Abstract
A comprehensive landslide inventory and susceptibility maps are prerequisite for developing and implementing landslide mitigation strategies. Landslide susceptibility maps for the landslides prone regions in northern Pakistan are rarely available. The Hunza-Nagar valley in northern Pakistan is known for its frequent and devastating landslides. In this paper, we have developed a landslide inventory map for Hunza-Nagar valley by using the visual interpretation of the SPOT-5 satellite imagery and mapped a total of 172 landslides. The landslide inventory was subsequently divided into modelling and validation data sets. For the development of landslide susceptibility map seven discrete landslide causative factors were correlated with the landslide inventory map using weight of evidence and frequency ratio statistical models. Four different models of conditional independence were used for the selection of landslide causative factors. The produced landslides susceptibility maps were validated by the success rate and area under curves criteria. The prediction power of the models was also validated with the prediction rate curve. The validation results shows that the success rate curves of the weight of evidence and the frequency models are 82% and 79%, respectively. The prediction accuracy results obtained from this study are 84% for weight of evidence model and 80% for the frequency ratio model. Finally, the landslide susceptibility index maps were classified into five different varying susceptibility zones. The validation and prediction result indicates that the weight of evidence and frequency ratio model are reliable to produce an accurate landslide susceptibility map, which may be helpful for landslides management strategies.
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References
Ahmed B (2015) Landslide susceptibility mapping using multicriteria evaluation techniques in Chittagong Metropolitan Area, Bangladesh. Landslides 12(6): 1077–1095. https://doi.org/10.1007/s10346-014-0521-x
Akbar T, Ha SR (2011) Landslide hazard zoning along Himalayan 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
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): 15–31. https://doi.org/10.1016/j.geomorph.2004.06.010
Basharat M, Shah HR, Hameed N (2016) Landslide susceptibility mapping using GIS and weighted overlay method: a case study from NW Himalayas, Pakistan. Arabian Journal of Geosciences 9(4): 292. https://doi.org/10.1007/s12517-016-2308-y
Bathrellos GD, Kalivas D, Skilodimou HD (2009) GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala, Central Greece. Estud Geol 65(1): 49–65. https://doi.org/10.3989/egeol.08642.036
Bonham-Carter GF (1994) Geographic Information Systems for geoscientists-modeling with GIS. Computer Methods In The Geoscientists 13398.
Bonham-Carter GF, Agterberg FP, Wright DF (1989) Weights of evidence modelling: a new approach to mapping mineral potential. Statistical Applications In The Earth Sciences 89(9): 171–183.
Booth AM, Roering JJ, Perron JT (2009) Automated landslide mapping using spectral analysis and high-resolution topographic data: Puget Sound lowlands, Washington, and Portland Hills, Oregon. Geomorphology 109(3–4): 132–147. https://doi.org/10.1016/j.geomorph.2009.02.027
Chalkias C, Ferentinou M, Polykretis C (2014) GIS-Based Landslide Susceptibility Mapping on the Peloponnese Peninsula, Greece. Geosciences 4(3): 176–190. https://doi.org/10.3390/geosciences4030176
Chau KT, Chan JE (2005) Regional bias of landslide data in generating susceptibility maps using logistic regression: Case of Hong Kong Island. Landslides 2(4): 280–290. https://doi.org/10.1007/s10346-005-0024-x
Chauhan S, Sharma M, Arora MK, Gupta NK (2010) Landslide Susceptibility Zonation through ratings derived from Artificial Neural Network. International Journal of Applied Earth Observation and Geoinformation 12(5): 340–350. https://doi.org/10.1016/j.jag.2010.04.006
CRED (2016) Poverty and death: disaster mortality 1996–2015 https://doi.org/cred.be/downloadFile.php?file=sites/default/files/CRED_Disaster_Mortality.pdf
