Skip to main content

Advertisement

Log in

Spatio-temporal evolution of landslides along transportation corridors of Muzaffarabad, Northern Pakistan

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

Landslide spatio-temporal distribution is an effective approach to understand the landslide mechanism and triggering factors. However, the quantitative characterization of the spatio-temporal distribution of landslides along with their causative factors remains a critical challenge for geoscientists due to limited historical landslide records. This study presents the landside spatio-temporal distribution analysis by developing landslide inventories from World view-3, SPOT-5, Quick Bird and Google Earth imageries and verified in the field through extensive field visits along main road corridors (i.e., Neelum Road, Jhelum valley road and Kohala road) of the Muzaffarabad district. Past landside records of 15 years were collected, and temporal inventories were prepared for 2005, 2007, 2012, 2015, and 2019 years. Based on the research activities, the landslide spatial variations were traced and analyzed to classify them into fall and slide types. The temporal analysis of the landslides was then compared with eleven causative factors, i.e., slope, aspect, surface relief, curvature, lithology, distance to roads, faults and streams, land use, Topographic Wetness Index (TWI) and Normalized Differential Vegetation Index (NDVI). The spatio-temporal analysis demonstrates that the total number of landslides along the selected road corridors are 107, 164, 169, 92, and 182 during the years 2005, 2007, 2012, 2015, and 2019, respectively. The analysis of the study area reveals that the landslide area and events depict an abrupt increase in 2005, 2007, 2012, and 2019 whereas a significant decrease in landslide area and events were recorded during 2015. The present research concluded that the combined effect of topographic factors (slope, aspect, elevation and curvature), lithology and distance to roads have found significant influence on the landslide phenomenon. This variation in landslide areas and events indicates the influence of causative factors with respect to time. The present work will be helpful to understand the spatial patterns, trends over the years and landslide triggering mechanisms.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

Data availability

Not applicable.

References

  • Ahmed KS, Basharat M, Riaz MT, Sarfraz Y, Shahzad A (2021) Geotechnical investigation and landslide susceptibility assessment along the Neelum road: a case study from Lesser Himalayas, Pakistan. Arabian J Geosci 14(11):1–19

    Article  Google Scholar 

  • Alcántara-Ayala I (2002) Geomorphology, natural hazards, vulnerability and prevention of natural disasters in developing countries. Geomorphology 47(2–4):107–124

    Article  Google Scholar 

  • Aslam B, Zafar A, Khalil U (2021) Development of integrated deep learning and machine learning algorithm for the assessment of landslide hazard potential. Soft Comput 25(21):13493–13512

    Article  Google Scholar 

  • Aslam B, Zafar A, Khalil U (2022a) Comparison of multiple conventional and unconventional machine learning models for landslide susceptibility mapping of Northern part of Pakistan. Environ Dev Sustain. https://doi.org/10.1007/s10668-022-02314-6

    Article  Google Scholar 

  • Aslam B, Maqsoom A, Khalil U, Ghorbanzadeh O, Blaschke T, Farooq D, Tufail RF, Suhail SA, Ghamisi P (2022b) Evaluation of different landslide susceptibility models for a local scale in the Chitral District, Northern Pakistan. Sensors 22(9):3107

    Article  Google Scholar 

  • Aslam B, Zafar A, Khalil U (2022c) Comparative analysis of multiple conventional neural networks for landslide susceptibility mapping. Nat Hazards 115:1–35

    Google Scholar 

  • Baig MS, Lawrence RD (1987) Precambrian to early Paleozoic orogenesis in the Himalaya. Kashmir J Geol 5:1–22

    Google Scholar 

  • Basharat M, Rohn J (2015) Effects of volume on travel distance of mass movements triggered by the 2005 Kashmir earthquake, in the Northeast Himalayas of Pakistan. Nat Hazards 77(1):273–292

    Article  Google Scholar 

  • Basharat M, Rohn J, Baig MS, Khan MR (2014) Spatial distribution analysis of mass movements triggered by the 2005 Kashmir earthquake in the Northeast Himalayas of Pakistan. Geomorphology 206:203–214

