of rainfall data at the present calibration. The climate change in Thailand, the future of climate scenarios are simulated by spatial and temporal scales. The precipitation impact is need to predict for the climate future, Statistical Downscaling Model (SDSM) version 4.2, is used to assess the simulation scenario of future change between latitude 16o 26’ and 18o 37’ north and between longitude 98o 52’ and 103o 05’ east by SDSM software. The research allows the mapping of risk parameters for landslide dynamics, and indicates the spatial and time trends of landslide occurrences. Thus, regional landslide hazard mapping under present-day climatic conditions from 1954 to 2012 and simulations of climate change based on GCM scenarios A2 and B2 from 2013 to 2099 related to the threshold rainfall values for the selected the study area in Uttaradit province in the northern part of Thailand. Finally, the landslide hazard mapping will be compared and shown by areas (km2 ) in both the present and the future under climate simulation scenarios A2 and B2 in Uttaradit province. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landslide%20hazard" title="landslide hazard">landslide hazard</a>, <a href="https://publications.waset.org/abstracts/search?q=GIS" title=" GIS"> GIS</a>, <a href="https://publications.waset.org/abstracts/search?q=slope%20stability%20index%20%28SINMAP%29" title=" slope stability index (SINMAP)"> slope stability index (SINMAP)</a>, <a href="https://publications.waset.org/abstracts/search?q=landslides" title=" landslides"> landslides</a>, <a href="https://publications.waset.org/abstracts/search?q=Thailand" title=" Thailand"> Thailand</a> </p> <a href="https://publications.waset.org/abstracts/26989/climate-change-and-landslide-risk-assessment-in-thailand" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26989.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">564</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">718</span> Assessing Social Vulnerability and Policy Adaption Application Responses Based on Landslide Risk Map</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Z.%20A.%20Ahmad">Z. A. Ahmad</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20C.%20Omar"> R. C. Omar</a>, <a href="https://publications.waset.org/abstracts/search?q=I.%20Z.%20Baharuddin"> I. Z. Baharuddin</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Roslan"> R. Roslan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Assessments of social vulnerability, carried out holistically, can provide an important guide to the planning process and to decisions on resource allocation at various levels, and can help to raise public awareness of geo-hazard risks. The assessments can help to provide answers for basic questions such as the human vulnerability at the geo-hazard prone or disaster areas causing health damage, economic loss, loss of natural heritage and vulnerability impact of extreme natural hazard event. To overcome these issues, integrated framework for assessing the increasing human vulnerability to environmental changes caused by geo-hazards will be introduced using an indicator from landslide risk map that is related to agent based modeling platform. The indicators represent the underlying factors, which influence a community’s ability to deal with and recover from the damage associated with geo-hazards. Scope of this paper is particularly limited to landslides. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=social" title="social">social</a>, <a href="https://publications.waset.org/abstracts/search?q=vulnerability" title=" vulnerability"> vulnerability</a>, <a href="https://publications.waset.org/abstracts/search?q=geo-hazard" title=" geo-hazard"> geo-hazard</a>, <a href="https://publications.waset.org/abstracts/search?q=methodology" title=" methodology"> methodology</a>, <a href="https://publications.waset.org/abstracts/search?q=indicators" title=" indicators"> indicators</a> </p> <a href="https://publications.waset.org/abstracts/7512/assessing-social-vulnerability-and-policy-adaption-application-responses-based-on-landslide-risk-map" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7512.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">285</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">717</span> GIS and Remote Sensing Approach in Earthquake Hazard Assessment and Monitoring: A Case Study in the Momase Region of Papua New Guinea</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tingneyuc%20Sekac">Tingneyuc Sekac</a>, <a href="https://publications.waset.org/abstracts/search?q=Sujoy%20Kumar%20Jana"> Sujoy Kumar Jana</a>, <a href="https://publications.waset.org/abstracts/search?q=Indrajit%20Pal"> Indrajit Pal</a>, <a href="https://publications.waset.org/abstracts/search?q=Dilip%20Kumar%20Pal"> Dilip Kumar Pal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Tectonism induced Tsunami, landslide, ground shaking leading to liquefaction, infrastructure collapse, conflagration are the common earthquake hazards that are experienced worldwide. Apart from human casualty, the damage to built-up infrastructures like roads, bridges, buildings and other properties are the collateral episodes. The appropriate planning must precede with a view to safeguarding people’s welfare, infrastructures and other properties at a site based on proper evaluation and assessments of the potential level of earthquake hazard. The information or output results can be used as a tool that can assist in minimizing risk from earthquakes and also can foster appropriate construction design and formulation of building codes at a particular site. Different disciplines adopt different approaches in assessing and monitoring earthquake hazard throughout the world. For the present study, GIS and Remote Sensing potentials were utilized to evaluate and assess earthquake hazards of the study region. Subsurface geology and geomorphology were the common features or factors that were assessed and integrated within GIS environment coupling with seismicity data layers like; Peak Ground Acceleration (PGA), historical earthquake magnitude and earthquake depth to evaluate and prepare liquefaction potential zones (LPZ) culminating in earthquake hazard zonation of our study sites. The liquefaction can eventuate in the aftermath of severe ground shaking with amenable site soil condition, geology and geomorphology. The latter site conditions or the wave propagation media were assessed to identify the potential zones. The precept has been that during any earthquake event the seismic wave is generated and propagates from earthquake focus to the surface. As it propagates, it passes through certain geological or geomorphological and specific soil features, where these features according to their strength/stiffness/moisture content, aggravates or attenuates the strength of wave propagation to the surface. Accordingly, the resulting intensity of shaking may or may not culminate in the collapse of built-up infrastructures. For the case of earthquake hazard zonation, the overall assessment was carried out through integrating seismicity data layers with LPZ. Multi-criteria Evaluation (MCE) with Saaty’s Analytical Hierarchy Process (AHP) was adopted for this study. It is a GIS technology that involves integration of several factors (thematic layers) that can have a potential contribution to liquefaction triggered by earthquake hazard. The factors are to be weighted and ranked in the order of their contribution to earthquake induced liquefaction. The weightage and ranking assigned to each factor are to be normalized with AHP technique. The spatial analysis tools i.e., Raster calculator, reclassify, overlay analysis in ArcGIS 10 software were mainly employed in the study. The final output of LPZ and Earthquake hazard zones were reclassified to ‘Very high’, ‘High’, ‘Moderate’, ‘Low’ and ‘Very Low’ to indicate levels of hazard within a study region. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hazard%20micro-zonation" title="hazard micro-zonation">hazard micro-zonation</a>, <a href="https://publications.waset.org/abstracts/search?q=liquefaction" title=" liquefaction"> liquefaction</a>, <a href="https://publications.waset.org/abstracts/search?q=multi%20criteria%20evaluation" title=" multi criteria evaluation"> multi criteria evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=tectonism" title=" tectonism"> tectonism</a> </p> <a href="https://publications.waset.org/abstracts/57539/gis-and-remote-sensing-approach-in-earthquake-hazard-assessment-and-monitoring-a-case-study-in-the-momase-region-of-papua-new-guinea" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57539.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">266</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">716</span> Instability Index Method and Logistic Regression to Assess Landslide Susceptibility in County Route 89, Taiwan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Y.%20H.%20Wu">Y. H. Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Ji-Yuan%20Lin"> Ji-Yuan Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Yu-Ming%20Liou"> Yu-Ming Liou </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study aims to set up the landslide susceptibility map of County Route 89 at Ren-Ai Township in Nantou County using the Instability Index Method and Logistic regression. Seven susceptibility factors including Slope Angle, Aspect, Elevation, Distance to fold, Distance to River, Distance to Road and Accumulated Rainfall were obtained by GIS based on the Typhoon Toraji landslide area identified by Industrial Technology Research Institute in 2001. To calculate the landslide percentage of each factor and acquire the weight and grade the grid by means of Instability Index Method. In this study, landslide susceptibility can be classified into four grades: high, medium high, medium low and low, in order to determine the advantages and disadvantages of the two models. The precision of this model is verified by classification error matrix and SRC curve. These results suggest that the logistic regression model is a preferred method than instability index in the assessment of landslide susceptibility. It is suitable for the landslide prediction and precaution in this area in the future. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=instability%20index%20method" title="instability index method">instability index method</a>, <a href="https://publications.waset.org/abstracts/search?q=logistic%20regression" title=" logistic regression"> logistic regression</a>, <a href="https://publications.waset.org/abstracts/search?q=landslide%20susceptibility" title=" landslide susceptibility"> landslide susceptibility</a>, <a href="https://publications.waset.org/abstracts/search?q=SRC%20curve" title=" SRC curve"> SRC curve</a> </p> <a href="https://publications.waset.org/abstracts/46070/instability-index-method-and-logistic-regression-to-assess-landslide-susceptibility-in-county-route-89-taiwan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46070.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">292</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">715</span> Seismic Microzonation of El-Fayoum New City, Egypt</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Suzan%20Salem">Suzan Salem</a>, <a href="https://publications.waset.org/abstracts/search?q=Heba%20Moustafa"> Heba Moustafa</a>, <a href="https://publications.waset.org/abstracts/search?q=Abd%20El-Aziz%20Abd%20El-Aal"> Abd El-Aziz Abd El-Aal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Seismic micro hazard zonation for urban areas is the first step towards a seismic risk analysis and mitigation strategy. Essential here is to obtain a proper understanding of the local subsurface conditions and to evaluate ground-shaking effects. In the present study, an attempt has been made to evaluate the seismic hazard considering local site effects by carrying out detailed geotechnical and geophysical site characterization in El-Fayoum New City. Seismic hazard analysis and microzonation of El-Fayoum New City are addressed in three parts: in the first part, estimation of seismic hazard is done using seismotectonic and geological information. The second part deals with site characterization using geotechnical and shallow geophysical techniques. In the last part, local site effects are assessed by carrying out one-dimensional (1-D) ground response analysis using the equivalent linear method by program SHAKE 2000. Finally, microzonation maps have been prepared. The detailed methodology, along with experimental details, collected data, results and maps are presented in this paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=El-Fayoum" title="El-Fayoum">El-Fayoum</a>, <a href="https://publications.waset.org/abstracts/search?q=microzonation" title=" microzonation"> microzonation</a>, <a href="https://publications.waset.org/abstracts/search?q=seismotectonic" title=" seismotectonic"> seismotectonic</a>, <a href="https://publications.waset.org/abstracts/search?q=Egypt" title=" Egypt"> Egypt</a> </p> <a href="https://publications.waset.org/abstracts/39788/seismic-microzonation-of-el-fayoum-new-city-egypt" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39788.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">381</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">714</span> Slope Stability and Landslides Hazard Analysis, Limitations of Existing Approaches, and a New Direction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alisawi%20Alaa%20T.">Alisawi Alaa T.</a>, <a href="https://publications.waset.org/abstracts/search?q=Collins%20P.%20E.%20F."> Collins P. E. F.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The analysis and evaluation of slope stability and landslide hazards are landslide hazards are critically important in civil engineering projects and broader considerations of safety. The level of slope stability risk should be identified due to its significant and direct financial and safety effects. Slope stability hazard analysis is performed considering static and/or dynamic loading circumstances. To reduce and/or prevent the failure hazard caused by landslides, a sophisticated and practical hazard analysis method using advanced constitutive modeling should be developed and linked to an effective solution that corresponds to the specific type of slope stability and landslides failure risk. Previous studies on slope stability analysis methods identify the failure mechanism and its corresponding solution. The commonly used approaches include used approaches include limit equilibrium methods, empirical approaches for rock slopes (e.g., slope mass rating and Q-slope), finite element or finite difference methods, and district element codes. This study presents an overview and evaluation of these