Landslide Inventory, Sampling and Effect of Sampling Strategies on Landslide Susceptibility/Hazard Modelling at a Glance

  • Isik YilmazEmail author
  • Murat Ercanoglu
Part of the Advances in Natural and Technological Hazards Research book series (NTHR, volume 48)


Landslides have a significant portion of responsibility on the damages and losses caused by natural hazards such as earthquakes, floods, storms, and tsunamis all over the world. Thus, landslides and their consequences are of great importance among the scientists and authorities who want to minimize these effects for a long time. This procedure simply begins with the preparation of landslide database and inventory maps, which constitutes a fundamental basis for the further steps including landslide susceptibility, hazard, and risk assessments. In this aspect, this procedure can be considered as one of the most important stages for any landslide work to minimize the undesired consequences of landslides. This stage can be realized using some statistical techniques such as simple random, systematic, stratified and cluster sampling strategies in the literature. In this chapter, firstly, basic landslide definitions and concepts were discussed. Then, landslide inventory, susceptibility and hazard concepts were pointed out and linked to the sampling strategies with the recent literature. Although, every considered method has pros and cons, it could be concluded that the sampling carried out in the rupture zones of landslides as polygon features or seed cell approach representing the pre-failure conditions seem to be more realistic to obtain more accurate maps. The other important issue pointed out in this chapter is on the selection of data mining technique(s). Since landslides are complex processes and can be affected by many factors, this stage is very important to reflect the landslide conditions with huge amount of data. In many cases, the researchers generally encounter to struggle with huge amount of data related to the landslide initiation and/or mechanisms. Thus, the selection of data mining techniques deserve the necessary precaution and is elaborately discussed overall the chapter.


Data mining GIS Landslide inventory Sampling strategy Susceptibility/hazard mapping 


  1. Antonini G, Cardinali M, Guzzetti F, Reichenbach P, Sorrentino A (1993) Carta Inventario dei Fenomeni Franosi della Regione Marche ed aree limitrofe. CNR, Gruppo Nazionale per la Difesa dalle Catastrofi Idrogeologiche, Publication n. 580, 2 sheets, scale 1:100,000, (in Italian)Google Scholar
  2. Baeza C (1994) Evaluación de las condiciones de rotura y la movilidad de los deslizamientos superficiales mediante el uso de técnicas de análisis multivariante, Tesis Univ. Pol. CatalunyaGoogle Scholar
  3. Balteanu D, Chendeş V, Sima M, Enciu P (2010) A country-wide spatial assessment of landslide susceptibility in Romania. Geomorphology 124:102–112CrossRefGoogle Scholar
  4. Barredo JJ, Benavides A, Hervas J, Van Westen CJ (2000) Comparing heuristic landslide hazard assessment techniques using GIS in the Trijana basin, Gran Canaria Island, Spain. JAG 2(1):9–23CrossRefGoogle Scholar
  5. Bednarik M, Yilmaz I, Marschalko M (2012) Landslide hazard and risk assessment: a case study from the Hlohovec-Sered landslide area in south-west Slovakia. Nat Hazards 64(1):547–575CrossRefGoogle Scholar
  6. Borzyszkowski AM, Sokolowski S (eds) (1993) Mathematical foundations of computer science 1993. in 18th international symposium, MFCS’93 Gdansk, Poland, August 30–September 3, 1993 Proceedings, Lecture Notes in Computer Science, vol 711, pp 281–290Google Scholar
  7. Brabb EE (1991) The world landslide problem. Episodes 14(1):52–61Google Scholar
