Skip to main content

Advertisement

SpringerLink
Log in

Landslide hazard mapping along national highway-154A in Himachal Pradesh, India using information value and frequency ratio

  • Original Paper
  • Published:
Arabian Journal of Geosciences Aims and scope Submit manuscript

Abstract

For the socio-economic development of a country, the highway network plays a pivotal role. It has therefore become an imperative to have landslide hazard assessment along these roads to provide safety. The current study presents landslide hazard zonation maps, based on the information value method and frequency ratio method using GIS on 1:50,000 scale by generating the information about the landslide influencing factors. The study was carried out in the year 2017 on a part of Ravi river catchment along one of the landslide-prone Chamba to Bharmour road corridor of NH-154A in Himachal Pradesh, India. A number of landslide triggering geo-environmental factors like “slope, aspect, relative relief, soil, curvature, Land Use and Land Cover (LULC), lithology, drainage density, and lineament density” were selected for landslide hazard mapping based on landslide inventory. The landslide inventory has been developed using satellite imagery, Google earth and by doing exhaustive field surveys. A digital elevation model was used to generate slope gradient, slope aspect, curvature, and relative relief map of the study area. The other information, i.e., soil maps, geological maps, and toposheets, have been collected from various departments. The landslide hazard zonation map was categorized namely “very high hazard, high hazard, medium hazard, low hazard, and very low hazard.” The results from these two methods have been validated using area under curve (AUC) method. It has been found that hazard zonation map prepared using frequency ratio model had a prediction rate of 75.37% while map prepared using information value method had prediction rate of 78.87%. Hence, on the basis of prediction rate, the landslide hazard zonation map, obtained using information value method, was experienced to be more suitable for the study area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig.7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • Achour Y, Boumezbeur A, Hadji R, Chouabbi A, Cavaleiro V, Bendaoud EA (2017) Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria. Arab J Geosci 10(8):194. https://doi.org/10.1007/s12517-017-2980-6

    Article  Google Scholar 

  • Ahmed F, Rogers JD, Ismail EH (2014) A regional level preliminary landslide susceptibility study of the upper Indus river basin. Eur J Remote Sens 2014(47):343–373

    Article  Google Scholar 

  • Akbar T, Ha S (2011) Landslide hazard zoning along Himalaya Kaghan Valley of Pakistan-by integration of GPS, GIS, and remote sensing technology. Landslides 8(4):527–540. https://doi.org/10.1007/s10346-011-0260-1

    Article  Google Scholar 

  • Akgun A (2011) A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at Lzmir, Turkey. Landslides 9(1):93–106. https://doi.org/10.1007/s10346-011-0283-7

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Anbalagan R (1992) Landslide hazard evaluation and zonation mapping in mountainous terrain. Eng Geol 32:69–277

    Article  Google Scholar 

  • Anbalagan R, Kumar R, Lakshmanan K, Parida S, Neethu S (2015) Landslide hazard zonation mapping using frequency ratio and fuzzy logic approach, a case study of Lachung Valley, Sikkim. Geo-environ Disasters 2(1):6. https://doi.org/10.1186/s40677-014-0009-y

    Article  Google Scholar 

  • Andrea F, Andrea G, Giuseppe M (2010) Rock slopes failure susceptibility analysis: from remote sensing measurements to geographic information system raster modules. Am J Environ Sci 6(6):489–494. https://doi.org/10.3844/ajessp.2010.489.494

  • Arora M, Das Gupta A, Gupta R (2004) An artificial neural network approach for landslide hazard zonation in the Bhagirathi (ganga) valley, Himalaya. Int J Remote Sens 25(3):559–572. https://doi.org/10.1080/0143116031000156819

    Article  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(1/2):15–31. https://doi.org/10.1016/j.geomorph.2004.06.010

    Article  Google Scholar 

  • Balsubramani K, Kumaraswamy K (2013) Application of geospatial technology and information value technique in landslide hazard zonation mapping: a case study of Giri Valley, Himachal Pradesh. Disaster Adv 6:38–47

    Google Scholar 

  • Balteanu D, Chendes V, Sima M, Enciu P (2010) A country-wide spatial assessment of landslide susceptibility in Romania. Geophys J R Astron Soc 124:102–112

