Abstract
The use of an inventory map of past landslide events in the derivation of susceptibility models is considered common practice. However, evidence of landslide activity may be lost due to various degrees of modification by subsequent landslides, erosional processes, vegetation growth and anthropic influences. The timely detection of active landslides can form an effective supplement to landslide records for improving the accuracy of landslide susceptibility maps. In this paper, we present a landslide susceptibility assessment carried out in a southwestern region of Cyprus using a synergy of differential interferometry and evidential statistics. A measurement of the vertical and horizontal displacements for the period 2016–2018 was done using the Small BAseline Subset multi-pass Differential Interferometric Synthetic Aperture Radar technique. Based on the results, a total of 8859 raster cells/pixels were classified as active landslides. The weight-of-evidence technique was applied to determine the weights of seven geomorphological and hydrological factors to landslide occurrence and compile a susceptibility model. The success and prediction rates of the derived model were calculated as 79.6% and 78.9%, respectively. The validation of the results against the existing landslide inventory indicates an 84% agreement with respect to the moderate and high landslide susceptibility zones. The proposed methodology can complement existing conventional landslide inventories as a means of providing updated landslide activity at frequent intervals and can provide valuable information regarding the distribution of landslides to support a detailed landslide assessment.
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References
Alexandris A, Katsipi Griva I, Abarioti M (2016) Remediation of the Pissouri Landslide in Cyprus. Int J Geoeng Case Hist 4:14–28
Alexakis D, Agapiou A, Tzouvaras M, Themistocleous K, Neocleous K, Michaelides S, Hadjimitsis D (2014) Integrated use of GIS and remote sensing for monitoring landslides in transportation pavements: the case study of Paphos area in Cyprus. Nat Hazards
Ardizzone F, Basile G, Cardinali M, Casagli N, Del Conte S, Del Ventisette C, Fiorucci F, Garfagnoli F, Gigli G, Guzzetti F, Iovine G, Mondini AC, Moretti S, Panebianco M, Raspini F, Reichembach P, Rossi M, Tanteri L, Terranova O (2012) Landslide inventory map for the Briga and the Giampilieri catchments, NE Sicily, Italy. J Maps 8(2):176–180
Arnone E, Noto LV, Lepore C, Bras RL (2011) Physically-based and distributed approach to analyze rainfall-triggered landslides at watershed scale. Geomorphology 133(3–4):121–131
Ayalew L, Yamagishi H (2004) Slope movements in the Blue Nile basin, as seen from landscape evolution perspective. Geomorphology 57:95–116
Berardino P, Fornaro G, Lanari R, Sansosti E (2002) A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Trans Geosci Remote Sens 40(11):2375–2383
Bonham-Carter GF, Agterberg FP, Wright DF (1989) Weights of evidence modelling: a new approach to mapping mineral potential. Stat Appl Earth Sci Geol Surv Can Paper 89–9:171–183
Bonham-Carter GF (1994) Geographic information systems for geoscientists: modeling with GIS. Pergamon, Oxford
Brabb EE (1991) The world landslide problem. Episodes J Int Geosci 14(1):52–61
Brabb EE (1984) Innovative approaches to landslide hazards and risk mapping. In: 4th International symposium on landslides. Toronto. 1:307–323
Budimir MEA, Atkinson PM, Lewis HG (2015) A systematic review of landslide probability mapping using logistic regression. Landslides 12:419–436
Calò F, Ardizzone F, Castaldo R, Piernicola Lollino P, Tizzani P, Guzzetti F, Lanari R, Angeli MG, Pontoni F, Manunt M (2014) Enhanced landslide investigations through advanced DInSAR techniques: the Ivancich case study, Assisi, Italy. Remote Sens Environ 142:69–82
Cando M, Martínez-Graña A (2018) Numerical modeling of flow patterns applied to the analysis of the susceptibility to movements of the ground. Geosciences
Carrara A, Cardinali M, Detti R, Guzzetti F, Pasqui V, Reichenbach P (1991) GIS Techniques and statistical models in evaluating landslide hazard. Earth Surface Process Landform 16(5):427–445
Chang K, Merghadi A, Yunus AP (2019) Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques. Sci Rep 9:12296
Chen X, Chen H, You Y, Chen X, Liu J (2016) Weights-of-evidence method based onGIS for assessing susceptibility to debrisflows in Kangding County, Sichuan Province, China. Environ Earth Sci 75(1):1–16
Chen Z, Liang S, Ke Y, Yang Z, Zhao H (2019) Landslide susceptibility assessment using different slope units based on the evidential belief function model. Geocarto Int 1:1–24
Ciampalini A, Raspini F, Lagomarsino D, Catani F, Casagli N (2016) Landslide susceptibility map refinement using PSInSAR data. Remote Sens Environ 184:302–315
Glade T (1998) Establishing the frequency and magnitude of landslide-triggering rainstorm events in New Zealand. Environ Geol 35(2–3):160–174
Coe JA, Michael JA, Crovelli RA, Savage WZ, Laprade WT, Nashem WD (2004) Probabilistic assessment of precipitation-triggered landslides using historical records of landslide occurrence, Seattle, Washington. Environ Eng Geosci 10(2):103–122
Corominas J, Copons R, Manuel J, Vilaplana Altimir J, Amigo J (2003) Integrated landslide susceptibility analysis and hazard assessment in the principality of Andorra. Nat Hazards 30(421–435):2003
Corominas J, Mavrouli O, Modaressi H, Nadim F, Vangelsten BV, Cascini L, Ferlisi S, Fotopoulou S, Pitilakis K, Faber M, Catani F, Tofani Van Den Eeckhaut M, Pastor M, Frattini P, Agliardi F, van Western C, Malet J, Smith JT, Winter MG (2011) Guidelines for landslide susceptibility, hazard and risk zoning, SafeLand: Living with landslide risk in Europe: Assessment, effects of global change and risk management strategies, 7th Framework Programme
Dai FC, Lee CF (2002) Landslide characteristics and slope instability modelling using GIS, Lantau Island, Hong Kong. Geomorphology 42:213–228
Devkota KC, Regmi AD, Pourghasemi HR, Yoshida K, Pradhan B, Ryu IC, Dhital MR, Althuwaynee OF (2013) Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling-Narayanghat road section in Nepal Himalaya. Nat Hazards 65:1–31
Donati L, Turrini MC (2002) An objective method to rank the importance of the factors predisposing landslides with the GIS methodology-application to an area of the Apennines (Valneria; Perugia, Italy). Eng Geol 63:277–290
Evans H, Pennington C, Jordan C, Foster C (2013) Mapping a nation’s landslides: a novel multi-stage methodology. In: Landslide science and practice. Springer, Berlin, pp 21–27
Fabbri A, Chung C, Cendrero A, Remondo J (2003) Is prediction of future landslides possible with a GIS? Nat Hazards 30:487–503
Fawcett T (2006) An introduction to ROC analysis. Pattern Recogn Lett 27(8):861–874
Ferretti A, Prati C, Rocca F (2000) Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE TGRS 38(5):2202–2212
Ferretti A, Prati C, Rocca F (2001) Permanent scatterers in SAR interferometry. IEEE TGRS 39(1):8–20
Hadji R, Chouabi A, Gadri L, Rais K, Hamed Y, Boumazbeur A (2016) Application of linear indexing model and GIS techniques for the slope movement susceptibility modeling in Bousselam upstream basin. Arab J Geosci 9:1
Hadjistavrinou Y, Afrodisis S (1977) Geology and hydrogeology of the Paphos region [Cyprus]. Bull Geol Surv Dept
Hart AB, Hearn GJ (2013) Landslide assessment for land use planning and infrastructure management in the Paphos District of Cyprus. Bull Eng Geol Environ 72:173–188
He H, Hu D, Sun Q, Zhu L, Liu Y (2019) A landslide susceptibility assessment method based on GIS technology and an AHP-weighted information content method: a case study of Southern Anhui, China. ISPRS Int J Geo-Inf 8:266
Hearn GJ, Hart AB (2019) Landslide susceptibility mapping: a practitioner’s view. Bull Eng Geol Environ 78:5811–5826
Hearn G, Larkin H, Hadjicharalambous K, Papageorgiou A, Zoi G (2018) Proving a landslide: Ground behaviour problems at Pissouri, Cyprus. Q J Eng Geol Hydrogeol
Hearn G, Larkin H, Papageorgiou A, Zoi G (2020) Acceleration of the Pissouri landslide, Cyprus. Q J Eng Geol Hydrogeol
Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Rem Sens Environ 83(1–2):195–213
Jaafari A, Najafi A, Pourghasemi HR, Rezaeian J, Sattarian A (2014) GIS-based frequency ratio and index of entropy models for landslide susceptibility assessment in the Caspian forest, northern Iran. Int J Environ Sci Technol 11(4):909–926
Jenson SK, Domingue JO (1988) Extracting topographic structure from digital elevation data for geographic information system analysis. Photogram Eng Remote Sens 54(11):1593–1600
Kemp LD, Bonham-Carter GF, Raines GL, Looney, CG (2001) Arc-SDM: ArcView extension for spatial data modelling using weights-of-evidence, logistic regression, fuzzy logic and neural network analysis (software)