  8. Brabb EE, Pampeyan EH (1972) Preliminary map of landslide deposits in San Mateo County, California. U.S. Geological Survey Miscellaneous Field Studies Map, MF-344Google Scholar
  9. Brabb EE, Pampeyan EH, Bonilla M (1972) Landslide susceptibility in the San Mateo County, California, scale 1: 62.500, U.S. Geol. Survey Misc. Field Studies Map MF344Google Scholar
  10. Brabb EE, Wieczorek GF, Harp EL (1989) Map showing 1983 landslides in Utah. U.S. Geological Survey Miscellaneous Field Studies Map MF-1867Google Scholar
  11. Cardinali M, Guzzetti F, Brabb EE (1990) Preliminary map showing landslide deposits and related features in New Mexico. U.S. Geological Survey Open File Report 90/293, 4 sheets, scale 1:500,000Google Scholar
  12. Cardinali M, Antonini G, Reichenbach P, Guzzetti F (2001) Photo geological and landslide inventory map for the Upper Tiber River basin. CNR, Gruppo Nazionale per la Difesa dalle Catastrofi Idrogeologiche, Publication n. 2116, scale 1:100,000Google Scholar
  13. Cardinali M, Carrara A, Guzzetti F, Reichenbach P (2002) Landslide hazard map for the Upper Tiber River basin. CNR, Gruppo Nazionale per la Difesa dalle Catastrofi Idrogeologiche, Publication n. 2634, scale 1:100,000Google Scholar
  14. Cardinali M, Galli M, Guzzetti F, Ardizzone F, Reichenbach P, Bartoccini P (2006) Rainfall induced landslides in December 2004 in south-western Umbria, central Italy: types, extent, damage and risk assessment. Nat Hazards Earth Syst Sci 6:237–260CrossRefGoogle Scholar
  15. Carrara A (1983) Multivariate models for landslide hazard evaluation. Math Geol 15(3):403–426CrossRefGoogle Scholar
  16. Carrara A, Cardinalli M, Detti R, Guzzetti F, Pasqui V, Reichenbach P (1991) GIS techniques and statitistical models in evaluating landslide hazards. Earth Surf Proc Land 16:427–445CrossRefGoogle Scholar
  17. Carrara A, Crosta G, Frattini P (2003) Geomorphological and historical data in assessing landslide hazard. Eart Surf Processes Land 28:1125–1142CrossRefGoogle Scholar
  18. Cascini L, Critelli S, Gulla G, Di Nocera S (1991) A methodological approach to landslide hazard assessment: a case history. In: Proceedings of 16th international landslide conference. Balkema, Rotterdam, pp 899–904Google Scholar
  19. Chacón J, Irigaray C, Fernández T (1994) Large to middle scale landslide inventory, analysis and mapping with modelling and assessment of derived susceptibility, hazards and risks in a GIS. In: Proceedings of 7th IAEG congress, Balkema, Rotterdam, Holland, pp 4669–4678Google Scholar
  20. Chacón J, Irigaray C, Fernández T (1996) From the inventory to the risk analysis: improvements to a large scale GIS method. In: Chacón J, Irigaray C, Fernández T (eds), Proceedings of 8th international conference and field workshop on landslides, Balkema, Rotterdam, Holland, pp 335–342Google Scholar
  21. Chung CF, Fabbri AG (1999) Probabilistic prediction models for landslide hazard mapping. Photogram Eng Remote Sens 65(12):1389–1399Google Scholar
  22. Chung CF, Fabbri AG, Van Westen CJ (1995) Multivariate regression analysis for landslide hazard zonalition. In: Carrara A, Guzetti F (eds) Geographical informations systems in assessing natural hazards. Kluwer Publishers, DordrechtGoogle Scholar
  23. Clerici A, Perego S, Tellini C, Vescovi P (2006) A GIS-based automated procedure for landslide susceptibility mapping by the conditional Analysis method: the Baganza valley case study (Italian Northern Apennines). Environ Geol 50(7):941–961CrossRefGoogle Scholar
  24. Cochran WG (1977) Sampling techniques, 3rd edn. Wiley. ISBN 0-471-16240-XGoogle Scholar
