Effect of Soil Geomechanical Properties and Geo-Environmental Factors on Landslide Predisposition at Mount Oku, Cameroon

Wamba Danny Love Djukem, Anika Braun, Armand Sylvain Ludovic Wouatong, Christian Guedjeo, Katrin Dohmen, Pierre Wotchoko, Tomas Manuel Fernandez-Steeger and Hans-Balder Havenith
Additional contact information
Wamba Danny Love Djukem: Department of Earth Sciences, Faculty of Sciences, University of Dschang, Dschang P.O. Box 67, Cameroon
Anika Braun: Department of Engineering Geology, Institute of Applied Geosciences, Faculty VI Planning Building Environment, Technische Universität Berlin, 10587 Berlin, Germany
Armand Sylvain Ludovic Wouatong: Department of Earth Sciences, Faculty of Sciences, University of Dschang, Dschang P.O. Box 67, Cameroon
Christian Guedjeo: Department of Earth Sciences, Faculty of Sciences, University of Dschang, Dschang P.O. Box 67, Cameroon
Katrin Dohmen: Department of Engineering Geology, Institute of Applied Geosciences, Faculty VI Planning Building Environment, Technische Universität Berlin, 10587 Berlin, Germany
Pierre Wotchoko: HTTC Bambili, University of Bamenda, Bamenda P.O. Box 39, Cameroon
Tomas Manuel Fernandez-Steeger: Department of Engineering Geology, Institute of Applied Geosciences, Faculty VI Planning Building Environment, Technische Universität Berlin, 10587 Berlin, Germany
Hans-Balder Havenith: Geology Department-B18, Georisk and Environment, Faculty of Sciences, Liege University, B-4000 Liege, Belgium

IJERPH, 2020, vol. 17, issue 18, 1-27

Abstract: In this work, we explored a novel approach to integrate both geo-environmental and soil geomechanical parameters in a landslide susceptibility model. A total of 179 shallow to deep landslides were identified using Google Earth images and field observations. Moreover, soil geomechanical properties of 11 representative soil samples were analyzed. The relationship between soil properties was evaluated using the Pearson correlation coefficient and geotechnical diagrams. Membership values were assigned to each soil property class, using the fuzzy membership method. The information value method allowed computing the weight value of geo-environmental factor classes. From the soil geomechanical membership values and the geo-environmental factor weights, three landslide predisposition models were produced, two separate models and one combined model. The results of the soil testing allowed classifying the soils in the study area as highly plastic clays, with high water content, swelling, and shrinkage potential. Some geo-environmental factor classes revealed their landslide prediction ability by displaying high weight values. While the model with only soil properties tended to underrate unstable and stable areas, the model combining soil properties and geo-environmental factors allowed a more precise identification of stability conditions. The geo-environmental factors model and the model combining geo-environmental factors and soil properties displayed predictive powers of 80 and 93%, respectively. It can be concluded that the spatial analysis of soil geomechanical properties can play a major role in the detection of landslide prone areas, which is of great interest for site selection and planning with respect to sustainable development at Mount Oku.

Keywords: soil geomechanical properties; geo-environmental factors; pearson correlation coefficient; statistical index information value method; fuzzy membership; receiver operator characteristic (ROC) curve; landslide susceptibility; disaster prevention (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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