Abstract

The Earth’s surface consists of land and water. Surface water is separated into two groups: permanent water and temporary water. Flooding is temporary water that is often experienced in many places in Indonesia, including Lamongan Regency. In this area, at the beginning of 2022, seasonal floods caused many residents’ houses, agricultural land, and access roads to be submerged in water. This is due to its topography, which is characterized by lowlands and water. Land cover monitoring in large areas can be identified and analyzed using remote sensing. In this case, remote sensing is used to obtain information about surface water for separating permanent water and temporary water for comprehensive treatment in the long term. This study uses two primary sources of data: Sentinel-1 and Sentinel-2 satellite images from five years of observation from January 2018 to December 2022. Sentinel-1 is used to exploit its Synthetic Aperture Radar (SAR) sensor, which is sensitive to dielectric properties; thus, the water objects can be identified easily. Meanwhile, the Sentinel-2 satellite provides up to 10 meters of spatial-resolution satellite data. Processing was carried out using Image Fusion with Fuzzy Logic Min to merge the advantages of different data sources. The result of processing obtained that the probability of permanent water distribution in Lamongan Regency from 2018 to 2022 has differences in the total area every year. The total area of permanent water from Image Fusion is 12.769 km2. Meanwhile, the total area for flood inundation is 57.023 km2. A comparison of the processing results with comparative data is carried out for the calculation of the accuracy test. Overall accuracy for permanent water is 91%, with a kappa coefficient of 0.82. Then an overall accuracy for flood inundation obtained 90% with a kappa coefficient is 0.79. The result of this study is a permanent water map and flood inundation map of the Lamongan Regency, which is expected to be a reference in flood disaster mitigation activities.

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