Landslide Susceptibility Mapping Using GIS and Bivariate Statistical Models in Chemoga Watershed, Ethiopia

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-02-20 DOI:10.1155/2024/6616269

Abinet Addis

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Abstract

This study aimed to map the landslide susceptibility in the Chemoga watershed, Ethiopia, using Geographic Information System (GIS) and bivariate statistical models. Based on Google earth imagery and field survey, about 169 landslide locations were identified and classified randomly into training datasets (70%) and test datasets (30%). Eleven landslides conditioning factors, including slope, elevation, aspect, curvature, topographic wetness index, normalized difference vegetation index, road, river, land use, rainfall, and lithology were integrated with training landslides to determine the weights of each factor and factor classes using both frequency ratio (FR) and information value (IV) models. The final landslide susceptibility map was classified into five classes: very low, low, moderate, high, and very high. The results of area under the curve (AUC) accuracy models showed that the success rates of the FR and IV models were 87.00% and 90.10%, while the prediction rates were 88.00% and 92.30%, respectively. This type of study will be very useful to the local government for future planning and decision on landslide mitigation plans.

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利用地理信息系统和双变量统计模型绘制埃塞俄比亚 Chemoga 流域的滑坡易发性地图

本研究旨在利用地理信息系统（GIS）和双变量统计模型绘制埃塞俄比亚 Chemoga 流域的滑坡易发性地图。根据谷歌地球图像和实地调查，确定了约 169 个滑坡地点，并将其随机分类为训练数据集（70%）和测试数据集（30%）。将坡度、海拔、坡向、曲率、地形湿润指数、归一化差异植被指数、道路、河流、土地利用、降雨量和岩性等 11 个滑坡条件因子与训练滑坡点进行整合，利用频率比（FR）和信息值（IV）模型确定每个因子和因子类别的权重。最终的滑坡易发性图被分为五个等级：极低、低、中、高和极高。曲线下面积（AUC）精度模型的结果显示，频率比模型和信息值模型的成功率分别为 87.00% 和 90.10%，预测率分别为 88.00% 和 92.30%。此类研究将对地方政府未来规划和决定滑坡缓解计划非常有用。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.