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2013 | OriginalPaper | Buchkapitel

The Susceptibility Map for Landslides with Shallow Initiation in the Emilia Romagna Region (Italy)

verfasst von : Mauro Generali, Marco Pizziolo

Erschienen in: Landslide Science and Practice

Verlag: Springer Berlin Heidelberg

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Abstract

The Emilia Romagna Region (RER) is probably one of the most landslide susceptible regions of the world, with ~24 % of the mountain sector covered by landslide accumulations. The regularly updated 1:10,000 Landslides Inventory Map (LIM), managed by the Regional Geological Survey, counts more than 70,000 landslides. Nowadays most land-use planning is based on LIM but this has several intrinsic shortcomings, mainly due to its scale and forecast significativity. This paper presents the methods we used to compile a detailed susceptibility map for the whole RER Apennines.

The triggering mechanism of the most common landslides phenomena in RER, disregarding of the subsequent evolution, is characterized by a first movements that may be described as “shallow phenomena” involving the upper part of the landslides (depletion areas). For this reasons we developed a model for the areas “outside” the LIM mapped landslides aimed to identify the triggering areas for future landslides. For this statistical analysis we used Bivariate Logistic Regression methods. As our aim was to predict triggering phenomena, we calibrated the model on the depletion areas, selected using a semi-automatic GIS procedure. The resulting map can be used for LIM verification and updating and adds it a forecast connotation useful for land use planning; nevertheless it has to be used by experienced users, for this purpose the model advantage and shortcomings will be discussed.

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Vorheriges Kapitel Slope Angle as Indicator Parameter of Landslide Susceptibility in a Geologically Complex Area

Nächstes Kapitel Methods for Shallow Landslides Susceptibility Mapping: An Example in Oltrepo Pavese

The State of activity definition doesn’t correspond to that used by Varnes (1978), WP/WLI (1993) or Cruden and Varnes (1996), but assume as active a landslide that has shown activity in the last ~30 years.

We used the Zevenbergen and Thorne (1987) algorithm that performs better then others on sharp slope changes.

For the flow accumulation we used the D∞ algorithm (Tarboton 1997), that performs much better then D8 to identify the accumulation/dispersion of water flow along the hillslopes.

Akgün A, Fikri B (2007) GIS-based landslide susceptibility for Arsin-Yomra (Trabzon, North Turkey) region. Environ Earth Sci 51(8):1377–1387

Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58:21–44CrossRef

APAT (2007) Rapporto sulle frane in Italia. Il progetto IFFI: metodologia, risultati e rapporti regionali. Rapporto 78/2007, Roma

Atkinson PM, Massari R (1998) Generalized linear modelling of susceptibility to landsliding in the central Apennines, Italy. Comput Geosci 24(4):373–385CrossRef

Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65:15–31CrossRef

Bai SB, Wang J, Pozdnoukhov A, Kanevski M (2008a) Validation of spatial prediction models for landslide susceptibility maps. In: Proceedings of the 8th international symposium on spatial accuracy assessment in natural resources and environmental sciences, Shanghai, 25–27 June 2008, pp 280–286

Bai SB, Wang J, Zhang F Y, Pozdnoukhov A, Kanevski M (2008b) Prediction of landslide susceptibility using logistic regression: a case study in Bailongjiang River Basin. In: Proceedings of the fifth international conference on fuzzy systems and knowledge discovery, Vol4, China, pp 647–651

Begueria S, Lorente A (1999) Landslide hazard mapping by multivariate statistics; comparison of methods and case study in the Spanish Pyrenees. The Damocles Project Work, Contract No EVG1-CT 1999–00007. Technical Report, 20p

Bertolini G, Canuti P, Casagli N, DE Nardo MT, Egidi D, Galliani G, Genevois R, Mainetti M, Pignone R, Pizziolo M, Pomi L, Zinoni F (2002) Carta della Franosità della Regione Emilia-Romagna ai fini di Protezione Civile. Regione Emilia-Romagna e CNR-GNDCI, 110p

Bertolini G, Pizziolo M (2008) Risk assessment strategies for the reactivation of earth flows in the Northern Apennines (Italy). Eng Geol 102(3–4):178–192CrossRef

Cardinali M, Carrara A, Guzzetti F, Reichenbach P (2002) Landslide hazard map of the upper Tiber River basin, Italy. Publication GNDCI no 2634. SystemCart, Roma

Carrara A (1983) Multivariate models for landslide hazard evaluation. Math Geol 15(3):403–427CrossRef