Dahal RK, Hasegawa S, Nonomura A, et al. (2008a) Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence. Geomorphology 102(3–4): 496–510. https://doi.org/10.1016/j.geomorph.2008.05.041
Dahal RK, Hasegawa S, Nonomura A, et al. (2008b) GIS-based weights-of-evidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility mapping. Environmental Geology 54(2): 311–324. https://doi.org/10.1007/s00254-007-0818-3
De Guidi G (2013) Landslide susceptibility assessment in the Peloritani Mts.(Sicily, Italy) and clues for tectonic control of relief processes. Natural Hazards and Earth System Sciences 13(4): 949. https://doi.org/10.5194/nhess-13-949-2013
Demir G, Aytekin M, Akgün A, et al. (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. Natural Hazards 65(3): 1481–1506. https://doi.org/10.1007/s11069-012-0418-8
Derbyshire E, Fort M, Owen LA (2001) Geomorphological Hazards along the Karakoram Highway: Khunjerab Pass to the Gilgit River, Northernmost Pakistan. Erdkunde 49–71. https://doi.org/www.jstor.org/stable/25647347
Erener A, Mutlu A, Düzgün HS (2016) A comparative study for landslide susceptibility mapping using GIS-based multicriteria decision analysis (MCDA), logistic regression (LR) and association rule mining (ARM). Engineering Geology 203: 45–55. https://doi.org/10.1016/j.enggeo.2015.09.007
Fell R, Corominas J, Bonnard C, et al. (2008) Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Engineering Geology 102(3–4): 85–98. https://doi.org/10.1016/j.enggeo.2008.03.022
Haeberlin Y, Turberg P, Retiere A, et al. (2004) Validation of Spot-5 satellite imagery for geological hazard identification and risk assessment for landslides, mud and debris flows in Matagalpa, Nicaragua. Nat. Resour. Canada 35(1): 273–278.
Hewitt K (1998) Catastrophic landslides and their effects on the Upper Indus streams, Karakoram Himalaya, northern Pakistan. Geomorphology 26(1): 47–80. https://doi.org/10.1016/S0169-555X(98)00051-8
Kamp U, Growley BJ, Khattak GA, Owen LA (2008) GIS-based landslide susceptibility mapping for the 2005 Kashmir earthquake region. Geomorphology 101(4): 631–642. https://doi.org/10.1016/j.geomorph.2008.03.003
Kanungo DP, Arora MK, Gupta RP, Sarkar S (2008) Landslide risk assessment using concepts of danger pixels and fuzzy set theory in Darjeeling Himalayas. Landslides 5(4): 407–416. https://doi.org/10.1007/s10346-008-0134-3
Kargel JS, Leonard G, Crippen RE, et al. (2010) Satellite Monitoring of Pakistan's Rockslide-Dammed Lake Gojal. Eos, Transactions American Geophysical Union 91(43): 394–395.
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. Computers & Geosciences 52(0): 398–408. https://doi.org/10.1016/j.cageo.2012.11.003
Khattak GA, Owen LA, Kamp U, Harp EL (2010) Evolution of earthquake-triggered landslides in the Kashmir Himalaya, northern Pakistan. Geomorphology 115(1): 102–108. https://doi.org/10.1016/j.geomorph.2009.09.035
Kumar KV, Martha T, Roy P (2006) Mapping damage in the Jammu and Kashmir caused by 8 October 2005 Mw 7.3 earthquake from the Cartosat–1 and Resourcesat–1 imagery. International Journal of Remote Sensing 27(20): 4449–4459. https://doi.org/10.1080/01431160600702376
Lee S, Choi J (2004) Landslide susceptibility mapping using GIS and the weight-of-evidence model. International Journal of Geographical Information Science 18(8): 789–814. https://doi.org/10.1080/13658810410001702003
Lee S, Pradhan B (2007) Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models. Landslides 4(1): 33–41. https://doi.org/10.1007/s10346-006-0047-y
Lee S, Sambath T (2006) Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models. Environmental Geology 50(6): 847–855. https://doi.org/10.1007/s00254-006-0256-7
Lodhi MA (2011) Earthquake-induced landslide mapping in the western Himalayas using medium resolution ASTER imagery. International Journal of Remote Sensing 32(19): 5331–5346. https://doi.org/10.1080/01431161.2010.502158
Malek Ž, Zumpano V, Schröter D, et al. (2015). Scenarios of land cover change and landslide susceptibility: An example from the Buzau Subcarpathians, Romania. In: Lollino G, Manconi A, Guzzetti F, et al. (eds.), Engineering Geology for Society and Territory-Volume 5. Springer International Publishing. pp. 743–746.
