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Exploring spatial non-stationarity in the relationships between landslide susceptibility and conditioning factors: a local modeling approach using geographically weighted regression

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Abstract

Landslide susceptibility is the likelihood of landslide occurrence, in a specific place and time. The identification of the potential relationships between landslide susceptibility and conditioning factors is very important towards landslide hazard mitigation. In this paper, we implement a local statistical analysis model geographically weighted regression, in two catchment areas located in northern Peloponnese, Greece. For this purpose, we examined the following eight conditioning factors: elevation, slope, aspect, lithology, land cover, proximity to the drainage network, proximity to the road network, and proximity to faults. Moreover, the relationship between these factors and landsliding in the study area is examined. The local statistical analysis model was also evaluated by finding its differences with the performance of a standard global statistical model logistic regression. The results indicated that the global statistical model can be enhanced by the application of a local model. The outputs of the proposed approach favored a better understanding of the factors influencing landslide occurrence and may be beneficial to local authorities and decision-makers dealing with the mitigation of landslide hazard.

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References

  • Akaike H (1973) Information theory and an extension of the maximum likelihood principle. In: Petrov BN, Csaki F (eds) Proceedings of the 2nd international symposium on information theory, pp 267–281

  • Akgun A (2012) A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at İzmir, Turkey. Landslides 9(1):93–106

    Google Scholar 

  • Allison PD (2012) Logistic regression using SAS: theory and application. SAS Institute, Cary

    Google Scholar 

  • Armijo R, Meyer B, King G, Rigo A, Papanastassiou D (1996) Quaternary evolution of the Corinth Rift and its implications for the Late Cenozoic evolution of the Aegean. Geophys J Int 126(1):11–53

    Google Scholar 

  • Avtar R, Singh CK, Singh G, Verma RL, Mukherjee S, Sawada H (2011) Landslide susceptibility zonation study using remote sensing and GIS technology in the Ken-Betwa River Link area, India. Bull Eng Geol Environ 70:595–606

    Google Scholar 

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

    Google Scholar 

  • Ayalew L, Yamagishi H, Maruib H, Takami K (2005) Landslides in Sado Island of Japan: part II. GIS-based susceptibility mapping with comparisons of results from two methods and verifications. Eng Geol 81(4):432–445

    Google Scholar 

  • Baeza C, Corominas J (2001) Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surf Process Landf 26:1251–1263

    Google Scholar 

  • Bai SB, Wang J, Thiebes B, Cheng C, Chang ZY (2014) Susceptibility assessments of the Wenchuan earthquake-triggered landslides in Longnan using logistic regression. Environ Earth Sci 71:731–743

    Google Scholar 

  • Benjamini Y, Yekutieli D (2001) The control of the false discovery rate in multiple testing under dependency. Ann Stat 29(4):1165–1188

    Google Scholar 

  • Brabb EE (1984) Innovative approaches to landslide hazard mapping. In: Proceedings of the 4th international symposium on landslides, pp 307–324

  • Briole P, Rigo A, Lyon-Caen H, Ruegg JC, Papazissi K, Mitsakaki C, Balodimou A, Veis G, Hatzfeld D, Deschamps A (2000) Active deformation of the Corinth Rift, Greece: results from repeated global position system surveys between 1990 and 1995. J Geophys Res Solid Earth 105(B11):25606–25626

    Google Scholar 

  • Brunsdon C, Fotheringham AS, Charlton M (1996) Geographically weighted regression: a method for exploring spatial nonstationarity. Geogr Anal 28(4):281–298

    Google Scholar 

  • Carrara A, Cardinali M, Detti R, Guzzetti F, Pasqui V, Reichenbach P (1991) GIS techniques and statistical models in evaluating landslide hazard. Earth Surf Process Landf 16:427–445

    Google Scholar 

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

    Google Scholar 

  • Chalkias C, Papadopoulos AG, Kalogeropoulos K, Tambalis K, Psarra G, Sidossis L (2013) Geographical heterogeneity of the relationship between childhood obesity and socio-environmental status: empirical evidence from Athens, Greece. Appl Geogr 37:34–43