  25. Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Turner AK, Schuster RL (eds) Landslides investigation and mitigation. Transportation research board, US National Research Council. Special Report 247, Washington, DC, Chapter 3, pp 36–75Google Scholar
  26. Dai FC, Lee CF (2003) A spatiotemporal probabilistic modelling of storm induced shallow landsliding using aerial photographs and logistic regression. Earth Surf Proc Land 28:527–545CrossRefGoogle Scholar
  27. Dai FC, Lee CF, Zhang XH (2001) GIS-based geo-environmental evaluation for urban land-use planning: a case study. Eng Geol 61:257–271CrossRefGoogle Scholar
  28. De Graff JV, Romesburg HC, Ahmad R, McCalpin JP (2012) Producing landslide-susceptibility maps for regional planning in data-scarce regions. Nat Hazards 64:729–749CrossRefGoogle Scholar
  29. DeGraff J, Romesburg H (1980) Regional landslide-susceptibility assessment for wildland management: a matrix approach. In: Coates D, Vitek J (eds) Thresholds in geomorphology. George Allen and Unwin, London, pp 401–414Google Scholar
  30. Delaunay J (1981) Carte de France des zones vulnèrables a des glissements, écroulements, affaissements et effrondrements de terrain. Bureau de Recherches Géologiques et Minières, 81. SGN 567 GEG, 23 p., (in French)Google Scholar
  31. Duman TY, Çan T, Emre Ö, Keçer M, Doğan A, Şerafettin A, Serap D (2005) Landslide inventory of northwestern Anatolia, Turkey. Eng Geol 77(1–2):99–114CrossRefGoogle Scholar
  32. Ercanoglu M, Dagdelenler G, Özsayin E, Alkevli T, Sönmez H, Özyurt NN, Kahraman B, Uçar İ, Çetinkaya S (2016) Application of Chebyshev theorem to data preparation in landslide susceptibility mapping studies: an example from Yenice (Karabük, Turkey) region. J Mt Sci 13(11):1923–1940CrossRefGoogle Scholar
  33. Fell R, Corominas J, Bonnard C, Cascini L, Leroi E, Savage WZ (2008) Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Eng Geol 102:85–98CrossRefGoogle Scholar
  34. Fernández T, Irigaray C, Hamdouni RE, Chacón J (2003) Methodology for landslide susceptibility mapping by means of a GIS. Application to the Contraviesa area (Granada, Spain). Nat Hazards 30:297–308CrossRefGoogle Scholar
  35. Galli M, Ardizzone F, Cardinali M, Guzzetti F, Reichenbach P (2008) Comparing landslide inventory maps. Geomorphology 94:268–289CrossRefGoogle Scholar
  36. Gokceoglu C, Aksoy H (1996) Landslide susceptibility mapping of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing technique. Eng Geol 44:147–161CrossRefGoogle Scholar
  37. Guzzetti F, Cardinali M, Reichenbach P (1996) The influence of structural setting and lithology on landslide type and pattern. Environ Eng Geosci 2(4):531–555CrossRefGoogle Scholar
  38. Guzzetti F, Reichenbach P, Cardinali M, Galli M, Ardizzone F (2005) Probabilistic landslide hazard assessment at the basin scale. Geomorphology 72:272–299CrossRefGoogle Scholar
  39. Guzzetti F, Galli M, Reichenbach P, Ardizzone F, Cardinali M (2006a) Landslide hazard assessment in the Collazzone area, Umbria, central Italy. Nat Hazards Earth Syst Sci 6:115–131CrossRefGoogle Scholar
  40. Guzzetti F, Reichenbach P, Ardizzone F, Cardinali M, Galli M (2006b) Estimating the quality of landslide susceptibility models. Geomorphology 81:166–184CrossRefGoogle Scholar
  41. Guzzetti F, Ardizzone F, Cardinali M, Galli M, Reichenbach P (2008) Distribution of landslides in the Upper Tiber River basin, central Italy. Geomorphology 96:105–122CrossRefGoogle Scholar
  42. Guzzetti F, Ardizzone F, Cardinali M, Galli M, Rossi M, Valigi D (2009) Landslide volumes and landslide mobilization rates in Umbria, central Italy. Earth Planet Sci Lett 279:222–229CrossRefGoogle Scholar
  43. Guzzetti F, Mondini AC, Cardinali M, Fiorucci F, Santangelo M, Chang KT (2012) Landslide inventory maps: new tools for an old problem. Earth Sci Rev 112:42–66CrossRefGoogle Scholar
