Flood Forecasting in Vientiane Capital, Laos based on the Analytic Hierarchy Process (AHP) Method in Remote Sensing

Introduces a flood risk prediction algorithm based on the Analytic Hierarchy Process (AHP), a robust decision-making methodology known for its simplicity and effectiveness in systematically evaluating and prioritizing multiple criteria. Utilizing the Analytic Hierarchy Process (AHP) entails the development of a hierarchical framework encompassing standards and options. It involves assigning numerical values to individual criteria and employing Comparisons conducted in pairs to ascertain their concerning other factors or comparison to a reference point significance. In the specific context of flood risk prediction, four crucial factors within the Analytic Hierarchy Process are considered: rainfall patterns, vertical elevation, proximity to the river, and Land Use/Land Cover (LULC). These factors, closely linked to floods, are essential considerations in flood risk analysis. After conducting a comprehensive analysis of different elements, the proposed method categorizes flood risk into five levels: the smallest level, small level, middle level, high level, and highest level. The flood risk prediction algorithm begins by constructing a pairwise comparison matrix to quantify the significance of each variable concerning flooding occurrences. Subsequently, leveraging this matrix along with data on rainfall patterns, vertical elevation, river distance, and the utilization and composition of land (Land Use/Land Cover - LULC), The algorithm computes and evaluates the level of risk associated with flooding. This methodical approach improves the precision and reliability of flood risk predictions, offering valuable insights for developing proactive flood risk management strategies.