Carrara A, Cardinali M, Detti R, Guzzetti F, Pasqui V, Reichenbach P (1990) Geographical information systems and multivariate models in landslide hazard evaluation. In: ALPS 90 Alpine landslide practical seminar, sixth international conference and field workshop on landslides, Università degli Studi di Milano, Milan, 31 Aug–12 Sept, pp 17–28

Carrara A, Cardinali M, Guzzetti F, Reichenbach P (1995) GIS technology in mapping landslide hazard. In: Guzzetti F, Carrara A (eds) Geographical information systems in assessing natural hazards. Kluwer Academic, Dordrecht, pp 135–175CrossRef

Cerrina Feroni A, Martelli L, Martinelli P, Ottria G (2002) Structural-Geological map of the Emilia-Romagna Apennines. Selca Ed, Firenze

Chung CF, Kojima H, Fabbri AG (2002) Stability analysis of prediction models for landslide hazard mapping. In: Allison RJ (ed) Applied geomorphology: theory and practice. Wiley, London, pp 1–19

Chung CF, Fabbri AG (1999) Probabilistic prediction model for landslide hazard mapping. Photogramm Eng Remote Sensing 65(12)

Chung CF, Fabbri AG (2003a) Validation of spatial prediction models for landslide hazard mapping. Nat Hazards 30:451–472CrossRef

Chung CF, Fabbri AG (2003b) On some weak points of quantitative landslide hazard zonation. In: Proceedings of the IAMG 2003, Portsmouth, 7–12 Sept

Chung CF, Fabbri AG (2005) Systematic procedures of landslide hazard mapping for risk assessment using spatial prediction models. In: Glade T, Anderson M, Crozier MJ (eds) Landslide hazard and risk. Wiley, Chichester, pp 139–174

Chung CF (2006) Using likelihood ratio function for modeling the conditional probability of occurrence of future landslides for risk assessment. Comput Geosci 32(8):1052–1068CrossRef

Conrad O (2006) SAGA – Program structure and current state of implementation. In: Böhner J, McCloy KR, Strobl J (eds) SAGA – Analysis and modelling applications, vol 115. Verlag Erich Goltze GmbH, Göttingen, pp 39–52

Crosta G, Frattini P, Sterlacchini S (2001) Valutazione e gestione del rischio da frana. Regione Lombardia, Milano

Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Turner AK, Schuster RL (eds) Landslides: investigation and mitigation, Special report. National Academy Press, Washington, DC, pp 36–75

Dai CF, Lee CF (2003) A spatiotemporal probabilistic modeling of storm-induced shallow landslide using aerial photographs and logistic regression. Earth Surf Proc Land 28:527–545CrossRef

Dai FC, Lee CF, Ngai YY (2002) Landslide risk assessment and management: an overview. Eng Geol 64(1):65–87CrossRef

Gallant JC, Wilson JP (2000) Terrain analysis: principles and applications. Wiley, New York, p 472

Glade T (2001) Landslide hazard assessment and historical landslide data – an inseparable couple? In: Glade T, Frances F, Albini P (eds) The use of historical data in natural hazard assessments, Advances in natural and technological hazards research. Kluwer Academic, Dordrecht, pp 153–168CrossRef

Gorsevski PV, Gessler P, Foltz RB (2000) Spatial prediction of landslide hazard using logistic regression and GIS. In: Proceedings of the 4th international conference on integrating GIS and environmental modeling. Alberta, 9p

Guzzetti F, Carrara A, Cardinali M, Reichenbach P (1999) Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy. Geomorphology 31:181–216CrossRef

Hosmer DW, Lemeshow S (1989) Applied regression analysis. Wiley, New York, p 307

Hutchinson JN, Bhandari RK (1971) Undrained loading, a fundamental mechanism of mudflow and other mass movements. Geotecnique 21:353–358CrossRef

Hutchinson JN (1988) Morphological and geotechnical parameters of landslides in relation to geology and hydrogeology. In: Proceedings of the 5th international symposium on landslides, Vol 1. Lausanne, pp 3–35

Hutchinson JN (1995) Landslide hazard assessment. In: Bell DH, Balkema AA (eds) Landslides. Balkema, Rotterdam, pp 1805–1841

King G, Zeng L (2001) Logistic regression in rare events data. Political Anal 9:137–163CrossRef

Jenness J (2006) Topographic Position Index (tpi_jen.avx) extension for ArcView 3.x, v. 1.3a. Jenness Enterprises. http://www.jennessent.com/arcview/tpi.htm

Lee S (2005) Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int J Remote Sens 26(7):1477–1491CrossRef

Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin. Korea Environ Geol 40:1095–1113CrossRef