Martha TR, Kerle N, Jetten V, et al. (2010) Characterising spectral, spatial and morphometric properties of landslides for semi-automatic detection using object-oriented methods. Geomorphology 116(1): 24–36. https://doi.org/10.1016/j.geomorph.2009.10.004
Martha TR, van Westen CJ, et al. (2013) Landslide hazard and risk assessment using semi-automatically created landslide inventories. Geomorphology 184: 139–150. https://doi.org/10.1016/j.geomorph.2012.12.001
Mathew J, Jha VK, Rawa GS (2007) Weights of evidence modelling for landslide hazard zonation mapping in part of Bhagirathi valley, Uttarakhand. Current Sciences 92(5): 628–638.
Mezughi TH, Akhir JM, Rafek AG, Abdullah I (2011) Landslide susceptibility assessment using frequency ratio model applied to an area along the E-W Highway (Gerik-Jeli). American Journal of Environmental Sciences 7 (1): 43–50.
Mohammady M, Pourghasemi H, Pradhan B (2012) Landslide susceptibility mapping at Golestan Province, Iran: A comparison between frequency ratio, Dempster-Shafer, and weights-of-evidence models. Journal of Asian Earth Sciences 61(0): 221–236. https://doi.org/10.1016/j.jseaes.2012.10.005
Neuhäuser B, Damm B, Terhorst B (2012) GIS-based assessment of landslide susceptibility on the base of the weights-of-evidence model. Landslides 9(4): 511–528. https://doi.org/10.1007/s10346-011-0305-5
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. https://doi.org/10.1016/j.geomorph.2006.08.002
Palin R, Searle M, Waters D, et al. (2012) Combined thermobarometry and geochronology of peraluminous metapelites from the Karakoram metamorphic complex, North Pakistan; New insight into the tectonothermal evolution of the Baltoro and Hunza Valley regions. Journal of Metamorphic Geology 30(8): 793–820. https://doi.org/10.1111/j.1525-1314.2012.00999.x
Panzera F, Lombardo G, Monaco C, Di Stefano A (2015) Seismic site effects observed on sediments and basaltic lavas outcropping in a test site of Catania, Italy. Natural Hazards 79(1): 1–27. https://doi.org/10.1007/s11069-015-1822-7
Park S, Choi C, Kim B, Kim J (2013) Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea. Environmental Earth Sciences 68(5): 1443–1464. https://doi.org/10.1007/s12665-012-1842-5
Pourghasemi HR, Mohammady M, Pradhan B (2012) Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran. CATENA 97(0): 71–84. https://doi.org/10.1016/j.catena.2012.05.005
Pradhan B (2010) Landslide susceptibility mapping of a catchment area using frequency ratio, fuzzy logic and multivariate logistic regression approaches. Journal of the Indian Society of Remote Sensing 38(2): 301–320. https://doi.org/10.1007/s12524-010-0020-z
Pradhan B, Oh HJ, Buchroithner M (2010) Weights-of-evidence model applied to landslide susceptibility mapping in a tropical hilly area. Geomatics, Natural Hazards and Risk 1(3): 199–223. https://doi.org/10.1080/19475705.2010.498151
Quan HC, Lee BG (2012) GIS-based landslide susceptibility mapping using analytic hierarchy process and artificial neural network in Jeju (Korea). KSCE Journal of Civil Engineering 16(7): 1258–1266. https://doi.org/10.1007/s12205-012-1242-0
Rahim I, Ali SM, Aslam M (2018) GIS Based landslide susceptibility mapping with application of analytical hierarchy process in District Ghizer, Gilgit Baltistan Pakistan. Journal of Geoscience and Environment Protection 6 (02): 34. https://doi.org/10.4236/gep.2018.62003.
Regmi NR, Giardino JR, Vitek JD (2010) Modeling susceptibility to landslides using the weight of evidence approach: Western Colorado, USA. Geomorphology 115(1–2): 172–187. https://doi.org/10.1016/j.geomorph.2009.10.002
Reichenbach P, Busca C, Mondini AC, Rossi M (2014) The influence of land use change on landslide susceptibility zonation: the Briga Catchment test site (Messina, Italy). Environmental Management 54(6): 1372–1384. https://doi.org/10.1007/s00267-014-0357-0
Reis S, Yalcin A, Atasoy M, et al. (2012) Remote sensing and GIS-based landslide susceptibility mapping using frequency ratio and analytical hierarchy methods in Rize province (NE Turkey). Environmental Earth Sciences 66(7): 2063–2073. https://doi.org/10.1007/s12665-011-1432-y
Ren Z, Zhang Z, Dai F, et al. (2013) Co-seismic landslide topographic analysis based on multi-temporal DEM—A case study of the Wenchuan earthquake. SpringerPlus 2(1): 544.
Saba SB, van der Meijde M, van der Werff H (2010) Spatiotemporal landslide detection for the 2005 Kashmir earthquake region. Geomorphology 124(1): 17–25. https://doi.org/10.1016/j.geomorph.2010.07.026
Sarkar S, Kanungo DP, Patra AK, Kumar P (2008) GIS based spatial data analysis for landslide susceptibility mapping. Journal of Mountain Science 5(1): 52–62. https://doi.org/10.1007/s11629-008-0052-9
Scaioni M, Longoni L, Melillo V, Papini M (2014) Remote sensing for landslide investigations: An overview of recent achievements and perspectives. Remote Sensing 6(10): 9600–9652. https://doi.org/10.3390/rs6109600
Searle M, Khan MA (1996) Geological map of North Pakistan and adjacent areas of Northern Ladakh and Western Tibet, scale 1: 650,000: Oxford University, Oxford, England.
Searle M, Khan MA, Fraser J, et al. (1999) The tectonicevolution of the Kohistan Karakoram collision belt along the Karakoram Highway transect, north Pakistan. Tectonics 18(6): 929–949. https://doi.org/10.1029/1999TC900042
Shafique M, van der Meijde M, Khan MA (2016) A review of the 2005 Kashmir earthquake-induced landslides; from a remote sensing prospective. Journal of Asian Earth Sciences 11868–80. https://doi.org/10.1016/j.jseaes.2016.01.002
Shahabi H, Hashim M, Ahmad B (2015) Remote sensing and GIS-based landslide susceptibility mapping using frequency ratio, logistic regression, and fuzzy logic methods at the central Zab basin, Iran. Environmental Earth Sciences 1–22. https://doi.org/10.1007/s12665-015-4028-0
Shaw R, Rahman A. (2015). Introduction and Approaches of Disaster Risk Reduction in Pakistan Disaster Risk Reduction Approaches in Pakistan. Springer. pp 3–29.
Talaei R (2014) Landslide susceptibility zonation mapping using logistic regression and its validation in Hashtchin Region, northwest of Iran. Journal of the Geological Society of India 84(1): 68–86. https://doi.org/10.1007/s12594-014-0111-5
USGS (2015) Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global. (https://doi.org/earthexplorer.usgs.gov/, accessed on: 2015-06-25)
van Westen CJ, Rengers N, Soeters R (2003) Use of geomorphological information in indirect landslide susceptibility assessment. Natural Hazards 30(3): 399–419. https://doi.org/10.1023/B:NHAZ.0000007097.42735.9e
Wan S, Lei TC, Chou TY (2012) A landslide expert system: image classification through integration of data mining approaches for multi-category analysis. International Journal of Geographical Information Science 26(4): 747–770. https://doi.org/10.1080/13658816.2011.613397
Xu C, Xu X, Dai F, et al. (2012) Landslide hazard mapping using GIS and weight of evidence model in Qingshui River watershed of 2008 Wenchuan earthquake struck region. Journal of Earth Science 23(1): 97–120. https://doi.org/10.1007/s12583-012-0236-7
Zhuang J, Peng J, Iqbal J, et al. (2015) Identification of landslide spatial distribution and susceptibility assessment in relation to topography in the Xi’an Region, Shaanxi Province, China. Frontiers of Earth Science 9(3): 449–462. https://doi.org/10.1007/s11707-014-0474-3
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The authors thank the Pakistan Science Foundation (PSF) for providing financial support for the study.
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Bacha, A.S., Shafique, M. & van der Werff, H. Landslide inventory and susceptibility modelling using geospatial tools, in Hunza-Nagar valley, northern Pakistan. J. Mt. Sci. 15, 1354–1370 (2018). https://doi.org/10.1007/s11629-017-4697-0
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DOI: https://doi.org/10.1007/s11629-017-4697-0