叙利亚塔尔图斯Al-Khawabi河流域滑坡易感性制图:双变量统计模型和地理空间技术的综合方法

Q2 Environmental Science
Hazem Ghassan Abdo
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引用次数: 0

摘要

山体滑坡是山区环境中最常见和最危险的自然灾害之一,对环境可持续性以及城市和人类发展构成重大威胁。在地质、气候和人为因素交织的地区,风险变得更加严重,就像叙利亚西部山区的情况一样,那里经常发生山体滑坡,导致基础设施和财产遭受重大破坏,并对当地居民构成威胁。本研究旨在利用空间分析技术和地理信息系统(GIS)为叙利亚西部的卡瓦比河流域绘制滑坡易感性图。共收集了33个记录在案的滑坡事件,并将其分为两个子集:70%用于训练以建立预测模型,30%用于测试以验证结果。选择10个被认为影响滑坡发生的条件因子进行空间分析:岩性、高程、坡度、坡向、曲率、断层距离、道路距离、河流距离、土地利用/土地覆盖(LULC)和地形湿度指数(TWI)。利用先进的GIS工具进行空间建模和制图,并将研究区划分为从低到高的不同易感区。结果表明,滑坡易感性极高的地区主要集中在东部陡坡沿线,地质、地形和人为因素共同作用于此。使用测试数据集的验证过程显示,预测准确率高达91.2%,证实了应用模型的可靠性和鲁棒性。本研究强调了利用遥感和地理信息系统技术绘制自然灾害风险地图的重要性,为叙利亚西部的滑坡风险管理和可持续城市规划提供准确的空间信息。该研究建议将研究结果纳入土地使用政策,并提高公众对减少与山体滑坡有关的灾害风险重要性的认识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Landslide susceptibility mapping in Al-Khawabi river basin, Tartous, Syria: An integrated approach of bivariate-statistical modelling and geospatial technology
Landslides are among the most common and hazardous natural disasters in mountainous environments, posing a significant threat to environmental sustainability and urban and human development. The risk becomes more severe in areas where geological, climatic, and human factors intersect, as is the case in the mountainous western region of Syria, which experiences recurrent landslides resulting in substantial damage to infrastructure, property, and threats to local populations. This study aims to produce a Landslide Susceptibility Map for the Khawabi River Basin in western Syria using spatial analysis techniques and Geographic Information Systems (GIS). A total of 33 documented landslide events were collected and divided into two subsets: 70 % for training to build the predictive model, and 30 % for testing to validate the results. Ten conditioning factors that are believed to influence landslide occurrence were selected for spatial analysis: lithology, elevation, slope, aspect, curvature, distance to faults, distance to roads, distance to rivers, land use/land cover (LULC), and the Topographic Wetness Index (TWI). Spatial modeling and mapping were performed using advanced GIS tools, and the study area was classified into different susceptibility zones ranging from low to very high. The results revealed that areas with very high landslide susceptibility are primarily concentrated along the steep eastern mountain slopes, where a combination of geological, topographical, and anthropogenic factors converge. The validation process using the testing dataset showed a high predictive accuracy of 91.2 %, confirming the reliability and robustness of the applied model. This study highlights the importance of using remote sensing and GIS technologies for mapping natural hazard risks, providing accurate spatial information that can support landslide risk management and sustainable urban planning in western Syria. The study recommends integrating the findings into land-use policies and increasing public awareness about the importance of disaster risk reduction related to landslides.
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来源期刊
Environmental Challenges
Environmental Challenges Environmental Science-Environmental Engineering
CiteScore
8.00
自引率
0.00%
发文量
249
审稿时长
8 weeks
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