analysis techniques. Contemporary source materials are used to examine these various methods on the basis of hypotheses, the factor of safety estimation, soil types, load conditions, and analysis conditions and limitations. Limit equilibrium methods play a key role in assessing the level of slope stability hazard. The slope stability safety level can be defined by identifying the equilibrium of the shear stress and shear strength. The slope is considered stable when the movement resistance forces are greater than those that drive the movement with a factor of safety (ratio of the resistance of the resistance of the driving forces) that is greater than 1.00. However, popular and practical methods, including limit equilibrium approaches, are not effective when the slope experiences complex failure mechanisms, such as progressive failure, liquefaction, internal deformation, or creep. The present study represents the first episode of an ongoing project that involves the identification of the types of landslides hazards, assessment of the level of slope stability hazard, development of a sophisticated and practical hazard analysis method, linkage of the failure type of specific landslides conditions to the appropriate solution and application of an advanced computational method for mapping the slope stability properties in the United Kingdom, and elsewhere through geographical information system (GIS) and inverse distance weighted spatial interpolation(IDW) technique. This study investigates and assesses the different assesses the different analysis and solution techniques to enhance the knowledge on the mechanism of slope stability and landslides hazard analysis and determine the available solutions for each potential landslide failure risk. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=slope%20stability" title="slope stability">slope stability</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20element%20analysis" title=" finite element analysis"> finite element analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=hazard%20analysis" title=" hazard analysis"> hazard analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=landslides%20hazard" title=" landslides hazard"> landslides hazard</a> </p> <a href="https://publications.waset.org/abstracts/154977/slope-stability-and-landslides-hazard-analysis-limitations-of-existing-approaches-and-a-new-direction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/154977.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">100</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">713</span> Artificial Neural Networks and Hidden Markov Model in Landslides Prediction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=C.%20S.%20Subhashini">C. S. Subhashini</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20L.%20Premaratne"> H. L. Premaratne </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Landslides are the most recurrent and prominent disaster in Sri Lanka. Sri Lanka has been subjected to a number of extreme landslide disasters that resulted in a significant loss of life, material damage, and distress. It is required to explore a solution towards preparedness and mitigation to reduce recurrent losses associated with landslides. Artificial Neural Networks (ANNs) and Hidden Markov Model (HMMs) are now widely used in many computer applications spanning multiple domains. This research examines the effectiveness of using Artificial Neural Networks and Hidden Markov Model in landslides predictions and the possibility of applying the modern technology to predict landslides in a prominent geographical area in Sri Lanka. A thorough survey was conducted with the participation of resource persons from several national universities in Sri Lanka to identify and rank the influencing factors for landslides. A landslide database was created using existing topographic; soil, drainage, land cover maps and historical data. The landslide related factors which include external factors (Rainfall and Number of Previous Occurrences) and internal factors (Soil Material, Geology, Land Use, Curvature, Soil Texture, Slope, Aspect, Soil Drainage, and Soil Effective Thickness) are extracted from the landslide database. These factors are used to recognize the possibility to occur landslides by using an ANN and HMM. The model acquires the relationship between the factors of landslide and its hazard index during the training session. These models with landslide related factors as the inputs will be trained to predict three classes namely, ‘landslide occurs’, ‘landslide does not occur’ and ‘landslide likely to occur’. Once trained, the models will be able to predict the most likely class for the prevailing data. Finally compared two models with regards to prediction accuracy, False Acceptance Rates and False Rejection rates and This research indicates that the Artificial Neural Network could be used as a strong decision support system to predict landslides efficiently and effectively than Hidden Markov Model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landslides" title="landslides">landslides</a>, <a href="https://publications.waset.org/abstracts/search?q=influencing%20factors" title=" influencing factors"> influencing factors</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network%20model" title=" neural network model"> neural network model</a>, <a href="https://publications.waset.org/abstracts/search?q=hidden%20markov%20model" title=" hidden markov model"> hidden markov model</a> </p> <a href="https://publications.waset.org/abstracts/21014/artificial-neural-networks-and-hidden-markov-model-in-landslides-prediction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21014.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">384</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">712</span> Analysis and Prediction of the Behavior of the Landslide at Ain El Hammam, Algeria Based on the Second Order Work Criterion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zerarka%20Hizia">Zerarka Hizia</a>, <a href="https://publications.waset.org/abstracts/search?q=Akchiche%20Mustapha"> Akchiche Mustapha</a>, <a href="https://publications.waset.org/abstracts/search?q=Prunier%20Florent"> Prunier Florent</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The landslide of Ain El Hammam (AEH) is characterized by a complex geology and a high hydrogeology hazard. AEH's perpetual reactivation compels us to look closely at its triggers and to better understand the mechanisms of its evolution in mass and in depth. This study builds a numerical model to simulate the influencing factors such as precipitation, non-saturation, and pore pressure fluctuations, using Plaxis software. For a finer analysis of instabilities, we use Hill's criterion, based on the sign of the second order work, which is the most appropriate material stability criterion for non-associated elastoplastic materials. The results of this type of calculation allow us, in theory, to predict the shape and position of the slip surface(s) which are liable to ground movements of the slope, before reaching the rupture given by the plastic limit of Mohr Coulomb. To validate the numerical model, an analysis of inclinometer measures is performed to confirm the direction of movement and kinematic of the sliding mechanism of AEH’s slope. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landslide" title="landslide">landslide</a>, <a href="https://publications.waset.org/abstracts/search?q=second%20order%20work" title=" second order work"> second order work</a>, <a href="https://publications.waset.org/abstracts/search?q=precipitation" title=" precipitation"> precipitation</a>, <a href="https://publications.waset.org/abstracts/search?q=inclinometers" title=" inclinometers"> inclinometers</a> </p> <a href="https://publications.waset.org/abstracts/84706/analysis-and-prediction-of-the-behavior-of-the-landslide-at-ain-el-hammam-algeria-based-on-the-second-order-work-criterion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84706.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">179</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">711</span> Comparing Stability Index MAPping (SINMAP) Landslide Susceptibility Models in the Río La Carbonera, Southeast Flank of Pico de Orizaba Volcano, Mexico</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gabriel%20Legorreta%20Paulin">Gabriel Legorreta Paulin</a>, <a href="https://publications.waset.org/abstracts/search?q=Marcus%20I.%20Bursik"> Marcus I. Bursik</a>, <a href="https://publications.waset.org/abstracts/search?q=Lilia%20Arana%20Salinas"> Lilia Arana Salinas</a>, <a href="https://publications.waset.org/abstracts/search?q=Fernando%20Aceves%20Quesada"> Fernando Aceves Quesada</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In volcanic environments, landslides and debris flows occur continually along stream systems of large stratovolcanoes. This is the case on Pico de Orizaba volcano, the highest mountain in Mexico. The volcano has a great potential to impact and damage human settlements and economic activities by landslides. People living along the lower valleys of Pico de Orizaba volcano are in continuous hazard by the coalescence of upstream landslide sediments that increased the destructive power of debris flows. These debris flows not only produce floods, but also cause the loss of lives and property. Although the importance of assessing such process, there is few landslide inventory maps and landslide susceptibility assessment. As a result in México, no landslide susceptibility models assessment has been conducted to evaluate advantage and disadvantage of models. In this study, a comprehensive study of landslide susceptibility models assessment using GIS technology is carried out on the SE flank of Pico de Orizaba volcano. A detailed multi-temporal landslide inventory map in the watershed is used as framework for the quantitative comparison of two landslide susceptibility maps. The maps are created based on 1) the Stability Index MAPping (SINMAP) model by using default geotechnical parameters and 2) by using findings of volcanic soils geotechnical proprieties obtained in the field. SINMAP combines the factor of safety derived from the infinite slope stability model with the theory of a hydrologic model to produce the susceptibility map. It has been claimed that SINMAP analysis is reasonably successful in defining areas that intuitively appear to be susceptible to landsliding in regions with sparse information. The validations of the resulting susceptibility maps are performed by comparing them with the inventory map under LOGISNET system which provides tools to compare by using a histogram and a contingency table. Results of the experiment allow for establishing how the individual models predict the landslide location, advantages, and limitations. The results also show that although the model tends to improve with the use of calibrated field data, the landslide susceptibility map does not perfectly represent existing landslides. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=GIS" title="GIS">GIS</a>, <a href="https://publications.waset.org/abstracts/search?q=landslide" title=" landslide"> landslide</a>, <a href="https://publications.waset.org/abstracts/search?q=modeling" title=" modeling"> modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=LOGISNET" title=" LOGISNET"> LOGISNET</a>, <a href="https://publications.waset.org/abstracts/search?q=SINMAP" title=" SINMAP"> SINMAP</a> </p> <a href="https://publications.waset.org/abstracts/62772/comparing-stability-index-mapping-sinmap-landslide-susceptibility-models-in-the-rio-la-carbonera-southeast-flank-of-pico-de-orizaba-volcano-mexico" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62772.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">313</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">710</span> Establishment of Landslide Warning System Using Surface or Sub-Surface Sensors Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Neetu%20Tyagi">Neetu Tyagi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sumit%20Sharma"> Sumit Sharma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study illustrates the results of an integrated study done on Tangni landslide located on NH-58 at Chamoli, Uttarakhand. Geological, geo-morphological and geotechnical investigations were carried out to understand the mechanism of landslide and to plan further investigation and monitoring. At any rate, the movements were favored by continuous rainfall water infiltration from the zones where the phyllites/slates and Dolomites outcrop. The site investigations were carried out including the monitoring of landslide movements and of the water level fluctuations due to rainfall give us a better understanding of landslide dynamics that have been causing in time soil instability at Tangni landslide site. The Early Warning System (EWS) installed different types of sensors and all sensors were directly connected to data logger and raw data transfer to the Defence Terrain Research Laboratory (DTRL) server room with the help of File Transfer Protocol (FTP). The slip surfaces were found at depths ranging from 8 to 10 m from Geophysical survey and hence sensors were installed to the depth of 15m at various locations of landslide. Rainfall is the main triggering factor of landslide. In this study, the developed model of unsaturated soil slope stability is carried out. The analysis of sensors data available for one year, indicated the sliding surface of landslide at depth between 6 to 12m with total displacement up to 6cm per year recorded at the body of landslide. The aim of this study is to set the threshold and generate early warning. Local peoples already alert towards landslide, if they have any types of warning system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=early%20warning%20system" title="early warning system">early warning system</a>, <a href="https://publications.waset.org/abstracts/search?q=file%20transfer%20protocol" title=" file transfer protocol"> file transfer protocol</a>, <a href="https://publications.waset.org/abstracts/search?q=geo-morphological" title=" geo-morphological"> geo-morphological</a>, <a href="https://publications.waset.org/abstracts/search?q=geotechnical" title=" geotechnical"> geotechnical</a>, <a href="https://publications.waset.org/abstracts/search?q=landslide" title=" landslide"> landslide</a> </p> <a href="https://publications.waset.org/abstracts/99668/establishment-of-landslide-warning-system-using-surface-or-sub-surface-sensors-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99668.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">158</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">709</span> Different Data-Driven Bivariate Statistical Approaches to Landslide Susceptibility Mapping (Uzundere, Erzurum, Turkey)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Azimollah%20Aleshzadeh">Azimollah Aleshzadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Enver%20Vural%20Yavuz"> Enver Vural Yavuz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=entropy%20weight%20method" title="entropy weight method">entropy weight method</a>, <a href="https://publications.waset.org/abstracts/search?q=evidence%20belief%20function" title=" evidence belief function"> evidence belief function</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20content%20model" title=" information content model"> information content model</a>, <a href="https://publications.waset.org/abstracts/search?q=landslide%20susceptibility%20mapping" title=" landslide susceptibility mapping"> landslide susceptibility mapping</a> </p> <a href="https://publications.waset.org/abstracts/125567/different-data-driven-bivariate-statistical-approaches-to-landslide-susceptibility-mapping-uzundere-erzurum-turkey" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/125567.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">132</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">708</span> Landslide Vulnerability Assessment in Context with Indian Himalayan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Neha%20Gupta">Neha Gupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Landslide vulnerability is considered as the crucial parameter for the assessment of landslide risk. The term vulnerability defined as the damage or degree of elements at risk of different dimensions, i.e., physical, social, economic, and environmental dimensions. Himalaya region is very prone to multi-hazard such as floods, forest fires, earthquakes, and landslides. With the increases in fatalities rates, loss of infrastructure, and economy due to landslide in the Himalaya region, leads to the assessment of vulnerability. In this study, a methodology to measure the combination of vulnerability dimension, i.e., social vulnerability, physical vulnerability, and environmental vulnerability in one framework. A combined result of these vulnerabilities has rarely been carried out. But no such approach was applied in the Indian Scenario. The methodology was applied in an area of east Sikkim Himalaya, India. The physical vulnerability comprises of building footprint layer extracted from remote sensing data and Google Earth imaginary. The social vulnerability was assessed by using population density based on land use. The land use map was derived from a high-resolution satellite image, and for environment vulnerability assessment NDVI, forest, agriculture land, distance from the river were assessed from remote sensing and DEM. The classes of social vulnerability, physical vulnerability, and environment vulnerability were normalized at the scale of 0 (no loss) to 1 (loss) to get the homogenous dataset. Then the Multi-Criteria Analysis (MCA) was used to assign individual weights to each dimension and then integrate it into one frame. The final vulnerability was further classified into four classes from very low to very high. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landslide" title="landslide">landslide</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-criteria%20analysis" title=" multi-criteria analysis"> multi-criteria analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=MCA" title=" MCA"> MCA</a>, <a href="https://publications.waset.org/abstracts/search?q=physical%20vulnerability" title=" physical vulnerability"> physical vulnerability</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20vulnerability" title=" social vulnerability"> social vulnerability</a> </p> <a href="https://publications.waset.org/abstracts/128930/landslide-vulnerability-assessment-in-context-with-indian-himalayan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/128930.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">301</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">707</span> Developing Improvements to Multi-Hazard Risk Assessments</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Fathianpour">A. Fathianpour</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20B.%20Jelodar"> M. B. Jelodar</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Wilkinson"> S. Wilkinson</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper outlines the approaches taken to assess multi-hazard assessments. There is currently confusion in assessing multi-hazard impacts, and so this study aims to determine which of the available options are the most useful. The paper uses an international literature search, and analysis of current multi-hazard assessments and a case study to illustrate the effectiveness of the chosen method. Findings from this study will help those wanting to assess multi-hazards to undertake a straightforward approach. The paper is significant as it helps to interpret the various approaches and concludes with the preferred method. Many people in the world live in hazardous environments and are susceptible to disasters. Unfortunately, when a disaster strikes it is often compounded by additional cascading hazards, thus people would confront more than one hazard simultaneously. Hazards include natural hazards (earthquakes, floods, etc.) or cascading human-made hazards (for example, Natural Hazard Triggering Technological disasters (Natech) such as fire, explosion, toxic release). Multi-hazards have a more destructive impact on urban areas than one hazard alone. In addition, climate change is creating links between different disasters such as causing landslide dams and debris flows leading to more destructive incidents. Much of the prevailing literature deals with only one hazard at a time. However, recently sophisticated multi-hazard assessments have started to appear. Given that multi-hazards occur, it is essential to take multi-hazard risk assessment under consideration. This paper aims to review the multi-hazard assessment methods through articles published to date and categorize the strengths and disadvantages of using these methods in risk assessment. Napier City is selected as a case study to demonstrate the necessity of using multi-hazard risk assessments. In order to assess multi-hazard risk assessments, first, the current multi-hazard risk assessment methods were described. Next, the drawbacks of these multi-hazard risk assessments were outlined. Finally, the improvements to current multi-hazard risk assessments to date were summarised. Generally, the main problem of multi-hazard risk assessment is to make a valid assumption of risk from the interactions of different hazards. Currently, risk assessment studies have started to assess multi-hazard situations, but drawbacks such as uncertainty and lack of data show the necessity for more precise risk assessment. It should be noted that ignoring or partial considering multi-hazards in risk assessment will lead to an overestimate or overlook in resilient and recovery action managements. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cascading%20hazards" title="cascading hazards">cascading hazards</a>, <a href="https://publications.waset.org/abstracts/search?q=disaster%20assessment" title=" disaster assessment"> disaster assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=mullti-hazards" title=" mullti-hazards"> mullti-hazards</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20assessment" title=" risk assessment"> risk assessment</a> </p> <a href="https://publications.waset.org/abstracts/115603/developing-improvements-to-multi-hazard-risk-assessments" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/115603.