Multi-Temporal Analysis of Flood Dynamics and Land Use Land Cover Change in the Konaweha Watershed Using Multi-Sensor Remote Sensing Approach

Abstract Flooding is one of the most frequent and destructive environmental hazards globally, and Indonesia is among the most affected countries. Understanding land use land cover (LULC) changes and flood distribution is essential for effective mitigation strategies. However, conventional methods using multiple processing environments are time-consuming, whereas integrating multi-sensor data within a single platform such as Google Earth Engine (GEE) improves efficiency and accuracy. This study aims to analyzes flood distribution and LULC changes in the Konaweha watershed from 2015 to 2024 using multi-temporal Sentinel-1 SAR and Landsat-8 optical imagery. Flooded areas were mapped using the Otsu thresholding combined with change detection, while LULC changes were identified using the Random Forest algorithm. The result reveal that flood inundation expanded from 6,709.24 ha in 2015 to 16,295.35 ha in 2020, before declining to 9,243.28 ha in 2024. Major LULC transitions included reductions in wetlands (12.82 %), primary forest (1.94 %), and agriculture (28.82 %), alongside increase in built-up areas (80.48 %), secondary forest (8.13 %), and water bodies (41.76 %). This finding indicate a strong correlation between flood occurrence and LULC changes, emphasizing the influence of environmental degradation on flood dynamics. The study contributes to global discourse on flood risk assessment by demonstrating the effectiveness of integrating multi-sensor remote sensing data for near real-time flood monitoring and sustainable land management planning.