    Google Scholar 

  • Blahut J, VanWesten C, Sterlacchini S (2010) Analysis of landslide inventories for accurate prediction of debris-flow source areas. Geophys J R Astron Soc 119:36–51

    Google Scholar 

  • Brooks SM, Crozier MJ, Glade TW, Anderson MG (2004) Towards establishing climatic thresholds for slope instability: use of a physically-based combined soil hydrology-slope stability model. Pure Appl Geophys 16:881–905

    Article  Google Scholar 

  • Cardinali M, Reichenbach P, Guzzetti F, Ardizzone F, Antonini G, Galli M, Cacciano M, Castellani M, Salvati P (2002) A geomorphological approach to estimation of landslide hazards and risks in Umbria, Central Italy. Nat Hazards Earth Syst Sci 2(1/2):57–72. https://doi.org/10.5194/nhess-2-57-2002

    Article  Google Scholar 

  • Champatiray P (2000) Perationalization of cost-effective methodology for landslide hazard zonation using RS and GIS: IIRS initiative. In: Roy P, Van Westen C, Jha V, Lakhera R (eds) Natural disasters and their mitigation; remote sensing and geographical information system perspectives. Indian Institute of Remote Sensing, Dehradun, pp 95–101

    Google Scholar 

  • Champatiray P, Dimri S, Lakhera R, Sati S (2007) Fuzzy based methods for landslide hazard assessment in active seismic zone of Himalaya. Landslides 4(2):101–110. https://doi.org/10.1007/s10346-006-0068-6

    Article  Google Scholar 

  • Chang K and Liu J (2004) Geo-imagery bridging continents. Landslide features interpreted by neural network method using a high resolution satellite image and digital topographical data. Proceedings of 20th ISPRS congress, Istambul

  • Chen W, Chai H, Zhao Z, Wang Q, Hong H (2016) Landslide susceptibility mapping based on GIS and support vector machine models for the Qianyang County, China. Environ Earth Sci 75(6):1–13

    Google Scholar 

  • Chung CJF, Fabbri AG (2003) Validation of spatial prediction models for landslide hazard mapping. Nat Hazards 30(3):451–472. https://doi.org/10.1023/B:NHAZ.0000007172.62651.2b

    Article  Google Scholar 

  • Chung MC, Tan CH, Chen CH (2016) Local rainfall thresholds for forecasting landslide occurrence: Taipingshan landslide triggered by typhoon Saola. Landslides 14(1):19–33. https://doi.org/10.1007/s10346-016-0698-2

    Article  Google Scholar 

  • Courture R (2011) Landslide Terminology - National Technical Guidelines and Best Practices on Landslides. Geological Survey of Canada. p 12, Open File 6824

  • Crosta GB and Frattini P (2003) Distributed modelling of shallow landslides triggered by intense rainfall. Natural hazards and earth system. Science 81–93

  • Cruden DM and Varnes DJ (1996) Landslide types and processes, special report, Transportation Research Board, National Academy of Sciences 247:36–75

  • Dai FC, Lee CF (2002) Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology 42(3):213–228. https://doi.org/10.1016/S0169-555X(01)00087-3

    Article  Google Scholar 

  • Das I, Sahoo S, Van Westen C, Stein A, Hack R (2010) Landslide susceptibility assessment using logistic regression and its comparison with a rock mass classification system, along a road section in the northern Himalayas (India). Geomorphology 114(4):627–637. https://doi.org/10.1016/j.geomorph.2009.09.023

    Article  Google Scholar 

  • Deeken A, Thiede RC, Sobel ER, HouriganJK SMR (2011) Exhumational variability within the Himalaya of northwest India. Earth Planet Sci Lett 305(1-2):103–114. https://doi.org/10.1016/j.epsl.2011.02.045

    Article  Google Scholar 

  • Demir G, Aytekin M, Akgun 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(3):1481–1506. https://doi.org/10.1007/s11069-012-0418-8

    Article  Google Scholar 

  • Ercanoglu M, Gokceoglu C (2004) Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (west Black Sea region, Turkey). Eng Geol 75(3-4):229–250. https://doi.org/10.1016/j.enggeo.2004.06.001

    Article  Google Scholar 

  • Fawcett T (2006) An introduction to ROC analysis. Pattern Recogn Lett 27(8):861–874. https://doi.org/10.1016/j.patrec. 2005.10.010

    Article  Google Scholar 

  • Feizizadeh B, Blaschke T, Nazmfar H, RezaeiMoghaddam MH (2013) Landslide susceptibility mapping for the Urmia Lake basin, Iran: a multi-criteria evaluation approach using GIS. Int J Environ Res 7(2):319–3336

    Google Scholar 

  • Floris M, Mari M, Romeo RW, Gori U (2004) Modelling of landslide-triggering factors - a case study in the northern Apen- nines, Italy, Lect. Notes Earth Sci 104:745–753

    Article  Google Scholar 

  • Frank W, Grasemann B, Guntli P, Miller C (1995) Geological map of the Kishtwar-Chamba-Kulu region (NWHimalaya India). Jahrb Geol Bundesanst 138(2):299–308

    Google Scholar 

  • Frattini P, Crosta G, Carrara A (2010) Techniques for evaluating the performance of landslide susceptibility models. Eng Geol 111(1-4):62–72. https://doi.org/10.1016/j.enggeo.2009.12.004

    Article  Google Scholar 

  • Giannecchini R (2005) Rainfall triggering soil slips in the southern Apuan alps (Tuscany, Italy). Adv Geosci 2:21–24 http://www.adv-geosci.net/2/21/2005/

    Article  Google Scholar 

  • Gomez H, Bradshow R, Mather P (2000) Monitoring the distribution of shallow landslide prone areas using remote sensing, DTM and GIS - a case study from the tropical Andes of Venezuela. In: Casanova E (ed) Remote sensing in 21st century: economic and environmental applications. Balkema, Rotterndam, pp 395–401

  • Guru B, Veerappan R, Mangminlen T (2016) Landslide susceptibility zonation mapping using frequency ratio and fuzzy gamma operator models in part of NH-39, Manipur, India. Nat Hazards 84:465–488

    Article  Google Scholar 

  • Guzzetti F (2003) Landslide hazard assessment and risk evaluation: limits and perspectives, proceedings of the 4th EGS Plinius conference held at Mallorca. Spain. University de les IllesBalears, Spain, pp 1–4

    Google Scholar 

  • 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(1):181–216. https://doi.org/10.1016/S0169-555X(99)00078-1

    Article  Google Scholar 

  • Guzzetti F, Reichenbach P, Ardizzone M, Cardinali M, Galli M (2006) Estimating the quality of landslides susceptibility models. Geomorphology 81(1-2):166–184. https://doi.org/10.1016/j.geomorph.2006.04.007

    Article  Google Scholar 

  • Hung LQ, Van Hai TH, Duc DM, Ha LTC, Son PV, Khanh NH, Binh LT (2015) Landslide susceptibility mapping by combining the analytical hierarchy process and weighted linear combination methods: a case study in the upper lo river catchment (Vietnam). Landslides

  • Hutchinson JN (1995) Landslide hazard assessment. In: proc VI Int. Symp on landslides, Christchurch. 1:1805–1842

  • Iverson RM (2000) Landslide triggering by rain infiltration. Water Resour Res 36(7):1897–1910. https://doi.org/10.1029/2000WR900090

    Article  Google Scholar 

  • Jaiswal P, Van Westen CJ, Jetten V (2010) Quantitative landslide hazard assessment along a transportation corridor in southern India. Eng Geol 116(3-4):236–250. https://doi.org/10.1016/j.enggeo.2010.09.005

    Article  Google Scholar 

  • Kannan M, Saranathan E, Anabalagan R (2013) Landslide vulnerability mapping using frequency ratio model: a geospatial approach in Bodi–Bodimettu Ghat section, Theni district, Tamil Nadu, India. Arab J Geosci 6(8):2901–2913. https://doi.org/10.1007/s12517-012-0587-5