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">112</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">706</span> Damage Assessment Based on Full-Polarimetric Decompositions in the 2017 Colombia Landslide</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hyeongju%20Jeon">Hyeongju Jeon</a>, <a href="https://publications.waset.org/abstracts/search?q=Yonghyun%20Kim"> Yonghyun Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Yongil%20Kim"> Yongil Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Synthetic Aperture Radar (SAR) is an effective tool for damage assessment induced by disasters due to its all-weather and night/day acquisition capability. In this paper, the 2017 Colombia landslide was observed using full-polarimetric ALOS/PALSAR-2 data. Polarimetric decompositions, including the Freeman-Durden decomposition and the Cloude decomposition, are utilized to analyze the scattering mechanisms changes before and after-landslide. These analyses are used to detect the damaged areas induced by the landslide. Experimental results validate the efficiency of the full polarimetric SAR data since the damaged areas can be well discriminated. Thus, we can conclude the proposed method using full polarimetric data has great potential for damage assessment of landslides. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Synthetic%20Aperture%20Radar%20%28SAR%29" title="Synthetic Aperture Radar (SAR)">Synthetic Aperture Radar (SAR)</a>, <a href="https://publications.waset.org/abstracts/search?q=polarimetric%20decomposition" title=" polarimetric decomposition"> polarimetric decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=damage%20assessment" title=" damage assessment"> damage assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=landslide" title=" landslide"> landslide</a> </p> <a href="https://publications.waset.org/abstracts/77442/damage-assessment-based-on-full-polarimetric-decompositions-in-the-2017-colombia-landslide" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77442.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">390</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">705</span> Elasto-Viscoplastic Constitutive Modelling of Slow-Moving Landslides</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Deepak%20Raj%20Bhat">Deepak Raj Bhat</a>, <a href="https://publications.waset.org/abstracts/search?q=Kazushige%20Hayashi"> Kazushige Hayashi</a>, <a href="https://publications.waset.org/abstracts/search?q=Yorihiro%20Tanaka"> Yorihiro Tanaka</a>, <a href="https://publications.waset.org/abstracts/search?q=Shigeru%20Ogita"> Shigeru Ogita</a>, <a href="https://publications.waset.org/abstracts/search?q=Akihiko%20Wakai"> Akihiko Wakai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Slow-moving landslides are one of the major natural disasters in mountainous regions. Therefore, study of the creep displacement behaviour of a landslide and associated geological and geotechnical issues seem important. This study has addressed and evaluated the slow-moving behaviour of landslide using the 2D-FEM based Elasto-viscoplastic constitutive model. To our based knowledge, two new control constitutive parameters were incorporated in the numerical model for the first time to better understand the slow-moving behaviour of a landslide. First, the predicted time histories of horizontal displacement of the landslide are presented and discussed, which may be useful for landslide displacement prediction in the future. Then, the simulation results of deformation pattern and shear strain pattern is presented and discussed. Moreover, the possible failure mechanism along the slip surface of such landslide is discussed based on the simulation results. It is believed that this study will be useful to understand the slow-moving behaviour of landslides, and at the same time, long-term monitoring and management of the landslide disaster will be much easier. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=numerical%20simulation" title="numerical simulation">numerical simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=ground%20water%20fluctuations" title=" ground water fluctuations"> ground water fluctuations</a>, <a href="https://publications.waset.org/abstracts/search?q=elasto-viscoplastic%20model" title=" elasto-viscoplastic model"> elasto-viscoplastic model</a>, <a href="https://publications.waset.org/abstracts/search?q=slow-moving%20behaviour" title=" slow-moving behaviour"> slow-moving behaviour</a> </p> <a href="https://publications.waset.org/abstracts/173306/elasto-viscoplastic-constitutive-modelling-of-slow-moving-landslides" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/173306.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">78</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">704</span> Identification of Landslide Features Using Back-Propagation Neural Network on LiDAR Digital Elevation Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chia-Hao%20Chang">Chia-Hao Chang</a>, <a href="https://publications.waset.org/abstracts/search?q=Geng-Gui%20Wang"> Geng-Gui Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jee-Cheng%20Wu"> Jee-Cheng Wu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The prediction of a landslide is a difficult task because it requires a detailed study of past activities using a complete range of investigative methods to determine the changing condition. In this research, first step, LiDAR 1-meter by 1-meter resolution of digital elevation model (DEM) was used to generate six environmental factors of landslide. Then, back-propagation neural networks (BPNN) was adopted to identify scarp, landslide areas and non-landslide areas. The BPNN uses 6 environmental factors in input layer and 1 output layer. Moreover, 6 landslide areas are used as training areas and 4 landslide areas as test areas in the BPNN. The hidden layer is set to be 1 and 2; the hidden layer neurons are set to be 4, 5, 6, 7 and 8; the learning rates are set to be 0.01, 0.1 and 0.5. When using 1 hidden layer with 7 neurons and the learning rate sets to be 0.5, the result of Network training root mean square error is 0.001388. Finally, evaluation of BPNN classification accuracy by the confusion matrix shows that the overall accuracy can reach 94.4%, and the Kappa value is 0.7464. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=digital%20elevation%20model" title="digital elevation model">digital elevation model</a>, <a href="https://publications.waset.org/abstracts/search?q=DEM" title=" DEM"> DEM</a>, <a href="https://publications.waset.org/abstracts/search?q=environmental%20factors" title=" environmental factors"> environmental factors</a>, <a href="https://publications.waset.org/abstracts/search?q=back-propagation%20neural%20network" title=" back-propagation neural network"> back-propagation neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=BPNN" title=" BPNN"> BPNN</a>, <a href="https://publications.waset.org/abstracts/search?q=LiDAR" title=" LiDAR "> LiDAR </a> </p> <a href="https://publications.waset.org/abstracts/93322/identification-of-landslide-features-using-back-propagation-neural-network-on-lidar-digital-elevation-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/93322.