    Google Scholar 

  • Chalkias C, Ferentinou M, Polykretis C (2014a) GIS-based landslide susceptibility mapping on the Peloponnese Peninsula, Greece. Geosciences 4:176–190

    Google Scholar 

  • Chalkias C, Kalogirou S, Ferentinou M (2014b) Landslide susceptibility map of the Peloponnese peninsula in South Greece. J Maps 10(2):211–222

    Google Scholar 

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

    Google Scholar 

  • Da Silva AR, Fotheringham AS (2016) The multiple testing issue in geographically weighted regression. Geogr Anal 48:233–247

    Google Scholar 

  • Dagdelenler G, Nefeslioglu HA, Gokceoglu C (2015) Modification of seed cell sampling strategy for landslide susceptibility mapping: an application from the eastern part of the Gallipoli Peninsula (Canakkale, Turkey). Bull Eng Geol Environ 75(2):575–590

    Google Scholar 

  • Dahal RK, Bhandary NP, Hasegawa S, Yatabe R (2014) Topo-stress based probabilistic model for shallow landslide susceptibility zonation in the Nepal Himalaya. Environ Earth Sci 71:3879–3892

    Google Scholar 

  • Demir G, Aytekin M, Akgün A, Ikizler SB, Tatar O (2013) A comparison of landslide susceptibility mapping of the eastern part of the North Anatolian Fault Zone (Turkey) by likelihood-frequency ratio and analytic hierarchy process methods. Nat Hazards 65:1481–1506

    Google Scholar 

  • Devoto S, Mantovani M, Pasuto A, Piacentini D, Soldati M (2015) Long-term monitoring to support landslide inventory maps: the case of the north-western coast of the island of Malta. Eng Geol Soc Territ 2:1307–1310

    Google Scholar 

  • Du S, Wang Q, Guo L (2014) Spatially varying relationships between land-cover change and driving factors at multiple sampling scales. J Environ Manag 137:101–110

    Google Scholar 

  • Erener A, Düzgün HSB (2010) Improvement of statistical landslide susceptibility mapping by using spatial and global regression methods in the case of More and Romsdal (Norway). Landslides 7(1):55–68

    Google Scholar 

  • Ferentinos G, Papatheodorou G, Collins MB (1988) Sediment Transport processes on an active submarine fault escarpment: Gulf of Corinth, Greece. Marine Geology 83(1-4):43–61

  • Fernández-Blanco D, de Gelder G, Lacassi R, Armijo R (2019) A new crustal fault formed the modern Corinth rift. Earth Sci Rev 199:102919

    Google Scholar 

  • Feuillet T, Coquin J, Mercier D, Cossart E, Decaulne A, Páll Jónsson H, Sæmundsson Þ (2014) Focusing on the spatial non-stationarity of landslide predisposing factors in northern Iceland: do paraglacial factors vary over space?. Progress in Physical Geography, pp 1–24

  • Fotheringham AS, Charlton ME, Brunsdon C (2001) Spatial variations in school performance: a local analysis using geographically weighted regression. Geogr Environ Model 5:43–66

    Google Scholar 

  • Fotheringham AS, Brunsdon C, Charlton M (2002) Geographically weighted regression: the analysis of spatially varying relationships. Wiley, Chichester

    Google Scholar 

  • Froude MJ, Petley DN (2018) Global fatal landslide occurrence from 2004 to 2016. Nat Hazards Earth Syst Sci 18:2161–2181

    Google Scholar 

  • Gutiérrez F, Soldati M, Audemard F, Balteanu D (2010) Recent advances in landslide investigation: issues and perspectives. Geomorphology 124:95–101

    Google Scholar 

  • Harris R, Singleton A, Grose D, Brunsdon C, Longley P (2010) Grid-enabling geographically weighted regression: a case study of participation in higher education in England. Trans GIS 14(1):43–61