  44. Holec J, Bednarik M, Sabo M, Minar J, Yilmaz I, Marschalko M (2013) A small-scale landslide susceptibility assessment for the territory of Western Carpathians. Nat Hazards 69(1):1081–1107CrossRefGoogle Scholar
  45. Hovius N, Stark CP, Allen PA (1997) Sediment flux from a mountain belt derived by landslide mapping. Geology 25:231–234CrossRefGoogle Scholar
  46. Hovius N, Stark CP, Hao-Tsu C, Jinn-Chuan L (2000) Supply and removal of sediment in a landslide-dominated mountain belt: Central Range, Taiwan. J Geol 108:73–89CrossRefGoogle Scholar
  47. Hungr O, Leroueil S, Picarelli L (2014) The Varnes classification of landslide types, an update. Landslides 11:167–194CrossRefGoogle Scholar
  48. Irigaray C (1995) Movimientos de ladera: inventoria, analisis y cartografaa de susceptibilidad mediante un Sistema de Informacion Geografica. Aplicacion a las zonas de Colmenar (Ma), Rute (Co) y Montefrio (Gr). Thesis Doctoral, University GranadaGoogle Scholar
  49. Ives JD, Messerli B (1981) Mountain hazard mapping in Nepal: introduction to an applied mountain research project. Mt Res Dev 1(3–4):223–230CrossRefGoogle Scholar
  50. Jade S, Sarkar S (1993) Statistical models for slope instability classification. Eng Geol 36:91–98CrossRefGoogle Scholar
  51. Keaton JR, DeGraff JV (1996) Surface observation and geologic mapping. In: Turner AK, Schuster RL (eds) Landslides investigation and mitigation: National Research Council Transportation Research Board Special Report, vol 247, pp 178–230Google Scholar
  52. Lee S, Min K (2001) Statistical analyses of landslide susceptibility at Yongin, Korea. Environ Geol 40:1095–1113CrossRefGoogle Scholar
  53. Malamud BD, Turcotte DL, Guzzetti F, Reichenbach P (2004a) Landslides, earthquakes and erosion. Earth Planet Sci Lett 229:45–59CrossRefGoogle Scholar
  54. Malamud BD, Turcotte DL, Guzzetti F, Reichenbach P (2004b) Landslide inventories and their statistical properties. Earth Surf Proc Land 29(6):687–711CrossRefGoogle Scholar
  55. McCalpin J (1984) Preliminary age classification of landslides for inventory mapping. In: Proceedings of the 21st engineering geology and soils engineering symposium, University, Moscow, ID, pp 99–120Google Scholar
  56. Nefeslioglu HA, Gokceoglu C, Sonmez H (2008) An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps. Eng Geol 97:171–191CrossRefGoogle Scholar
  57. Parker RN, Densmore AL, Rosser NJ, de Michele M, Li Y, Huang R, Whadcoat S, Petley DN (2011) Mass wasting triggered by the 2008 Wenchuan earthquake is greater than orogenic growth. Nat Geosci 4(7):449–452CrossRefGoogle Scholar
  58. Peck R, Olsen C, Devore JL (2008) Introduction to statistics and data analysis, 3rd edn. Cengage Learning. ISBN 0-495-55783-8Google Scholar
  59. Pratt JW, Raiffa H, Schaifer R (1995) Introduction to statistical decision theory. MIT Press, Cambridge, MA. MR1326829Google Scholar
  60. Radbruch-Hall DH, Colton RB, Davies WE, Lucchitta I, Skipp BA, Varnes DJ (1982) Landslide overview map of the conterminous United States. U.S. Geological Survey Professional Paper, 1183. WWW page 25 p
  61. Remondo J, Gonzalez-Diez A, Teran JRD, Cendrero A (2003) Landslide susceptibility models utilising spatial data analysis techniques. A case study from the lower Deba Valley, Guipúzcoa (Spain). Nat Hazards 30:267–279CrossRefGoogle Scholar
  62. Rengers N, Van Westen CJ, Chacón J, Irigaray C (1998) Draft for the chapter on the application of digital techniques for natural hazard zonation, Report on Mapping of Natural Hazards, International Association of Engineering Geology. Commission No. 1 on Engineering Geological MappingGoogle Scholar