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">144</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">703</span> Affect of Reservoir Fluctuations on an Active Landslide in the Xiangjiaba Reservoir Area, Southwest China</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Javed%20Iqbal">Javed Iqbal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Filling of Xiangjiaba Reservoir Lake in Southwest China triggered and re-activated numerous landslides due to water fluctuation. In order to understand the relationship between reservoirs and slope instability, a typical reservoir landslide (Dasha landslide) at right bank of Jinsha River was selected as a case study for in-depth investigations. The detailed field investigations were carried out in order to identify the landslide with respect to its surroundings and to find out the slip-surface. Boreholes were drilled in order to find out the subsurface lithology and the depth of failure of Dasha landslide. The in-situ geotechnical tests were performed, and the soil samples from exposed slip surface were retrieved for geotechnical laboratory analysis. Finally, stability analysis was done using 3D strength reduction method under different conditions of reservoir water level fluctuations and rainfall conditions. The in-depth investigations show that the Dasha landslide is a bedding rockslide which was once activated in 1986. The topography of Dasha landslide is relatively flat, while the back scarp and local terrain are relatively steep. The landslide area is about 29 × 104 m², and the maximum thickness of the landslide deposits revealed by drilling is about 40 m with the average thickness being about 20 m, and the volume is thus estimated being about 580 × 10⁴ m³. Bedrock in the landslide area is composed of Suining Formation of Jurassic age. The main rock type is silty mudstone with sandstone, and bedding orientation is 300~310° ∠ 7~22°. The factor of safety (FOS) of Dasha landslide obtained by 3D strength reduction cannot meet the minimum safety requirement under the working condition of reservoir level fluctuation as designed, with effect of rainfall and rapid drawdown. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dasha%20landslide" title="Dasha landslide">Dasha landslide</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiangjiaba%20reservoir" title=" Xiangjiaba reservoir"> Xiangjiaba reservoir</a>, <a href="https://publications.waset.org/abstracts/search?q=strength%20reduction%20method" title=" strength reduction method"> strength reduction method</a>, <a href="https://publications.waset.org/abstracts/search?q=bedding%20rockslide" title=" bedding rockslide "> bedding rockslide </a> </p> <a href="https://publications.waset.org/abstracts/87622/affect-of-reservoir-fluctuations-on-an-active-landslide-in-the-xiangjiaba-reservoir-area-southwest-china" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87622.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">162</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">702</span> Identification of Deep Landslide on Erzurum-Turkey Highway by Geotechnical and Geophysical Methods and its Prevention</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ne%C5%9Fe%20I%C5%9F%C4%B1k">Neşe Işık</a>, <a href="https://publications.waset.org/abstracts/search?q=%C5%9Eenol%20Alt%C4%B1ok"> Şenol Altıok</a>, <a href="https://publications.waset.org/abstracts/search?q=Galip%20Devrim%20Ery%C4%B1lmaz"> Galip Devrim Eryılmaz</a>, <a href="https://publications.waset.org/abstracts/search?q=Ayd%C4%B1n%20durukan"> Aydın durukan</a>, <a href="https://publications.waset.org/abstracts/search?q=Hasan%20%C3%96zg%C3%BCr%20Da%C5%9F"> Hasan Özgür Daş</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, an active landslide zone affecting the road alignment on the Tortum-Uzundere (Erzurum/Turkey) highway was investigated. Due to the landslide movement, problems have occurred in the existing road pavement, which has caused both safety problems and reduced driving comfort in the operation of the road. In order to model the landslide, drilling, geophysical and inclinometer studies were carried out in the field within the scope of ground investigation. Laboratory tests were carried out on soil and rock samples obtained from the borings. When the drilling and geophysical studies were evaluated together, it was determined that the study area has a complex geological structure. In addition, according to the inclinometer results, the direction and speed of movement of the landslide mass were observed. In order to create an idealized geological profile, all field and laboratory studies were evaluated together and then the sliding surface of the landslide was determined by back analysis method. According to the findings obtained, it was determined that the landslide was massively large, and the movement occurred had a deep sliding surface. As a result of the numerical analyses, it was concluded that the Slope angle reduction is the most economical and environmentally friendly method for the control of the landslide mass. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landslide" title="landslide">landslide</a>, <a href="https://publications.waset.org/abstracts/search?q=geotechnical%20methods" title=" geotechnical methods"> geotechnical methods</a>, <a href="https://publications.waset.org/abstracts/search?q=geophysics" title=" geophysics"> geophysics</a>, <a href="https://publications.waset.org/abstracts/search?q=monitoring" title=" monitoring"> monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=highway" title=" highway"> highway</a> </p> <a href="https://publications.waset.org/abstracts/162498/identification-of-deep-landslide-on-erzurum-turkey-highway-by-geotechnical-and-geophysical-methods-and-its-prevention" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162498.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">68</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">701</span> Identification of Thermally Critical Zones Based on Inter Seasonal Variation in Temperature</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sakti%20Mandal">Sakti Mandal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Varying distribution of land surface temperature in an urbanized environment is a globally addressed phenomenon. Usually has been noticed that criticality of surface temperature increases from the periphery to the urban centre. As the centre experiences maximum severity of heat throughout the year, it also represents most critical zone in terms of thermal condition. In this present study, an attempt has been taken to propose a quantitative approach of thermal critical zonation (TCZ) on the basis of seasonal temperature variation. Here the zonation is done by calculating thermal critical value (TCV). From the Landsat 8 thermal digital data of summer and winter seasons for the year 2014, the land surface temperature maps and thermally critical zonation has been prepared, and corresponding dataset has been computed to conduct the overall study of that particular study area. It is shown that TCZ can be clearly identified and analyzed by the help of inter-seasonal temperature range. The results of this study can be utilized effectively in future urban development and planning projects as well as a framework for implementing rules and regulations