Geo-deformation failures leading to landslides cause huge loss to socioeconomic infrastructures a... more Geo-deformation failures leading to landslides cause huge loss to socioeconomic infrastructures and personal life and property all over the world, specifically in hilly terrains. It is a localized phenomenon which usually gets triggered by rainfall. In this paper, a framework for a warning system based on prediction of failure of geo-deformation has been proposed. The system warns against rainfall-triggered landslides making use of a Knowledge Based System including a warning module. The system consists of the input module, the understanding module, rainfall prediction module, the expert module, the output module and the warning module. The input module accepts scanned images of thematic maps of contributing factors of landslides as well as output from rainfall prediction module, based on field observed GPS data. The understanding module interprets input information to extract relevant information as required by expert module. The expert module consists of a Knowledge Base (KB) and Inference strategy to categorize the given region into different intensities of landslide hazard, output module communicates a warning message to warning module provided by the inference module and finally, warning module proclaim the warning message to user. At present, the system has the capability to prepare a Landslide Susceptibility Zone map of a region and its extension to a prediction system is under development. The major outcomes of the proposed system will be towards development of a warning system towards local geo-hazard analyses and provide a support system for landslide disaster preparedness and mitigation activities.
Geo-deformation failures leading to landslides cause huge loss to socio-economic infrastructures ... more Geo-deformation failures leading to landslides cause huge loss to socio-economic infrastructures and personal life and property all over the world, specifically in hilly terrains. It is a localized phenomenon which usually gets triggered by rainfall. In this paper, a framework for a warning system based on prediction of failure of geo-deformation has been proposed. The system warns against rainfall-triggered landslides making use of a Knowledge Based System including a warning module. The system consists of the input module, the understanding module, rainfall prediction module, the expert module, the output module and the warning module. The input module accepts scanned images of thematic maps of contributing factors of landslides as well as output from rainfall prediction module, based on field observed GPS data. The understanding module interprets input information to extract relevant information as required by expert module. The expert module consists of a Knowledge Base (KB) and Inference strategy to categorize the given region into different intensities of landslide hazard, output module communicates a warning message to warning module provided by the inference module and finally, warning module proclaim the warning message to user. At present, the system has the capability to prepare a Landslide Susceptibility Zone map of a region and its extension to a prediction system is under development. The major outcomes of the proposed system will be towards development of a warning system towards local geo-hazard analyses and provide a support system for landslide disaster preparedness and mitigation activities.
Geo-deformation failures leading to landslides cause huge loss to socioeconomic infrastructures a... more Geo-deformation failures leading to landslides cause huge loss to socioeconomic infrastructures and personal life and property all over the world, specifically in hilly terrains. It is a localized phenomenon which usually gets triggered by rainfall. In this paper, a framework for a warning system based on prediction of failure of geo-deformation has been proposed. The system warns against rainfall-triggered landslides making use of a Knowledge Based System including a warning module. The system consists of the input module, the understanding module, rainfall prediction module, the expert module, the output module and the warning module. The input module accepts scanned images of thematic maps of contributing factors of landslides as well as output from rainfall prediction module, based on field observed GPS data. The understanding module interprets input information to extract relevant information as required by expert module. The expert module consists of a Knowledge Base (KB) and Inference strategy to categorize the given region into different intensities of landslide hazard, output module communicates a warning message to warning module provided by the inference module and finally, warning module proclaim the warning message to user. At present, the system has the capability to prepare a Landslide Susceptibility Zone map of a region and its extension to a prediction system is under development. The major outcomes of the proposed system will be towards development of a warning system towards local geo-hazard analyses and provide a support system for landslide disaster preparedness and mitigation activities.
Geo-deformation failures leading to landslides cause huge loss to socio-economic infrastructures ... more Geo-deformation failures leading to landslides cause huge loss to socio-economic infrastructures and personal life and property all over the world, specifically in hilly terrains. It is a localized phenomenon which usually gets triggered by rainfall. In this paper, a framework for a warning system based on prediction of failure of geo-deformation has been proposed. The system warns against rainfall-triggered landslides making use of a Knowledge Based System including a warning module. The system consists of the input module, the understanding module, rainfall prediction module, the expert module, the output module and the warning module. The input module accepts scanned images of thematic maps of contributing factors of landslides as well as output from rainfall prediction module, based on field observed GPS data. The understanding module interprets input information to extract relevant information as required by expert module. The expert module consists of a Knowledge Base (KB) and Inference strategy to categorize the given region into different intensities of landslide hazard, output module communicates a warning message to warning module provided by the inference module and finally, warning module proclaim the warning message to user. At present, the system has the capability to prepare a Landslide Susceptibility Zone map of a region and its extension to a prediction system is under development. The major outcomes of the proposed system will be towards development of a warning system towards local geo-hazard analyses and provide a support system for landslide disaster preparedness and mitigation activities.
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Papers by Narendra Kumar