Applying Random Forest approach in forecasting flash flood susceptibility area in Lao Cai region
- Authors: Thao Phuong Thi Ngo 1*, Long Hung Ngo 1, Khanh Quang Nguyen 1, Tinh Thanh Bui 2, Phong Van Tran 3, Ha Viet Nhu 2, Yen Hai Thi Nguyen 1
Affiliations:
1 Faculty of Information Technology, Hanoi University of Mining and Geology, Vienam
2 Faculty of Geosciences and Geoengineering, Hanoi University of Mining and Geology, Vietnam
3 Institute of Geological Sciences, Vietnam Academy of Science and Technology, Vietnam
- *Corresponding:This email address is being protected from spambots. You need JavaScript enabled to view it.
- Keywords: Flash Floods, GIS, Machine Learning, RandomForest, Sentinel-1A.
- Received: 18th-Aug-2020
- Revised: 13th-Sept-2020
- Accepted: 31st-Oct-2020
- Online: 31st-Oct-2020
- Section: Geomatics and Land Administration
Abstract:
The main objectives of this research are to provide a new approach for flash flood prediction in Lao Cai, where frequent typhoons happen. This method is based on the Random Forest classification algorithm. The researcher applied GIS database in combination with construction machine learning model and verified the forecasting model, extracted the data based on field survey of the flash flood area of Lao Cai and GIS (Geographic Information System). The results have proved that the model can be a useful tool for flash flood forecasting model, providing more data for land planning and management for preventing and predicting flash flood for Lao Cai area.
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