埃塞俄比亚西北部巴索利本地区滑坡易发性和风险分区的 GIS、FR 和 AHP 组合方法

IF 2.9 Q2 GEOGRAPHY, PHYSICAL
Biniyam Taye Alamrew , Tibebu Kassawmar , Likinaw Mengstie , Muralitharan Jothimani
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引用次数: 0

摘要

在山区,山体滑坡会对环境造成严重威胁,削弱基础设施,造成人员伤亡,并使经济蒙受损失。本文采用层次分析法(AHP)和基于地理信息系统(GIS)的频率比(FR)对埃塞俄比亚西北部巴索利本地区的滑坡易发性和风险进行了评估。研究了 11 个关键的环境和地质要素--高度、坡度、岩性、土壤类型和土地利用。经过实地调查和谷歌地球照片,整理出 342 起滑坡事件,并将其分为验证数据集(30%)和训练数据集(70%)。ROC 曲线为分析 FR 模型和 AHP 模型的有效性提供了一种技术。AHP 模型的曲线下面积(AUC)值为 83.4%,比 FR 模型(AUC 值为 74.4%)表现出更高的准确性。极低、低、中、高和极高的脆弱性被定义为滑坡危险区的五个类别。AHP 模型将 10.5% 的区域评估为极高风险区,19.8% 为高危险区,25.6% 为中等风险区,28% 为中等风险区,16.1% 为极低风险区。而 FR 模型则将 10.16% 的区域评估为极高风险,21.3% 为高风险,28.9% 为中等风险,22.5% 为低风险,17.04% 为极低风险。结果表明,坡角、岩性和海拔是影响滑坡脆弱性的关键因素。这些研究结果为土地利用规划和减少灾害风险提供了一个实用框架,为决策者提供了帮助减少滑坡危害的适当工具。这项研究强调了将客观数据分析与专家知识相结合以提高滑坡易发性模型的准确性和可靠性的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combined GIS, FR and AHP approaches to landslide susceptibility and risk zonation in the Baso Liben district, Northwestern Ethiopia
In mountainous places, landslides pose severe environmental threats, weakening infrastructure, resulting in death and costing the economy. This article assesses landslide susceptibility and risk in the Baso Liben district of Northwestern Ethiopia using an analytical hierarchy process (AHP) and Geographic Information System (GIS)-based Frequency Ratio (FR). Eleven key environmental and geological components— height, slope, lithology, soil type, and land use—were studied. After field research and Google Earth photos, 342 landslide incidents were collated and separated into validation (30%) and training (70%) datasets. ROC curves provide a technique for analyzing the efficacy of the FR and AHP models. With an Area Under the Curve (AUC) value of 83.4%, the AHP model exhibited superior accuracy than the FR model, with an AUC value of 74.4%. Very low, low, moderate, high, and very high vulnerability are five categories defined as landslide hazard zones. The AHP model assessed 10.5% of the area as very high risk, 19.8% as high danger, 25.6% as moderate risk, 28% as medium risk, and 16.1% as very low risk. The FR model meanwhile assessed 10.16% of the area as very high risk, 21.3% as high risk, 28.9% as moderate risk, 22.5% as low risk, and 17.04% as very low risk. The results reveal that slope angle, lithology, and elevation are key factors impacting landslide vulnerability. These findings equip a practical framework for land-use planning and disaster risk reduction, providing decision-makers with appropriate instruments to help lessen landslide hazards. The research underscores the significance of combining objective data analysis with expert knowledge to enhance the accuracy and reliability of landslide susceptibility models.
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来源期刊
Quaternary Science Advances
Quaternary Science Advances Earth and Planetary Sciences-Earth-Surface Processes
CiteScore
4.00
自引率
13.30%
发文量
16
审稿时长
61 days
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