Lee CT, Huang CC, Lee JF, Pan KL, Lin ML, Dong JJ (2008) Statistical approach to storm event-induced landslides susceptibility. Nat Hazards Earth Syst Sci 8:941–960CrossRef

Leroueil S, Locat J, Vaunat J, Picarelli L, Lee H, Faure R (1996) Geotechnical characterization of slope movements. In: Proceedings of the 7th international symposium on landslides, Vol 1. Trondheim, pp 53–74

Moore ID, Grayson RB, Ladson AR (1991) Digital terrain modelling: a review of hydrological, geomorphological and biological applications. Hydrol Proc 5:3–30CrossRef

O’Callaghan JF, Mark DM (1984) The extraction of drainage networks from digital elevation data. Comput Vision Graphics Image Proc 28:328–344

Ohlmacher CG, Davis CJ (2003) Using multiple regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng Geol 69:331–343CrossRef

Rossi M, Guzzetti F, Reichenbach P, Mondini AC, Peruccacci S (2010) Optimal landslide susceptibility zonation based on multiple forecasts. Geomorphology 114:129–142CrossRef

Srinivasan R, Engel BA (1991) Effect of slope prediction methods on slope and erosion estimates. Appl Eng Agric 7(6):79–783

Suzen ML, Doyuran V (2003) A comparison of the GIS based landslide susceptibility assessment methods: multivariate versus bivariate. Environ Geol 45(8):665–679

Swets JA (1988) Measuring the accuracy of diagonstic systems. Science 204(4857):1285–1293CrossRef

Tarboton DG (1997) A new method for the determination of flow directions and upslope areas in grid digital elevation models. Water Res Res 33(2):309–319CrossRef

Thierya Y, Maleta JP, Sterlacchini S, Puissant A, Maquairea O (2007) Landslide susceptibility assessment by bivariate methods at large scales: application to a complex mountainous environment. Geomorphology 92(1–2):38–59CrossRef

Vanacker V, Vanderschraeghe M, Govers G, Willems E, Poesen J, Deckers J, De Bievre B (2003) Linking hydrological, infinite slope stability and land-use change models through GIS for assessing the impact of deforestation on slope stability in high Andes watersheds. Geomorphology 52:299–315CrossRef

Van Den Eeckhaut M, Reichenbach P, Guzzetti F, Rossi M, Poesen J (2009) Combined landslide inventory and susceptibility assessment based on different mapping units: an example from the Flemish Ardennes, Belgium. Nat Haz Earth Syst Sci 9:507–521CrossRef

Van Den Eeckhaut M, Vanwalleghem T, Poesen J, Govers G, Verstraeten G, Vandekerckhove L (2006) Prediction of landslide susceptibility using rare events logistic regression: a case-study in the Flemish Ardennes (Belgium). Geomorphology 76:392–410CrossRef

Van Westen CJ, van Asch TWJ, Soeters R (2006) Landslide hazard and risk zonation – why is it still so difficult? B Eng Geol Environ 65:167–184CrossRef

Varnes DJ (1978) Slope movement types and processes. In: Schuster RL, Krizek RJ (eds) Landslides analysis and control: national research council, vol 176, Transportation research board, Special report. Transportation Research Board, Washington, DC, pp 11–33

Wang HB, Sassa K, Xu WY (2007) Assessment of landslide susceptibility using multivariate.logistic regression: a case study in Southern Japan. Environ Eng Geosci 13:183–192CrossRef

Wang HB, Liu G, Xu WY, Wang G (2005) GIS-based landslide hazard assessment: an overview. Prog Phys Geography 29:548–567CrossRef

Weiss A (2001) Topographic position and landforms analysis. In: Poster presentation. ESRI User Conference, San Diego

WP/WLI (1993) A suggested method for describing the activity of a landslide. Bull Int Ass Eng Geol 47:53–57CrossRef

Zevenbergen LW, Thorne CR (1987) Quantitative analysis of land surface topography. Earth Surf Proc Landf 12:47–56CrossRef

Zêzere JL (2002) Landslide susceptibility assessment considering landslide typology, a case study in the area north of Lisbon (Portugal). Nat Hazard Earth Syst Sci 2:73–82CrossRef

Titel: The Susceptibility Map for Landslides with Shallow Initiation in the Emilia Romagna Region (Italy)
verfasst von: Mauro Generali
Marco Pizziolo
Verlag: Springer Berlin Heidelberg
Buch: Landslide Science and Practice
Print ISBN: 978-3-642-31324-0

Electronic ISBN: 978-3-642-31325-7

Copyright-Jahr: 2013
DOI: https://doi.org/10.1007/978-3-642-31325-7_57

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