    Google Scholar 

  • Hasekioǧullari GD, Ercanoglu M (2012) A new approach to use AHP in landslide susceptibility mapping: a case study at Yenice (Karabuk, NW Turkey). Nat Hazards 63(2):1157–1179

    Google Scholar 

  • He Y, Beighley RE (2008) GIS-based regional landslide susceptibility mapping: a case study in southern California. Earth Surf Process Landf 33(3):380–393

    Google Scholar 

  • Highland LM, Bobrowsky P (2008) The landslide handbook—a guide to understanding landslides. United States Geological Survey (USGS), Circular 1325, Reston, Virginia, USA

  • HMGS (1989) General use map of Greece, 1:50,000, Aiyion, Dhervenion, Dhafni and Kandhila sheets

  • Huang J, Huang Y, Pontius RG Jr, Zhang Z (2015) Geographically weighted regression to measure spatial variations in correlations between water pollution versus land use in a coastal watershed. Ocean Coast Manag 103:14–24

    Google Scholar 

  • Huang F, Yin K, Huang J, Gui L, Wang P (2017) Landslide susceptibility mapping based on self-organizing-map network and extreme learning machine. Eng Geol 223:11–22

    Google Scholar 

  • Hungr O, Leroueil S, Picarelli L (2014) The Varnes classification of landslide types, an update. Landslides 11(2):167–194

    Google Scholar 

  • IGME (1983) Geological map of Greece, scale 1:500,000

  • IGME (1993) Geological map of Greece, scale 1:50,000, Aiyion, Dhervenion, Dhafni and Kandhila sheets

  • Karymbalis E, Ferentinou M, Giles PT (2018) Use of morphometric variables and self-organizing maps to identify clusters of alluvial fans and catchments in the North Peloponnese, Greece. Geol Soc Spec Publ 440(1):45–64

    Google Scholar 

  • Karymbalis E, Papanastassiou D, Gaki-Papanastassiou K, Ferentinou M, Chalkias C (2016) Late Quaternary rates of stream incision in Northeast Peloponnese, Greece. Front Earth Sci 10(3):455–478

    Google Scholar 

  • Kavoura K, Sabatakakis N (2020) Investigating landslide susceptibility procedures in Greece. Landslides 17:127–145

    Google Scholar 

  • Kavzoglu T, Sahin EK, Colkesen I (2014) Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression. Landslides 11:425–439

    Google Scholar 

  • Kuo C-C, Wardrop N, Chang C-T, Wang H-C, Atkinson PM (2017) Significance of major international seaports in the distribution of murine typhus in Taiwan. PLoS Negl Trop Dis 11(3):1–20

    Google Scholar 

  • Laboratory of Engineering Geology, Department of Geology, University of Patras (2018) Landslide Inventory Database. http://www.geoarch.gr/. Accessed 15 Nov 2018

  • Leeder R, Mark F, Gawthorpe L, Kranis H, Loveless S, Pedentchouk N, Skourtsos E, Turner J, Andrews E, Stamatakis M (2012) A “great deepening”: chronology of rift climax, Corinth rift, Greece. Geology 40(11):999–1002

    Google Scholar 

  • Li Y, Chen G, Tang C, Zhou G, Zheng L (2012) Rainfall and earthquake-induced landslide susceptibility assessment using GIS and artificial neural network. Nat Hazards Earth Syst Sci 12(8):2719–2729

    Google Scholar 

  • Listo FDLR, Carvalho Vieira B (2012) Mapping of risk and susceptibility of shallow-landslide in the city of Sao Paulo, Brazil. Geomorphology 169–170:30–44

    Google Scholar 

  • Magliulo P, Lisio A, Russo F, Zelano A (2008) Geomorphology and landslide susceptibility assessment using GIS and bivariate statistics: a case study in southern Italy. Nat Hazards 47:411–435

