利用 GIS 矩阵法和频率比绘制滑坡易发性地图,在摩洛哥 Moulay Yacoub 地区大理岩环境中的应用

Ilias Obda, Elkharim Younes, Obda Oussama, Sahran Reda, Lahrach Abderrahim, Ahniche Mohamed
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引用次数: 0

摘要

近几十年来,人口、人造设施、基础设施和生命线的增长以滑坡易发地区为代价,导致世界许多地区的人员和经济损失成倍增加。在以泥质丘陵为主的 Moulay Yacoub 地区,半城市和农村的社会经济发展与山体滑坡的相互作用显著增加,这就需要识别风险区域并确定其优先次序,以最大限度地减少危害,避免 Moulay Yacoub 镇的灾难性后果。本文旨在为该省受影响严重的地区绘制山体滑坡易发区地图,该地区以前从未编制过山体滑坡数据,本文还旨在找到最相关的参数。为实现这一目标,将采用两种稳健的方法,即频率比法和 GIS 矩阵法。在此之前,对 11 个因素的相关性进行了测试。结果表明,人为因素,尤其是农业耕作方式,对水土流失的影响很大。两个模型的成功率约为 0.75(75%),表明两个易感性图的结果质量良好。因此,这两个模型可以得到有效利用,位于该省滑坡易发区的新农业项目必须包括这种可靠的滑坡风险分析方法,以最大限度地降低引发滑坡的概率,因为滑坡会危及人类生命、生态系统、粮食生产和基础设施。
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 using GIS Matrix Method and Frequency Ratio, application in the marly context of Moulay Yacoub Region, Morocco
In the recent decades, the growth of population, man-made facilities, infrastructures, and lifelines at the expense of landslides prone areas has been responsible for an exponential increase in human and economic losses in many parts of the world. In the Moulay Yacoub region, where marly hills dominate, the interaction of the semi-urban and rural socioeconomic development and landslides significantly increases, which urges identifying and prioritizing areas of risk in order to maximize harm reduction and to avoid the disastrous outcomes as is the case of Moulay Yacoub town. This paper aims to develop a landslide susceptibility map in a highly affected sector of the province, where no previous landslide data have been produced, and to find the most involved parameters. This goal will be attained using two robust methods, the Frequency Ratio and the GIS Matrix Method. Before that, the correlation of 11 factors was tested. The results show that the anthropogenic factors, particularly the agricultural practices, were highly involved, and the field investigation proved that cereal farming slopes were the most affected. The success rate was about 0.75 (75%) for both models showing good quality results for the two susceptibility maps. Therefore, the two models could be efficiently used, and the new agricultural projects located in landslide-prone areas of the province must include such reliable methods of landslide risk analysis to minimize the triggering probabilities, which would put human lives, ecosystems, food production, and infrastructure at risk.
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