Multi-hazard assessment for flood and Landslide risk in Kalimantan and Sumatra: Implications for Nusantara, Indonesia's new capital.

ABSTRACT: Situated within the Ring of Fire and characterized by a tropical climate and high seismic activity, Indonesia is uniquely vulnerable to natural disasters such as floods and landslides. These events pose significant threats to both the population and infrastructure. This study predicts areas exposed to flood and landslide risk by considering various environmental factors related to climate, topography, and land use. The predictive performance of three machine learning models-naïve Bayes, k-nearest neighbors, and random forest (RF)-was evaluated by comparing the AUC, RMSE, and R² values of each model. Ultimately, the RF model, which demonstrated the highest accuracy, was used to prioritize disaster impact factors and generate hazard maps. The results identified the interaction of

SUBMITTER: Heo S 

PROVIDER: S-EPMC11437940 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature