Penerapan Data Citra Satelit Landsat-9 Dalam Mendeteksi Genangan Banjir di Kabupaten Kudus Tahun 2023

Abstract

This study compares NDWI and MNDWI applied to Landsat-9 imagery for mapping flood inundation in Kudus Regency during January-February 2023. Top of Atmosphere Reflectance imagery was processed using Google Earth Engine, Fiji ImageJ, and QGIS; NDWI thresholds were derived with Otsu, while MNDWI used Natural Breaks. Accuracy was evaluated using confusion matrices. Inundated areas in January reached 43.77 km² (NDWI) and 78.15 km² (MNDWI), increasing in February to 60.99 km² (NDWI) and 90.45 km² (MNDWI). The highest Kappa was obtained by MNDWI in January (0.90) and NDWI in February (0.97), indicating that index performance depends on image conditions. Undaan consistently ranked first under both indices. The results can support risk-assessment updates, intervention prioritization in Undaan, and agricultural impact assessment. Scene metadata, reference data, cloud masking, and field validation must nevertheless be completed before operational use.