    Article  Google Scholar 

  • Kanungo DP, Sharma S (2014) Rainfall thresholds for prediction of shallow landslides around Chamoli-Joshimath region, Garhwal Himalayas, India. Landslides 11(4):629–638. https://doi.org/10.1007/s10346-013-0438-9

    Article  Google Scholar 

  • Kanungo DP, Arora MK, Sarkar S, Gupta RP (2009) Landslide susceptibility zonation (LSZ) mapping – areview. J South Asia Dis Stu 2:81–105

    Google Scholar 

  • Kaur H, Gupta S, Parkash S (2017) Comparative evaluation of various approaches for landslide hazard zoning: a critical review in Indian perspectives. Spat Inf Res 25(3):389–398. https://doi.org/10.1007/s41324-017-0105-7

    Article  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(3):425–439. https://doi.org/10.1007/s10346-013-0391-7

    Article  Google Scholar 

  • Kayastha P, Dhital MR, De Smedt F (2013) Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: a case study from the Tinau watershed, west Nepal. Comput Geosci 52:398–408. https://doi.org/10.1016/j.cageo.2012.11.003

    Article  Google Scholar 

  • Kumar R, Anbalagan R (2016) Landslide susceptibility mapping using analytical hierarchy process (AHP) in Tehri reservoir rim region, Uttarakhand. J Geol Soc India 87(3):271–286. https://doi.org/10.1007/s12594-016-0395-8

    Article  Google Scholar 

  • Kumar S, Mahajan AK (2001) Seismotectonics of the Kangra region north Himalaya. Tectonophys 331(4):359–371. https://doi.org/10.1016/S0040-1951(00)00293-6

    Article  Google Scholar 

  • 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):1477–1491. https://doi.org/10.1080/01431160412331331012

    Article  Google Scholar 

  • Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40(9):1095–1113. https://doi.org/10.1007/s002540100310

    Article  Google Scholar 

  • Lee S, Pradhan B (2006) Probabilistic landslide hazard and risk mapping on Penang Island, Malaysia. J Earth Syst Sci 115:661–672

    Article  Google Scholar 

  • Lee S, Talib JA (2005) Probabilistic landslide susceptibility and factor effect analysis. Environ Geol 47(7):982–990. https://doi.org/10.1007/s00254-005-1228-z

    Article  Google Scholar 

  • Lee S, Hwang J, Park I (2013) Application of data-driven evidential belief functions to landslide susceptibility mapping in Jinbu, Korea. Catena 100:15–30. https://doi.org/10.1016/j.catena.2012.07.014

    Article  Google Scholar 

  • Leir M, Michell A, Ramsay S (2004) Regional landslide hazard susceptibility mapping for pipelines in British Columbia. Geo-engineering for the society and its environment. In: 57th Canadian geotechnical conference and the 5th joint CGS-IAH conference, pp 1–9

  • Marchi L, Arattano M, Deganutti AM (2002) Ten years of debris- flow monitoring in the Moscardo torrent (Italian alps). Geomorphology 46(1-2):1–17. https://doi.org/10.1016/S0169-555X(01)00162-3

    Article  Google Scholar 

  • Mezughi TH, Akhir JM, Rfek AG, Abdullah I (2011) Landslide susceptibility assessment using frequency ratio model applied to an area along the E-W highway (Gerik-Jeli). Am J Environ Sci 7(1):43–50. https://doi.org/10.3844/ajessp.2011.43.50

    Article  Google Scholar 

  • Mondal S, Maiti R (2012) Landslide susceptibility analysis of shiv-Khola watershed, Darjiling; a remote sensing and GIS based analytic hierarchy process. J Indian Soc Remote Sens 3:483–496

    Article  Google Scholar 

  • Montrasio L, Valentino R, Losi GL (2012) Shallow landslides triggered by rainfalls: modeling of some case histories in the Reggiano Apennine (Emilia Romagna region, northern Italy). Nat Hazards 60(3):1231–1254. https://doi.org/10.1007/s11069-011-9906-5

    Article  Google Scholar 

  • Nagarajan R, Roy A, Vinodkumar R, Khire M (2000) Landslide hazard susceptibility mapping based on terrain and climatic factors for tropical monsoon region. Eng Geol 58:275–287

