标题： 基于云计算的光学卫星遥感数据在巴东市易液化性脆弱性制图中的应用 显示英文标题

标题： Vulnerability Liquefaction Mapping in Padang City Based on Cloud Computing Using Optical Satellite Imagery Data

摘要： 液化是在地震多发地区如印度尼西亚巴东市的一种重要的地质灾害。 这种现象发生在饱和土壤由于地震震动失去强度时，导致基础设施严重损坏。 准确识别敏感区域对于减轻灾难至关重要。 本研究旨在利用光学卫星数据绘制水体分布，并评估其作为确定液化易损性关键因素的重要性。 使用归一化差异水体指数（NDWI）来评估水体和植被指数，利用其对不同地表水分含量的敏感性。 我们建议使用近红外（NIR）和短波红外（SWIR）波段，分别为832.8纳米和2202.4纳米，这些波段对土壤水分含量敏感。 高分辨率卫星数据用于创建NDWI图，突出显示水分饱和度高的区域。 这些结果与地质和地震数据相结合，以识别易发生液化的区域。 研究表明，通过NDWI测量的高水分含量区域与更高的液化敏感性高度相关。 研究结果强调了水体分布在地震发生时决定土壤行为的重要性。 本研究突出了NDWI作为一种低成本且高效工具在区域层面测量液化易损性的重要性。 该技术为巴东市的城市规划、灾难风险降低和社区准备提供了见解。 显示英文摘要

摘要： 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.