    Article  Google Scholar 

  • Borgomeo E, Hebditch KV, Whittaker AC, Lonergan L (2014) Characterising the spatial distribution, frequency and geomorphic controls on landslide occurrence, Molise, Italy. Geomorphology 226:148–161

    Article  Google Scholar 

  • Bossart P, Dietrich D, Greco A, Ottiger R, Ramsay JG (1988) The tectonic structure of the Hazara-Kashmir syntaxis, southern Himalayas, Pakistan. Tectonics 7(2):273297

    Article  Google Scholar 

  • Calkins JA, Offield TW, Abdullah SKM, Ali ST (1975) Geology of the southern Himalaya in Hazara, Pakistan, and adjacent areas. US Geological Survey 716C. USGS, Washington, DC

  • Chen W, Yan X, Zhao Z, Hong H, Bui DT, Pradhan B (2019) Spatial prediction of landslide susceptibility using data mining-based kernel logistic regression, naive Bayes and RBF Network models for the Long County area (China). Bull Eng Geol Environ 78(1):247–266

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Devoli G, Strauch W, Chávez G, Høeg K (2007) A landslide database for Nicaragua: a tool for landslide-hazard management. Landslides 4(2):163–176

    Article  Google Scholar 

  • Dikau R, Schrott L (1999) The temporal stability and activity of landslides in Europe with respect to climatic change (TESLEC): main objectives and results. Geomorphology 30(1–2):1–12

    Article  Google Scholar 

  • Domènech G, Fan X, Scaringi G, van Asch TW, Xu Q, Huang R, Hales TC (2019) Modelling the role of material depletion, grain coarsening and revegetation in debris flow occurrences after the 2008 Wenchuan earthquake. Eng Geol 250:34–44

    Article  Google Scholar 

  • Fiorucci F, Cardinali M, Carlà R, Rossi M, Mondini AC, Santurri L, Ardizzone F, Guzzetti F (2011) Seasonal landslide mapping and estimation of landslide mobilization rates using aerial and satellite images. Geomorphology 129(1–2):59–70. https://doi.org/10.1016/j.geomorph.2011.01.013

    Article  Google Scholar 

  • Guzzetti F, Reichenbach P, Cardinali M, Galli M, Ardizzone F (2005) Probabilistic landslide hazard assessment at the basin scale. Geomorphology 72(1–4):272–299. https://doi.org/10.1016/j.geomorph.2005.06.002

    Article  Google Scholar 

  • Guzzetti F, Ardizzone F, Cardinali M, Rossi M, Valigi D (2009) Landslide volumes and landslide mobilization rates in Umbria, central Italy. Earth Planet Sci Lett 279(3–4):222–229

    Article  Google Scholar 

  • Guzzetti F, Mondini AC, Cardinali M, Fiorucci F, Santangelo M, Chang KT (2012) Landslide inventory maps: new tools for an old problem. Earth Sci Rev 112(1–2):42–66

    Article  Google Scholar 

  • Hadmoko DS, Lavigne F, Sartohadi J, Gomez C, Daryono D (2017) Spatio temporal distribution of landslides in Java and the triggering factors. Forum Geografi 31(1):1–15

    Article  Google Scholar 

  • Holcombe E, Anderson M (2010) Tackling landslide risk: helping land use policy to reflect unplanned housing realities in the Eastern Caribbean. Land Use Policy 27(3):798–800. https://doi.org/10.1016/j.landusepol.2009.10.013

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Kerle N, van WykdeVries B, Oppenheimer C (2003) New insight into the factors leading to the 1998 flank collapse and lahar disaster at Casita volcano, Nicaragua. Bull Volcanol 65(5):331–345

    Article  Google Scholar 

  • Khalil U, Imtiaz I, Aslam B, Ullah I, Tariq A, Qin S (2022) Comparative analysis of machine learning and multi-criteria decision making techniques for landslide susceptibility mapping of Muzaffarabad district. Front Environ Sci 10:1–19

