Vulnerability Liquefaction Mapping in Padang City Based on Cloud Computing Using Optical Satellite Imagery Data - Razi, Pakhrur; Putri, Amalia; Sri Sumantyo, Josaphat Tetuko; Akmam, - (JOIV : International Journal on Informatics Visualization, 2024)
Liquefaction is a significant geological hazard in earthquake-prone locations like Padang City, Indonesia. The phenomenon happens when saturated soil loses strength owing to seismic shaking, resulting in substantial infrastructure damage. Accurate identification of sensitive locations is critical to catastrophe mitigation. This study aims to map water distribution using optical satellite data and estimate its importance as a crucial element in determining liquefaction vulnerability. The Normalized Difference Water Index (NDWI) was used to assess water and vegetation indexes, taking advantage of its sensitivity to water content in varied land surfaces. We recommended using the NIR (near-infrared) and SWIR (short wave infrared) bands with 832.8 nm and 2202.4 nm, respectively, which are sensitive to soil water content. High-resolution satellite data were used to create NDWI maps, highlighting locations with high water saturation. These findings were combined with geological and seismic data to identify liquefaction-prone zones. The study found that locations with high water content, as measured by NDWI, are highly associated with greater liquefaction susceptibility. The findings highlight the importance of water distribution in determining soil behavior during seismic occurrences. This study highlights the value of NDWI as a low-cost and efficient tool for measuring liquefaction vulnerability at the regional level. The technique offers insights into Padang City's urban planning, catastrophe risk reduction, and community preparedness. By identifying high-risk zones, the study aids in making informed decisions to reduce the impact of future earthquakes. Most of the water content change occurred along the coastal line and in the low-lying areas of Koto Tanggah and North Padang sub-districts. The model can be used in other places with similar geological challenges, providing a scalable solution for liquefaction risk assessment.