    Google Scholar 

  • Nandi A, Shakoor A (2009) A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses. Eng Geol 110(1-2):11–20. https://doi.org/10.1016/j.enggeo.2009.10.001

    Article  Google Scholar 

  • PandeyDD, SinghKP, SardaVK (2016) GIS based inventory study of landslide hazard zonation in LahaulSpiti Valley between Rohtang to Baralacha la, Himachal Pradesh, India. Int J Earth Sci Eng 2847–2854

  • Parise M (2002) Landslide hazard zonation of slopes susceptible to rock falls and topples. Nat Hazards Earth Syst Sci 2(1/2):37–49. https://doi.org/10.5194/nhess-2-37-2002

    Article  Google Scholar 

  • Poudyal CP, Chang C, Oh HJ, Lee S (2010) Landslide susceptibility maps comparing frequency ratio and artificial neural networks: a case study from the Nepal Himalaya. Environ Earth Sci 61(5):1049–1064. https://doi.org/10.1007/s12665-009-0426-5

    Article  Google Scholar 

  • Pourghasemi HR, Pradhan B, Gokceoglu C (2012) Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Nat Hazards 63(2):965–996. https://doi.org/10.1007/s11069-012-0217-2

    Article  Google Scholar 

  • Pradhan B (2010) Application of an advanced fuzzy logic model for landslide susceptibility analysis. Int J Comput Intel Syst 3(3):370–381. https://doi.org/10.1080/18756891.2010.9727707

    Article  Google Scholar 

  • Pradhan Ananta MS, Kim YT (2017) (2017) landslide susceptibility mapping of Phewa catchment using multilayer perceptron artificial neural network. Nep J Environ Sci 4:1–9

    Google Scholar 

  • Pradhan B, Lee S (2010) Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models. Environ Earth Sci 60(5):1037–1054. https://doi.org/10.1007/s12665-009-0245-8

    Article  Google Scholar 

  • Preuth T, Glade T, Demoulin A (2010) Stability analysis of a human-influenced landslides in eastern Belgium. Geophys J R Astron Soc 120:4–98

    Google Scholar 

  • Ramakrishnan D, Singh TN, Verma AK, Gulati A, Tiwari KC (2013) Soft computing and GIS for landslide susceptibility assessment in Tawaghat area, Kumaon Himalaya, India. Nat Hazards 65(1):315–330. https://doi.org/10.1007/s11069-012-0365-4

    Article  Google Scholar 

  • Ramesh V, Anbazhagan S (2015) Landslide susceptibility assessment along Kohli hills Ghat road section India using frequency ratio, relative effect and fuzzy logic models. Environ Earth Sci 73(12):8009–8021. https://doi.org/10.1007/s12665-014-3954-6

    Article  Google Scholar 

  • Ran QH, Su DY, Fu XD, Wang GQ, He ZG (2012) Physically-based approach to analyze rainfall-triggered landslide using hydraulic gradient as slide direction. Appl Phys Eng 13(12):943–957

    Google Scholar 

  • Razavizadeh S, Solaimani K, Massironi M, Kavian A (2017) Mapping landslide susceptibility with frequency ratio, statistical index, and weights of evidence models: a case study in northern Iran. Environ Earth Sci 76(14):499. https://doi.org/10.1007/s12665-017-6839-7

    Article  Google Scholar 

  • Saaty T (2008) Decision making with the analytical hierarchy process. Int J Services Sci 1(1):83–98. https://doi.org/10.1504/IJSSCI.2008.017590

    Article  Google Scholar 

  • Salciarini D, Tamagnini C, Conversini P, Rapinesi S (2012) Spatially distributed rainfall thresholds for the initiation of shallow landslides. Nat Hazards 6:229–245

    Article  Google Scholar 

  • Sarkar S, Kanungo D, Mehrotra G (1995) Landslide hazard zonation: a case study of garhwal Himalaya, India. Mt Res Dev 15(4):301–309. https://doi.org/10.2307/3673806

    Article  Google Scholar 

  • Sarkar S, Kanungo D, Patra A, Kumar P (2006) Disaster mitigation of debris flows, slope failures and landslides. GIS based landslide susceptibility mapping- a case study in Indian Himalaya. Universal Academy Press, Tokyo, pp 617–624