    Article  Google Scholar 

  • Khan SF, Kamp U, Owen LA (2013) Documenting five years of landsliding after the 2005 Kashmir earthquake, using repeat photography. Geomorphology 197:45–55

    Article  Google Scholar 

  • Khattak GA, Owen LA, Kamp U, Harp EL (2010) Evolution of earthquake triggered landslides in the Kashmir Himalaya, northern Pakistan. Geomorphology 115(1–2):102–108

    Article  Google Scholar 

  • Kirschbaum D, Stanley T, Zhou Y (2015) Spatial and temporal analysis of a global landslide catalog. Geomorphology 249:4–15

    Article  Google Scholar 

  • Kjekstad O, Highland L (2009) Economic and social impacts of landslides. Landslides–disaster risk reduction. Springer, Berlin, pp 573–587

    Chapter  Google Scholar 

  • Lai JS, Tsai F (2019) Improving GIS-based landslide susceptibility assessments with multi-temporal remote sensing and machine learning. Sensors 19(17):3717

    Article  Google Scholar 

  • Li H, He Y, Xu Q, Deng J, Li W, Wei Y (2022) Detection and segmentation of loess landslides via satellite images: a two-phase framework. Landslides 19(3):673–686. https://doi.org/10.1007/s10346-021-01789-0

    Article  Google Scholar 

  • Lin Q, Wang Y (2018) Spatial and temporal analysis of a fatal landslide inventory in China from 1950 to 2016. Landslides 15(12):2357–2372

    Article  Google Scholar 

  • Lin L, Lin Q, Wang Y (2017) Landslide susceptibility mapping on a global scale using the method of logistic regression. Nat Hazard 17(8):1411–1424

    Article  Google Scholar 

  • Merghadi A, Abderrahmane B, Tien Bui D (2018) Landslide susceptibility assessment at Mila Basin (Algeria): a comparative assessment of prediction capability of advanced machine learning methods. ISPRS Int J Geo Inf 7(7):268

    Article  Google Scholar 

  • Nanda AM, Yousuf M, Islam ZU, Ahmed P, Kanth TA (2020) Slope stability analysis along NH 1D from Sonamarg to Kargil, J&K, India: implications for Landslide Risk Reduction. J Geol Soc India 96(5):499–506

    Article  Google Scholar 

  • Owen LA, Kamp U, Khattak GA, Harp EL, Keefer DK, Bauer MA (2008) Landslides triggered by the 8 October 2005 Kashmir earthquake. Geomorphology 94(1–2):1–9

    Article  Google Scholar 

  • Pennington C, Freeborough K, Dashwood C, Dijkstra T, Lawrie K (2015) The National Landslide Database of Great Britain: Acquisition, communication and the role of social media. Geomorphology 249:44–51

    Article  Google Scholar 

  • Pisano L, Zumpano V, Malek Ž, Rosskopf CM, Parise M (2017) Variations in the susceptibility to landslides, as a consequence of land cover changes: a look to the past, and another towards the future. Sci Total Environ 601:1147–1159. https://doi.org/10.1016/j.scitotenv.2017.05.231

    Article  Google Scholar 

  • Riaz MT, Basharat M, Hameed N, Shafique M, Luo J (2018) A data-driven approach to landslide-susceptibility mapping in mountainous terrain: case study from the Northwest Himalayas, Pakistan. Nat Hazards Rev 19(4):05018007

    Article  Google Scholar 

  • Riaz S, Wang G, Basharat M, Takara K (2019) Experimental investigation of a catastrophic landslide in northern Pakistan. Landslides 16(10):2017–2032

    Article  Google Scholar 

  • Riaz MT, Basharat M, Brunetti MT (2022a) Assessing the effectiveness of alternative landslide partitioning in machine learning methods for landslide prediction in the complex Himalayan terrain. Progress Phys Geogr Earth Environ. https://doi.org/10.1177/03091333221113660