Kirschbaum DB, Adler R, Hong Y, Lerner-Lam A (2009) Evaluation of a preliminary satellite-based landslide hazard algorithm using global landslide inventories. Nat Hazards Earth Syst Sci 9(3):1
Larsen MC, Torres-Sanchez AJ (1998) The frequency and distribution of recent landslides in three montane tropical regions of Puerto Rico. Geomorphology 24(4):309–331
Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40(9):1095–1113
Mohammady M, Pourghasemi HR, Pradhan B (2012) Landslide susceptibility mapping at Golestan Province Iran: a comparison between frequency ratio and weights-of evidence models. J Asian Earth Sci 61:221–236
O’Callaghan JF, Mark DM (1984) The extraction of drainage networks from digital elevation data. Comput Vis Gr Image Process 28(3):323–344
Neuhäuser B, Terhorst B (2007) Landslide susceptibility assessment using “weights-of-evidence” applied to a study area at the Jurassic escarpment (SW-Germany). Geomorphology 86(1):12–24
Oh HJ, Pradhan B (2011) Application of a neuro-fuzzy model to landslide susceptibility mapping for shallow landslides in a tropical hilly area. Comput Geosci 37:1264–1276
Pashiardis S (2002) Trends of precipitation in Cyprus rainfall analysis for agricultural planning, UN Food and Agriculture Organization (FAO), Climagri Workshop, on Development of a regional network on climate change and agriculture for the countries in the Mediterranean region. FAO’s Headquarters, Rome, Italy
Popescu ME (2002) Landslide causal factors and landslide remediatial options. In 3rd International Conference on Landslides, Slope Stability and Safety of Infra-Structures. CI-Premier PTE LTD Singapore, pp 61–81
Ruff M, Czurda K (2008) Landslide susceptibility analysis with a heuristic approach in the Eastern Alps (Vorarlberg, Austria). Geomorphology 94(3–4):314–324
Lanari R, Casu F, Manzo M, Zeni G, Berardino P, Manunta M, Pepe A (2007) An overview of the small baseline subset algorithm: A DInSAR technique for surface deformation analysis. In Deformation and Gravity Change: Indicators of Isostasy, Tectonics, Volcanism, and Climate Change, pp 637–661
Ly S, Charles C, Degré A (2013) Different methods for spatial interpolation of rainfall data for operational hydrology and hydrological modeling at watershed scale: a review, BASE, vol 17
Sarkar S, Kanungo DP (2004) An integrated approach for landslide susceptibility mapping using remote sensing and GIS. Photogram Eng Rem Sens 70(5):617–625
Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New York
Schuster RL, Fleming RW (1986) Economic Losses and Fatalities due to Landslides. Bull Assoc Geol 23:11–28
Sujatha ER, Kumaravel P, Rajamanickam GV (2014) Assessing landslide susceptibility using Bayesian probability-based weight of evidence model. Bull Eng Geol Environ 73(1):147–161
Tofani V, Raspini F, Catani F, Casagli N (2013) Persistent scatterer interferometry (PSI) technique for landslide characterization and monitoring. Rem Sens 5:1045–1065
Xu C, Xu X, Lee YH, Tan X, Yu G, Dai F (2012) The 2010 yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling. Environ Earth Sci 66:1603–1616
Van Westen CJ, Ghosh S, Jaiswal P, Martha TR, Kuriakos SL (2013) From landslide inventories to landslide risk assessment; an attempt to support methodological development in India, Landslide Science and Practice, Landslide Inventory and Suscepotibility and Hazard Zoning, vol 1
Vicente-Serrano S, Saz M, Cuadrat J (2003) Comparative analysis of interpolation methods in the middle Ebro Valley (Spain): application to annual precipitation and temperature. Clim Res 24(2):2
Wallemacq P, Below R, McLean D (2018) Economic losses, poverty and disasters 1998–2017, United Nations Office for disaster risk reduction (UNDRR) and Centre for Research on the Epidemiology of Disasters (CRED) publications
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The Cyprus Geological Survey Department, Cyprus Department of Meteorology for the provision of data and the European Space Agency-ESA Copernicus Programme for Sentinel data.
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Kouhartsiouk, D., Perdikou, S. The application of DInSAR and Bayesian statistics for the assessment of landslide susceptibility. Nat Hazards 105, 2957–2985 (2021). https://doi.org/10.1007/s11069-020-04433-7
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DOI: https://doi.org/10.1007/s11069-020-04433-7