Flood Disaster Monitoring Application In The National Rice Granary Area Based On Sentinel-1 Imagery (Case Study: Laren Disctrict, Lamongan Regency)

Natural conditions such as geography, climate, and the form of river flow can cause losses crop failure in the rice field sector due to natural disasters such as floods. The largest rice harvest area in 2021 makes East Java a national rice granary or a large rice-producing area. However, the rice harvest did not provide the same results, in the form of a decreasing amount of rice production in Laren District where the area directly adjacent to the Bengawan Solo River. So it's necessary to monitor rice fields that become national rice barn areas to mitigate and evaluate food security handling. Remote sensing technology with SAR Sentinel1 helps identify flood inundation areas because the sensor can work in all weather and penetrate clouds during cloud-covered floods. This research uses Sentinel-l GRD with the change detection method and thresholding 1.1 through the GEE cloud computing platform thrice on March 13, 2019;December 20,2020;and March 2, 2021. Research uses flood prediction with the Cellular Automata and ANN (CA-ANN) method through the MOLUSCE plugin. The results of flood identification show that the flood position is always in the southern part of the Laren District. Based on the three flood times identified, the three villages with the widest flood ranking are Gelap, Jabung, and Pelangwot Village. The results of flood prediction with CA-ANN showed that the method generally can evaluated the flood distribution area based on the spatiotemporal flood data, which showed that the flood area was still in the southern part of Laren District.