Source Code Repository : "A Comparative Flood Susceptibility Mapping Using Machine Learning and Deep Learning: A Case Study of the November 2025 Extreme Flood Event in West Sumatra"

This code combines a deep learning architecture (CNN) with five machine learning ensemble algorithms—Random Forest, XGBoost, LightGBM, CatBoost, and ExtraTrees—to accurately map and predict flood vulnerability levels. This integration leverages the CNN’s spatial feature processing capabilities as well as the robustness of tree-based models in handling nonlinear tabular data. Main Requirements: Python 3.12 We use Google Colab to run this script, but you can run it in any other application that supports the Python programming language. The data used in this script is not included; you can adapt it to the dataset you have.