Landslide susceptibility assessment using the maximum entropy model in a sector of the Cluj–Napoca Municipality, Romania

Q4 Earth and Planetary Sciences
A. Kerekes, S. Poszet, A. Gál
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引用次数: 11

Abstract

The administrative territory of Cluj–Napoca, due to its specific geological and geomorphological characteristics and anthropic activities, has been affected for a long time by landslides. Thus, it becomes necessary to analyse affected areas with different spatial methods, with the aim of generating landslide susceptibility maps. In this research, we studied the most prone area of the city, the Becaș stream watershed, situated in the Southern part of the municipality. The aim of this paper is to generate a valid susceptibility map, to be able to raise awareness about the existing situation: due to human induced activities and rapid urban growth, the peripheral part of Cluj–Napoca becomes more and more prone to mass–movements. We used the maximum entropy (MaxEnt) model, which was fed with accurate information on the existing landslides and seven landslide–causing factors: slope, aspect, land–use, depth of fragmentation, geology and plan– and profile curvature. The results confirm that the most influential factors are the land use and slope–angle, affected in a large degree by human activities. The accuracy of the generated map was verified using the AUC method, proving a very good performance (0.844) of the applied model.
利用最大熵模型在罗马尼亚克卢日-纳波卡市某地区进行滑坡易感性评价
克卢日-纳波卡行政区域由于其特殊的地质地貌特征和人类活动,长期以来一直受到山体滑坡的影响。因此,有必要用不同的空间方法分析受影响的地区,以生成滑坡易感性图。在这项研究中,我们研究了该市最容易发生这种情况的地区,即位于该市南部的becancu溪流流域。本文的目的是生成一个有效的易感性地图,以提高人们对现有情况的认识:由于人类活动和城市的快速增长,克卢日-纳波卡的外围地区越来越容易发生群众运动。我们使用了最大熵(MaxEnt)模型,该模型提供了现有滑坡和七个滑坡成因因素的准确信息:坡度、坡向、土地利用、破碎化深度、地质、平面和剖面曲率。研究结果表明,土地利用和坡度是影响耕地面积的主要因素,受人类活动的影响较大。使用AUC方法验证了生成地图的准确性,证明了所应用模型的性能非常好(0.844)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Revista de Geomorfologie
Revista de Geomorfologie Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
1.20
自引率
0.00%
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0
审稿时长
10 weeks
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