by the authorities for a sustainable urban development through an environmentally affable approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=thermal%20critical%20values%20%28TCV%29" title="thermal critical values (TCV)">thermal critical values (TCV)</a>, <a href="https://publications.waset.org/abstracts/search?q=thermally%20critical%20zonation%20%28TCZ%29" title=" thermally critical zonation (TCZ)"> thermally critical zonation (TCZ)</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20surface%20temperature%20%28LST%29" title=" land surface temperature (LST)"> land surface temperature (LST)</a>, <a href="https://publications.waset.org/abstracts/search?q=Landsat%208" title=" Landsat 8"> Landsat 8</a>, <a href="https://publications.waset.org/abstracts/search?q=Kolkata%20Municipal%20Corporation%20%28KMC%29" title=" Kolkata Municipal Corporation (KMC)"> Kolkata Municipal Corporation (KMC)</a> </p> <a href="https://publications.waset.org/abstracts/85395/identification-of-thermally-critical-zones-based-on-inter-seasonal-variation-in-temperature" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/85395.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">197</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">700</span> Study of the Mega–Landslide at the Community of Ropoto, Central Greece, and of the Design of Mitigation and Early Warning System Using the Fiber Bragg Grating Technology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Michael%20Bellas">Michael Bellas</a>, <a href="https://publications.waset.org/abstracts/search?q=George%20Voulgaridis"> George Voulgaridis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper refers to the world known mega - landslide induced at the community of Ropoto, belonging to the Municipality of Trikala, in the Central part of Greece. The landslide affected the debris as well as the colluvium mantle of the flysch, and makes up a special case of study in engineering geology and geotechnical engineering not only because of the size of the domain affected by the landslide (approximately 750m long), but also because of the geostructure’s global behavior. Due to the landslide, the whole community’s infrastructure massively collapsed and human lives were put in danger. After the complete simulation of the coupled Seepage - Deformation phenomenon due to the extreme rainfall, and by closely examining the slope’s global behavior, both the mitigation of the landslide, as well as, an advanced surveillance method (Fiber Bragg Grating) using fiber optics were further studied, in order both to retain the geostructure and to monitor its health by creating an early warning system, which would serve as a complete safety net for saving both the community’s infrastructure as well as the lives of its habitats. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=landslide" title="landslide">landslide</a>, <a href="https://publications.waset.org/abstracts/search?q=remediation%20measures" title=" remediation measures"> remediation measures</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20finite%20element%20method%20%28FEM%29" title=" the finite element method (FEM)"> the finite element method (FEM)</a>, <a href="https://publications.waset.org/abstracts/search?q=Fiber%20Bragg%20Grating%20%28FBG%29%20sensing%20method" title=" Fiber Bragg Grating (FBG) sensing method"> Fiber Bragg Grating (FBG) sensing method</a> </p> <a href="https://publications.waset.org/abstracts/71430/study-of-the-mega-landslide-at-the-community-of-ropoto-central-greece-and-of-the-design-of-mitigation-and-early-warning-system-using-the-fiber-bragg-grating-technology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71430.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">329</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">699</span> Flood Hazard Assessment and Land Cover Dynamics of the Orai Khola Watershed, Bardiya, Nepal</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Loonibha%20Manandhar">Loonibha Manandhar</a>, <a href="https://publications.waset.org/abstracts/search?q=Rajendra%20Bhandari"> Rajendra Bhandari</a>, <a href="https://publications.waset.org/abstracts/search?q=Kumud%20Raj%20Kafle"> Kumud Raj Kafle</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nepal’s Terai region is a part of the Ganges river basin which is one of the most disaster-prone areas of the world, with recurrent monsoon flooding causing millions in damage and the death and displacement of hundreds of people and households every year. The vulnerability of human settlements to natural disasters such as floods is increasing, and mapping changes in land use practices and hydro-geological parameters is essential in developing resilient communities and strong disaster management policies. The objective of this study was to develop a flood hazard zonation map of Orai Khola watershed and map the decadal land use/land cover dynamics of the watershed. The watershed area was delineated using SRTM DEM, and LANDSAT images were classified into five land use classes (forest, grassland, sediment and bare land, settlement area and cropland, and water body) using pixel-based semi-automated supervised maximum likelihood classification. Decadal changes in each class were then quantified using spatial modelling. Flood hazard mapping was performed by assigning weights to factors slope, rainfall distribution, distance from the river and land use/land cover on the basis of their estimated influence in causing flood hazard and performing weighed overlay analysis to identify areas that are highly vulnerable. The forest and grassland coverage increased by 11.53 km² (3.8%) and 1.43 km² (0.47%) from 1996 to 2016. The sediment and bare land areas decreased by 12.45 km² (4.12%) from 1996 to 2016 whereas settlement and cropland areas showed a consistent increase to 14.22 km² (4.7%). Waterbody coverage also increased to 0.3 km² (0.09%) from 1996-2016. 1.27% (3.65 km²) of total watershed area was categorized into very low hazard zone, 20.94% (60.31 km²) area into low hazard zone, 37.59% (108.3 km²) area into moderate hazard zone, 29.25% (84.27 km²) area into high hazard zone and 31 villages which comprised 10.95% (31.55 km²) were categorized into high hazard zone area. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flood%20hazard" title="flood hazard">flood hazard</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20use%2Fland%20cover" title=" land use/land cover"> land use/land cover</a>, <a href="https://publications.waset.org/abstracts/search?q=Orai%20river" title=" Orai river"> Orai river</a>, <a href="https://publications.waset.org/abstracts/search?q=supervised%20maximum%20likelihood%20classification" title=" supervised maximum likelihood classification"> supervised maximum likelihood classification</a>, <a href="https://publications.waset.org/abstracts/search?q=weighed%20overlay%20analysis" title=" weighed overlay analysis"> weighed overlay analysis</a> </p> <a href="https://publications.waset.org/abstracts/83533/flood-hazard-assessment-and-land-cover-dynamics-of-the-orai-khola-watershed-bardiya-nepal" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/83533.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">353</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=landslide%20hazard%20zonation&page=2">2</a></li> <li class="page-item"><a class="page-link" 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