the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Assessing Typhoon Soulik-induced morphodynamics over the Mokpo coastal region in South Korea based on a geospatial approach
Sang-Guk Yum
Moon-Soo Song
Manik Das Adhikari
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To reduce the consequences of landslides due to rainfall, such as loss of life, economic losses, and disruption to daily living, this study describes the process of building a machine learning model which can help to estimate the volume of landslide material that can occur in a particular region, taking into account antecedent rainfall, soil characteristics, type of vegetation, etc. The findings can be useful for land use management, infrastructure design, and rainfall disaster management.
To reduce the consequences of landslides due to rainfall, such as loss of life, economic losses, and disruption to daily living, this study describes the process of building a machine learning model which can help to estimate the volume of landslide material that can occur in a particular region, taking into account antecedent rainfall, soil characteristics, type of vegetation, etc. The findings can be useful for land use management, infrastructure design, and rainfall disaster management.