  63. Rupke J, Cammeraat E, Seijmonsbergen AC, Van Westen CJ (1988) Engineering geomorphology of the widentobel catchment, Switzerland: a geomorphological inventory system applied to geotechnical appraisal of the slope stability. Eng Geol 26:33–68CrossRefGoogle Scholar
  64. Santacana N, Baeza B, Corominas J, Paz A, Marturia J (2003) A GIS based multivariate statistical analysis for shallow landslide susceptibility mapping in la Pobla de Lillet area (Eastern Pyrenees, Spain). Nat Hazards 30:281–295CrossRefGoogle Scholar
  65. Soeters R, Van Westen CJ (1996) Slope instability, recognition, analysis, and zonation. In: Turner AK, Schuster RL (eds) Landslides—investigation and mitigation, transportation research board special report 247. National Academy Press, Washington, DC, pp 129–177Google Scholar
  66. Suzen ML, Doyuran V (2004) Data driven bivariate landslide susceptibility assessment using geographical information systems: a method and application to Asarsuyu catchment, Turkey. Eng Geol 71:303–321CrossRefGoogle Scholar
  67. Trigila A, Iadanza C, Spizzichino D (2010) Quality assessment of the Italian landslide inventory using GIS processing. Landslides 7:455–470CrossRefGoogle Scholar
  68. Van Westen CJ, Soeters R, Sijmons K (2000) Digital geomorphological landslide hazard mapping of the Alpago area, Italy. Int J Appl Earth Obs Geoinf 2(1):51–59CrossRefGoogle Scholar
  69. Van Westen CJ, van Asch TWJ, Soeters R (2006) Landslide hazard and risk zonation—why is it still so difficult? Bull Eng Geol Environ 65:167–184CrossRefGoogle Scholar
  70. Van Westen CJ, Castellanos Abella EA, Sekhar LK (2008) Spatial data for landslide susceptibility, hazards and vulnerability assessment: an overview. Eng Geol 102:112–131CrossRefGoogle Scholar
  71. Varnes DJ (1978) Slope movement types and processes. In: Schuster RL, Krizek RJ (eds) Landslides, analysis and control, special report 176: transportation research board. National Academy of Sciences, Washington, DC, pp 11–33Google Scholar
  72. Ward T, Ruh-Ming L, Simons D (1982) Mapping landslide hazard in forest watershed. J Geotech Eng Div 108(GT2):319–324Google Scholar
  73. Wieczorek GF (1984) Preparing a detailed landslide-inventory map for hazard evaluation and reduction. Assoc Eng Geol Bull 21(3):337–342Google Scholar
  74. Yilmaz I (2009a) a. Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat–Turkey). Comput Geosci 35(6):1125–1138CrossRefGoogle Scholar
  75. Yilmaz I (2009b) b. A case study from Koyulhisar (Sivas–Turkey) for landslide susceptibility mapping by artificial neural networks. Bull Eng Geol Environ 68(3):297–306CrossRefGoogle Scholar
  76. Yilmaz I (2010a) Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey: conditional probability, logistic regression, artificial neural networks, and support vector machine. Environ Earth Sci 61(4):821–836CrossRefGoogle Scholar
  77. Yilmaz I (2010b) The effect of the sampling strategies on the landslide susceptibility mapping by conditional probability (CP) and artificial neural networks (ANN). Environ Earth Sci 60(3):505–519CrossRefGoogle Scholar
  78. Yilmaz I, Keskin I (2009) GIS based statistical and physical approaches to landslide susceptibility mapping (Sebinkarahisar, Turkey). Bull Eng Geol Env 68(4):459–471CrossRefGoogle Scholar
  79. Yilmaz I, Yildirim M (2006) Structural and geomorphological aspects of the Kat landslides (Tokat—Turkey), and susceptibility mapping by means of GIS. Environ Geol 50(4):461–472CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Geological Engineering SivasCumhuriyet UniversitySivasTurkey
  2. 2.Geological Engineering DepartmentHacettepe UniversityAnkaraTurkey

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