    Google Scholar 

  • Martino S, Bozzano F, Caporossi P, D’Angiò D, Della Seta M, Esposito C, Fantini A, Fiorucci M, Giannini LM, Iannucci R, Marmoni GM, Mazzanti P, Missori C, Moretto S, Piacentini D, Rivellino S, Romeo RW, Sarandrea P, Schilirò L, Troiani F, Varone C (2019) Impact of landslides on trasportation routes during the 2016-2017 Central Italy seismic sequence. Landslides 16(6):1221–1241

    Google Scholar 

  • McNeil LC, Collier REL, De Martini PM, Pantosti D, D’Adezio G (2005) Recent history of the eastern Eliki fault, gulf of Corinth: geomorphology, palaeoseismology and impact on palaeoenvironments. Geophys J Int 161:154–166

    Google Scholar 

  • Nakaya T, Charlton M, Lewis P, Brundson C, Yao J, Fotheringham S (2014) GWR4, Windows application for geographically weighted regression modelling. Department of Geography-Ritsumeikan University, NCG-National University of Ireland, School of Geography & Geosciences-University of St. Andrews

  • Papathanassiou G, Valkaniotis S, Ganas A, Pavlides S (2013) GIS-based statistical analysis of the spatial distribution of earthquake-induced landslides in the island of Lefkada, Ionian Islands, Greece. Landslides 10:771–783

    Google Scholar 

  • Park DW, Nikhil NV, Lee SR (2013) Landslide and debris flow susceptibility zonation using TRIGRS for the 2011 Seoul landslide event. Nat Hazards Earth Syst Sci 13:2833–2849

    Google Scholar 

  • Piacentini D, Troiani F, Soldati M, Notarnicola C, Savelli D, Schneiderbauer S, Strada C (2012) Statistical analysis for assessing shallow-landslide susceptibility in South Tyrol (South-Eastern Alps, Italy). Geomorphology 151–152:196–206

    Google Scholar 

  • Pnevmatikos JD, Katsoulis BD (2006) The changing rainfall regime in Greece and its impact on climatological means. Meteorol Appl 13:331–345

    Google Scholar 

  • Polykretis C, Ferentinou M, Chalkias C (2015) A comparative study of landslide susceptibility mapping using landslide susceptibility index and artificial neural networks in the Krios River and Krathis River catchments (northern Peloponnesus, Greece). Bull Eng Geol Environ 74:27–45

    Google Scholar 

  • Rigo A, Lyon-Caen H, Armijo R, Deschamps A, Hatzfeld D, Makropoulos K, Papadimitriou P, Kassaras I (1996) A microseismic study in the western part of the Gulf of Corinth (Greece): implications for large-scale normal faulting mechanisms. Geophys J Int 126(3):663–688

    Google Scholar 

  • Rodrigues M, de la Riva J, Fotheringham S (2014) Modeling the spatial variation of the explanatory factors of human-caused wildfires in Spain using geographically weighted logistic regression. Appl Geogr 48:52–63

    Google Scholar 

  • Rozos D, Bathrellos GD, Skillodimou HD (2011) Comparison of the implementation of rock engineering system and analytic hierarchy process methods, upon landslide susceptibility mapping, using GIS: a case study from the eastern Achaia County of Peloponnesus, Greece. Environ Earth Sci 63:49–63

    Google Scholar 

  • Santacana N, Baeza B, Corominas J, de 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 30:281–295

    Google Scholar 

  • Sdao F, Lioi DS, Pascale S, Caniani D, Mancini IM (2013) Landslide susceptibility assessment by using a neuro-fuzzy model: a case study in the Rupestrian heritage rich area of Matera. Nat Hazards Earth Syst Sci 13:395–407

    Google Scholar 

  • Shafizadeh-Moghadama H, Helbicha M (2015) Spatiotemporal variability of urban growth factors: a global and local perspective on the megacity of Mumbai. Int J Appl Earth Obs Geoinf 35:187–198

    Google Scholar 

  • Su S, Xiao R, Zhang Y (2011) Multi-scale analysis of spatially varying relationships between agricultural landscape patterns and urbanization using geographically weighted regression. Appl Geogr 32:360–375

