Monitoring and Visualizing the Impact of the Lapindo Mudflow Disaster Using Earth Engine Apps Platform based on Cloud Computing
https://doi.org/10.52045/jca.v4i2.703
Keywords:
disaster, landsat, remote sensingAbstract
The Lapindo mudflow disaster at the PT Lapindo Brantas drilling site in Ronokenongo Village, Porong District, Sidoarjo Regency, East Java caused the loss of agricultural and residential areas. The research aimed to detect the areas that are affected by Lapindo mudflow 2006-2022 using Landsat 7 ETM and Landsat 8 OLI-TIRS imageries, as well as visualize their impact using the cloud computing-based Google Earth Engine/GEE platform. Spatiotemporal data analysis was performed on the GEE platform using random forest machine learning as algorithm for supervised land use classification, while visualization was carried out through Earth Engine Apps. The results showed an increase in the mudflow-affected area from 2006 (204.57 ha) to 2012 (542.32 ha) with northeast direction, whereas the increase was insignificant at the following years. Within the detection period, agricultural land was the most affected area, followed by residential areas and bare land. The area ordering was similar during all detected years. The increasing size of the affected area can potentially have both direct and indirect impacts on the surrounding area. Therefore, special action is needed for the surrounding area, such as relocating settlements to safer areas against the Lapindo mudflow disaster.
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Copyright (c) 2024 Ali Dzulfigar, Muhammad Ikhwan Ramadhan, Azzahra Pascawisudawati, Rahmat Asy'Ari, Yudi Setiawan, Rahmat Pramulya
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