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The effects of a landslide can represent a very big problem, including the death of people, damage to the land, environmental pollution and the loss of natural resources. Landslides are the most important medium for transferring sediments and polluting waterways by earth and organic materials. An excess of sediments reduces the quality of fish habitat and the potability of water. In order to understand landslides in depth, a thorough study was conducted using a scientometric analysis, as well as a thorough practical examination of landslide analysis and monitoring techniques. This review focused on methods used for landslide analysis, including physical models requiring easily prepared event-based landslide inventory, probabilistic methods which are useful for both shallow and earthquake-based landslides, and landslide monitoring performed by remote sensing techniques, which provide data helpful for prediction, monitoring and mapping. The fundamental principles of each method are described in terms of the method used, and its advantages, and limits. People and infrastructure are at danger from landslides caused by heavy rain, so this report highlights landslide-prone regions and considers the analysis methods for landslides used in these countries, with a view to identifying mitigation measures for coping with landslide risks in hilly areas. Furthermore, future landslide research possibilities, as well as possible modeling methods, are addressed. The report summarizes some landslide prediction and monitoring techniques used in landslide-prone countries which can help inform researchers seeking to protect the public from danger in landslide areas. [ABSTRACT FROM AUTHOR]

The effects of a landslide can represent a very big problem, including the death of people, damage to the land, environmental pollution and the loss of natural resources. Landslides are the most important medium for transferring sediments and polluting waterways by earth and organic materials. An excess of sediments reduces the quality of fish habitat and the potability of water. In order to understand landslides in depth, a thorough study was conducted using a scientometric analysis, as well as a thorough practical examination of landslide analysis and monitoring techniques. This review focused on methods used for landslide analysis, including physical models requiring easily prepared event-based landslide inventory, probabilistic methods which are useful for both shallow and earthquake-based landslides, and landslide monitoring performed by remote sensing techniques, which provide data helpful for prediction, monitoring and mapping. The fundamental principles of each method are described in terms of the method used, and its advantages, and limits. People and infrastructure are at danger from landslides caused by heavy rain, so this report highlights landslide-prone regions and considers the analysis methods for landslides used in these countries, with a view to identifying mitigation measures for coping with landslide risks in hilly areas. Furthermore, future landslide research possibilities, as well as possible modeling methods, are addressed. The report summarizes some landslide prediction and monitoring techniques used in landslide-prone countries which can help inform researchers seeking to protect the public from danger in landslide areas.

Semarang has a high potential of landslides occurrences in its almost area that should be noted by the stakeholders. Consider this fact, human as the part of the system should be used as a center of the disaster management system to reduce the risk caused by the disaster. An adapted model of human factor toolkits is developed to represent a specific phase of human-centered disaster management. This model presents four phases including major disaster scenario, human error analysis, safety critical task and performance influence factors (PIFs). As the preliminary implementation, this study takes the pilot implementation of each phase of the model to examine the reliability of the concept in the landslide cases, especially in Semarang city. The result shows that there is quite a high deviation between expected and observed behavior of the community and the government institution regarding the awareness states of the system.

Semarang has a high potential of landslides occurrences in its almost area that should be noted by the stakeholders. Consider this fact, human as the part of the system should be used as a center of the disaster management system to reduce the risk caused by the disaster. An adapted model of human factor toolkits is developed to represent a specific phase of human-centered disaster management. This model presents four phases including major disaster scenario, human error analysis, safety critical task and performance influence factors (PIFs). As the preliminary implementation, this study takes the pilot implementation of each phase of the model to examine the reliability of the concept in the landslide cases, especially in Semarang city. The result shows that there is quite a high deviation between expected and observed behavior of the community and the government institution regarding the awareness states of the system. [ABSTRACT FROM AUTHOR]