    Google Scholar 

  • Sengupta A, Gupta S, Anbarasu K (2010) Rainfall thresholds for the initiation of landslide at LantaKhola in north Sikkim, India. Nat Hazards 52(1):31–42. https://doi.org/10.1007/s11069-009-9352-9

    Article  Google Scholar 

  • SharmaVK, KumarH, Kumar P (2005) Macro-seismic investigation of Chamba earthquake of 14th April, 2005, Himachal Pradesh. Geol Surv India, Unpublished Report, FS2004–2005

  • Sharma L, Patel N, Ghosh M, Debnath P (2009) Geographical information system based landslide probabilistic model with Trivariate approach– acase study in Sikkim Himalaya. Eighteenth United Nations regional cartographic conference for Asia and the Pacific. Economic and Social Council, UN, Bankok

    Google Scholar 

  • Sujatha ER, Rajamanickam GV, Kumaravel P (2012) Landslide susceptibility analysis using probablistic certainty factor approach: a case study on Tevankarai stream watershed, India. J Earth Syst Sci 121(5):1337–1350. https://doi.org/10.1007/s12040-012-0230-6

    Article  Google Scholar 

  • Trampoglou P, Loupasakis C (2017) Mining geohazards susceptibility and risk mapping: The case of the Amyntaio open-pit coal mine, West Macedonia, Greece. Environ Earth Sci 76:542

    Article  Google Scholar 

  • Van Westen CJ (1993) Application of geographic information systems to landslide hazard zonation. ITC publication, vol. 15. International Institute for Aerospace and Earth Resources Survey, Enschede, pp245

  • Van Westen CJ, Rengers N, Soeters R (2003) Use of geomorphological information in indirect landslide susceptibility assessment. Nat Hazards 30(3):399–419. https://doi.org/10.1023/B:NHAZ.0000007097.42735.9e

    Article  Google Scholar 

  • Varnes DJ (1978) Slope movement typesandprocesses. In: Schuster RL, Krizek RJ (eds) Special report 176:Landslides: analysis and control. Transportation and Road Research Board, National Academy of Science, Washington D. C, pp 11–33

    Google Scholar 

  • Varnes DJ (1984) Landslide hazard zonation: a review of principles and practice. Natural hazard, 3. United Nations Educational, Scientific and Cultural Organization. pp63

  • Wadia DN (1931) The syntaxes of the north-west Himalya-its rocks, tectonics, and orogeny. Rec Geol Surv India 65:189–220

    Google Scholar 

  • Wang H, Sassa K (2005) Comparative evaluation of landslide susceptibility in Minamata area, Japan. Environ Geol 47(7):956–966. https://doi.org/10.1007/s00254-005-1225-2

    Article  Google Scholar 

  • White H and Senior M (1983) Transport geography, Longman, London

  • Yalcin A (2008) GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): comparisons of results and confirmations. Catena 72(1):1–12. https://doi.org/10.1016/j.catena.2007.01.003

    Article  Google Scholar 

  • Yan TZ (1988) Recent advances of quantitative prognoses of landslide in China. In: Proceedings of the fifth international symposium on landslides, Lausanne, Switzerland. 2:1263–1268

  • Yin KL and Yan TZ (1988) Statistical prediction model for slope instability of metamorphosed rocks. In: Bonnard C (ed) Proc., fifth international symposium in landslides, Lausanne, Vol. 2., a.A. Balkema, Rotterdam, pp 1269–1272

  • Zezere J (2002) Landslide susceptibility assessment considering landslide typology. A case study in the area north of Lisbon (Portugal). Nat Hazard Earth Syst Sci 2:73–82

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Civil Engineering Department, National Institute of Technology, Hamirpur, India

    Kanwarpreet Singh & Virender Kumar

Authors
  1. Kanwarpreet Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Virender Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kanwarpreet Singh.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singh, K., Kumar, V. Landslide hazard mapping along national highway-154A in Himachal Pradesh, India using information value and frequency ratio. Arab J Geosci 10, 539 (2017). https://doi.org/10.1007/s12517-017-3315-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12517-017-3315-3

Keywords

Search

Navigation