    Google Scholar 

  • Trgovac AB, Kedron PJ, Bagchi-Sen S (2015) Geographic variation in male suicide rates in the United States. Appl Geogr 62:201–209

    Google Scholar 

  • Tsagas D (2011) Geomorphological observations, and gravity movements in northern Peloponnesus. PhD dissertation, National and Kapodistrian University of Athens

  • Tu J (2013) Spatial variations in the relationships between land use and water quality across an urbanization gradient in the watersheds of northern Georgia, USA. Environ Manag 51:1–17

    Google Scholar 

  • Vega-Corredor MC, Opadeyi J (2014) Hydrology and public health: linking human leptospirosis and local hydrological dynamics in Trinidad, West Indies. Earth Perspect 1:3

    Google Scholar 

  • Wu X, Ren F, Niu R (2014) Landslide susceptibility assessment using object mapping units, decision tree, and support vector machine models in the three gorges of China. Environ Earth Sci 71:4725–4738

    Google Scholar 

  • Xu S, Wu C, Wang L, Gonsamo A, Shen Y, Niu Z (2015) A new satellite-based monthly precipitation downscaling algorithm with non-stationary relationship between precipitation and land surface characteristics. Remote Sens Environ 162:119–140

    Google Scholar 

  • Youssef AM, Al-Kathery M, Pradhan B (2015a) Landslide susceptibility mapping at Al-Hasher area, Jizan (Saudi Arabia) using GIS-based frequency ratio and index of entropy models. Geosci J 19(1):113–134

    Google Scholar 

  • Youssef AM, Pradhan B, Jebur MN, El-Harbi HM (2015b) Landslide susceptibility mapping using ensemble bivariate and multivariate statistical models in Fayfa area, Saudi Arabia. Environ Earth Sci 73:3745–3761

    Google Scholar 

  • Zelilidis A (2000) Drainage evolution in a rifted basin, Corinth graben, Greece. Geomorphology 35:69–85

    Google Scholar 

  • Zhang C, Tang Y, Xu X, Kiely G (2011) Towards spatial geochemical modelling: use of geographically weighted regression for mapping soil organic carbon contents in Ireland. Appl Geochem 26(7):1239–1248

    Google Scholar 

  • Zhou C, Yin K, Cao Y, Ahmed B, Li Y, Catani F, Pourghasemi HR (2018) Landslide susceptibility modeling applying machine learning methods: a case study from Longju in the Three Gorges Reservoir area, China. Comput Geosci 112:23–37

    Google Scholar 

  • Zygouri V, Koukouvelas K (2019) Landslides and natural dams in the Krathis River, north Peloponnese, Greece. Bull Eng Geol Environ 78:207–222

    Google Scholar 

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Funding

The paper is also part of the UNIMORE Project “Hazard and vulnerability assessment—The path to identifying risk” funded by the EUR-OPA Major Hazards Agreement of the Council of Europe, 2018-19 (scientific responsible: Mauro Soldati).

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Authors and Affiliations

  1. Department of Geography, Harokopio University, El. Venizelou 70, 17671, Athens, Greece

    Christos Chalkias, Christos Polykretis & Efthimios Karymbalis

  2. Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via G. Campi, 103, 41125, Modena, Italy

    Mauro Soldati & Alessandro Ghinoi

  3. Department of Civil Engineering Science, University of Johannesburg, Auckland Park Kingsway Campus, Johannesburg, 2006, South Africa

    Maria Ferentinou

Authors
  1. Christos Chalkias
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  2. Christos Polykretis
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  3. Efthimios Karymbalis
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  4. Mauro Soldati
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  5. Alessandro Ghinoi
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  6. Maria Ferentinou
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Correspondence to Christos Chalkias.

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Chalkias, C., Polykretis, C., Karymbalis, E. et al. Exploring spatial non-stationarity in the relationships between landslide susceptibility and conditioning factors: a local modeling approach using geographically weighted regression. Bull Eng Geol Environ 79, 2799–2814 (2020). https://doi.org/10.1007/s10064-020-01733-x

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