Accounting for Uncertainty and Reconstruction of Flooding Patterns Based on Multi-Satellite Imagery and Support Vector Machine Technique: A Case Study of Can Tho City, Vietnam

摘要: One of the most frequent natural perils affecting world today is flooding, and over years, flooding has caused a large loss life damage to property. Remote sensing technology satellite imagery derived data are useful in mapping inundated area, which for flood risk management. In current paper, commonly used from public domain extent capturing studied considering Can Tho City as study area. The differences areas different sensors possible reasons explored. An effective relatively advanced method address uncertainties—inundated area capture remote sensors—was implemented while establishing pattern between years 2000 2018. This solution involves usage machine learning technique, Support Vector Machine Regression (SVR) further helps filling gaps whenever there lack single source. could be extended establish patterns data-sparse regions where access difficult. Furthermore, economical, freely available purpose.