    Article  Google Scholar 

  • Riaz MT, Basharat M, Pham QB, Sarfraz Y, Shahzad A, Ahmed KS et al (2022b) Improvement of the predictive performance of landslide mapping models in mountainous terrains using cluster sampling. Geocarto Int. https://doi.org/10.1080/10106049.2022.2066202

    Article  Google Scholar 

  • Saba SB, van der Meijde M, van der Werff H (2010) Spatiotemporal landslide detection for the 2005 Kashmir earthquake region. Geomorphology 124(1–2):17–25

    Article  Google Scholar 

  • Samia J, Temme A, Bregt A, Wallinga J, Guzzetti F, Ardizzone F, Rossi M (2017) Characterization and quantification of path dependency in landslide susceptibility. Geomorphology 292:16–24

    Article  Google Scholar 

  • Sandric I, Ionita C, Chitu Z, Dardala M, Irimia R, Furtuna FT (2019) Using CUDA to accelerate uncertainty propagation modelling for landslide susceptibility assessment. Environ Model Softw 115:176–186

    Article  Google Scholar 

  • Shafique M (2020) Spatial and temporal evolution of co-seismic landslides after the 2005Kashmir earthquake. Geomorphology 362:107228

    Article  Google Scholar 

  • Shafique M, van der Meijde M, Khan MA (2016) A review of the 2005 Kashmir earthquake-induced landslides; from a remote sensing prospective. J Asian Earth Sci 118:68–80

    Article  Google Scholar 

  • Tanyas H, Lombardo L (2020) Completeness index for earthquake-induced landslide inventories. Eng Geol 264:105331. https://doi.org/10.1016/j.enggeo.2019.105331

    Article  Google Scholar 

  • Witt A, Malamud BD, Rossi M, Guzzetti F, Peruccacci S (2010) Temporal correlations and clustering of landslides. Earth Surf Process Landf 35(10):1138–1156

    Article  Google Scholar 

  • Yang Z, Qiao J, Uchimura T, Wang L, Lei X, Huang D (2017) Unsaturated hydro-mechanical behaviour of rainfall-induced mass remobilization in post-earthquake landslides. Eng Geol 222:102–110

    Article  Google Scholar 

  • Yousefi S, Jaafari A, Valjarević A, Gomez C, Keesstra S (2022) Vulnerability assessment of road networks to landslide hazards in a dry-mountainous region. Environ Earth Sci 81(22):1–17

    Article  Google Scholar 

  • Youssef AM, Pourghasemi HR (2021) Landslide susceptibility mapping using machine learning algorithms and comparison of their performance at Abha Basin, Asir Region, Saudi Arabia. Geosci Front 12(2):639–655

    Article  Google Scholar 

  • Zhu AX, Miao Y, Wang R, Zhu T, Deng Y, Liu J et al (2018) A comparative study of an expert knowledge-based model and two data-driven models for landslide susceptibility mapping. CATENA 166:317–327

    Article  Google Scholar 

Download references

Funding

There is no funding involved.

Author information

Authors and Affiliations

Authors

Contributions

Yasir Sarfraz and Muhammad Basharat designed the study. Yasir Sarfraz and Muhammad Tayyib Riaz collected and analyzed the data. Yasir Sarfraz and Muhammad Tayyib Riaz drafted the manuscript. Yasir Sarfraz , Muhammad Basharat, Muhammad Tayyib Riaz and Mian Sohail Akram interpreted the results. Khawaja Shoaib Ahmed and Amir Shahzad revised the manuscript. All authors reviewed and edited the manuscript.

Corresponding author

Correspondence to Yasir Sarfraz.

Ethics declarations

Conflict of interest

The authors declare no any conflict of interest/competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sarfraz, Y., Basharat, M., Riaz, M.T. et al. Spatio-temporal evolution of landslides along transportation corridors of Muzaffarabad, Northern Pakistan. Environ Earth Sci 82, 131 (2023). https://doi.org/10.1007/s12665-023-10822-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12665-023-10822-5

Keywords

Navigation