Landslide susceptibility assessment for a transmission line in Gansu Province, China by using a hybrid approach of fractal theory, information value, and random forest models

2021 ◽  
Vol 80 (12) ◽  
Author(s):  
Binbin Zhao ◽  
Yunfeng Ge ◽  
Hongzhi Chen
Keyword(s):  
Random Forest ◽  
Landslide Susceptibility ◽  
Fractal Theory ◽  
Hybrid Approach ◽  
Gansu Province ◽  
Information Value ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment ◽  
Forest Models ◽  
Random Forest Models

scholarly journals Using the rotation and random forest models of ensemble learning to predict landslide susceptibility

2020 ◽  
Vol 11 (1) ◽  
pp. 1542-1564
Author(s):  
Lingran Zhao ◽  
Xueling Wu ◽  
Ruiqing Niu ◽  
Ying Wang ◽  
Kaixiang Zhang
Keyword(s):  
Random Forest ◽  
Ensemble Learning ◽  
Landslide Susceptibility ◽  
Forest Models ◽  
Random Forest Models

Statistical landslide susceptibility assessment in a dynamic environment: A case study for Lanzhou City, Gansu Province, NW China

2018 ◽  
Vol 15 (6) ◽  
pp. 1299-1318 ◽  
Author(s):  
Jewgenij Torizin ◽  
Li-chao Wang ◽  
Michael Fuchs ◽  
Bin Tong ◽  
Dirk Balzer ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Dynamic Environment ◽  
Gansu Province ◽  
Susceptibility Assessment ◽  
Nw China ◽  
Lanzhou City ◽  
Landslide Susceptibility Assessment

scholarly journals Landslide susceptibility assessment considering landslide typology. A case study in the area north of Lisbon (Portugal)

2002 ◽  
Vol 2 (1/2) ◽  
pp. 73-82 ◽  
Author(s):  
J. L. Zêzere
Keyword(s):  
Landslide Susceptibility ◽  
Slope Movement ◽  
Information Value ◽  
Slope Instability ◽  
Slope Aspect ◽  
Susceptibility Assessment ◽  
Slope Movements ◽  
Landslide Susceptibility Assessment ◽  
Different Types ◽  
Area North

Abstract. The aim of the study is to confirm the importance of discriminate different types of slope movements for a better landslide susceptibility evaluation. The study was applied to the sample area of Calhandriz (11.3 km2) in the area North of Lisbon. Sixty shallow translational slides, 23 deeper translational movements and 19 rotational movements were selected for statistical analysis. Landslide susceptibility assessment was achieved using a data-driven approach: the Information Value Method (Yin and Yan, 1988). The method was applied both to the total set of considered landslides and to each type of slope movement, and the obtained success rates for the highest susceptibility classes are higher in the latter case. The different types of landslides are not equally conditioned by the considered instability factors. Information scores are higher for lithology, concordance between slope aspect and dip of the strata, and slope angle, respectively, for rotational movements, translational movements and shallow translational slides. The information value of the variables "presence of artificial cut (roads)" and "presence of fluvial channel" is systematically high for the three types of slope movement, pointing out the importance of both anthropogenic influence and bank erosion on slope instability in the study area. Different types of landslides have neither the same magnitude nor equal damaging potential. Furthermore, technical strategies to mitigate landsliding also depend on landslide typology. These are additional reasons to discriminate between different types of slope movements when assessing landslide susceptibility and hazard.

scholarly journals Rainfall-induced landslide susceptibility assessment using random forest weight at basin scale

2017 ◽  
Vol 49 (5) ◽  
pp. 1363-1378 ◽  
Author(s):  
Chengguang Lai ◽  
Xiaohong Chen ◽  
Zhaoli Wang ◽  
Chong-Yu Xu ◽  
Bing Yang
Keyword(s):  
Random Forest ◽  
Landslide Susceptibility ◽  
Slope Angle ◽  
Fuzzy Comprehensive Evaluation ◽  
Assessment Model ◽  
Assessment Procedure ◽  
Susceptibility Assessment ◽  
Entropy Weight ◽  
Landslide Susceptibility Assessment ◽  
Basin Scale

Abstract Rainfall-induced landslide susceptibility assessment is currently considered an effective tool for landslide hazard assessment as well as for appropriate warning and forecasting. As part of the assessment procedure, a credible index weight matrix can strongly increase the rationality of the assessment result. This study proposed a novel weight-determining method by using random forests (RFs) to find a suitable weight. Random forest weights (RFWs) and eight indexes were used to construct an assessment model of the Dongjiang River basin based on fuzzy comprehensive evaluation. The results show that RF identified the elevation (EL) and slope angle (SL) as the two most important indexes, and soil erodibility factor (SEF) and shear resistance capacity (SRC) as the two least important indexes. The assessment accuracy of RFW can be as high as 79.71%, which is higher than the entropy weight (EW) of 63.77%. Two experiments were conducted by respectively removing the most dominant and the weakest indexes to examine the rationality and feasibility of RFW; both precision validation and contrastive analysis indicated the assessment results of RFW to be reasonable and satisfactory. The initial application of RF for weight determination shows significant potential and the use of RFW is therefore recommended.

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