Different landslide sampling strategies in a grid-based bi-variate statistical susceptibility model

被引:143
作者
Hussin, Haydar Y. [1 ]
Zumpano, Veronica [2 ]
Reichenbach, Paola [3 ]
Sterlacchini, Simone [4 ]
Micu, Mihai [2 ]
van Westen, Cees [1 ]
Balteanu, Dan [2 ]
机构
[1] Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, NL-7500 AE Enschede, Netherlands
[2] Acad Romana, Inst Geog, Bucharest 023993, Romania
[3] CNR, Res Inst Geohydrol Protect, I-06128 Perugia, Italy
[4] CNR, Inst Dynam Environm Proc, I-20126 Milan, Italy
关键词
Landslide susceptibility; Weights-of-evidence (WofE); Landslide sampling; Grid-based analysis; ARTIFICIAL NEURAL-NETWORKS; SPATIAL PREDICTION MODELS; LOGISTIC-REGRESSION; HAZARD ASSESSMENT; WENCHUAN EARTHQUAKE; FLEMISH ARDENNES; FREQUENCY RATIO; RISK-ASSESSMENT; FLASH-FLOOD; MAPS;
D O I
10.1016/j.geomorph.2015.10.030
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
This study had three aims. The first was to assess the performance of the weights-of-evidence (WofE) landslide susceptibility model in areas that are very different in terms of size, geoenvironmental settings, and landslide types. The second was to test the appropriate strategies to sample the mapped landslide polygon. The final aim was to evaluate the performance of the method to changes in the landslide sample size used to train the model. The method was applied to two areas: the Fella River basin (eastern Italian Alps) containing debris flows, and Buzau County (Romanian Carpathians) with shallow landslides. The three landslide sampling strategies used were: (1) the landslide scarp centroid, (2) points populating the scarp on a 50-m grid, and (3) the entire scarp polygon. The highest success rates were obtained when sampling shallow landslides as 50-m grid-points and debris flow scarps as polygons. Prediction rates were highest when using the entire scarp polygon method for both landslide types. The sample size test using the landslide centroids showed that a sample of 104 debris flow scarps was sufficient to predict the remaining 941 debris flows in the Fella River basin, while 161 shallow landslides was the minimum required number to predict the remaining 1451 scarps in Buzau County. Below these landslide sample thresholds, model performance was too low. However, using more landslides than the threshold produced a plateau effect with little to no increase in the model performance rates. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:508 / 523
页数:16
相关论文
共 84 条
[1]   A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at Izmir, Turkey [J].
Akgun, Aykut .
LANDSLIDES, 2012, 9 (01) :93-106
[2]  
Aleotti P., 1999, B ENG GEOL ENVIRON, V58, P21, DOI DOI 10.1007/S100640050066
[3]  
[Anonymous], 2011, J DATA SCI
[4]  
[Anonymous], 1989, STAT APPL EARTH SCI
[5]  
[Anonymous], 1984, NAT HAZARDS
[6]   Generalised linear modelling of susceptibility to landsliding in the central Apennines, Italy [J].
Atkinson, PM ;
Massari, R .
COMPUTERS & GEOSCIENCES, 1998, 24 (04) :373-385
[7]   The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan [J].
Ayalew, L ;
Yamagishi, H .
GEOMORPHOLOGY, 2005, 65 (1-2) :15-31
[8]   Validation and evaluation of predictive models in hazard assessment and risk management [J].
Beguería, S .
NATURAL HAZARDS, 2006, 37 (03) :315-329
[9]   Analysis of landslide inventories for accurate prediction of debris-flow source areas [J].
Blahut, Jan ;
van Westen, Cees J. ;
Sterlacchini, Simone .
GEOMORPHOLOGY, 2010, 119 (1-2) :36-51
[10]   Surveying flash floods: gauging the ungauged extremes [J].
Borga, Marco ;
Gaume, Eric ;
Creutin, Jean Dominique ;
Marchi, Lorenzo .
HYDROLOGICAL PROCESSES, 2008, 22 (18) :3883-3885