Skip to main content

Advertisement

Log in

Spatio-temporal landslide inventory and susceptibility assessment using Sentinel-2 in the Himalayan mountainous region of Pakistan

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

The 2005 Kashmir earthquake has triggered widespread landslides in the Himalayan mountains in northern Pakistan and surrounding areas, some of which are active and are still posing a significant risk. Landslides triggered by the 2005 Kashmir earthquake are extensively studied; nevertheless, spatio-temporal landslide susceptibility assessment is lacking. This can be partially attributed to the limited availability of high temporal resolution remote sensing data. We present a semi-automated technique to use the Sentinel-2 MSI data for co-seismic landslide detection, landslide activities monitoring, spatio-temporal change detection, and spatio-temporal susceptibility mapping. Time series Sentinel-2 MSI images for the period of 2016–2021 and ALOS PALSAR DEM are used for semi-automated landslide inventory map development and temporal change analysis. Spectral information combined with topographical, contextual, textural, and morphological characteristics of the landslide in Sentinel-2 images is applied for landslide detection. Subsequently, spatio-temporal landslide susceptibility maps are developed utilizing the weight of evidence statistical modeling with seven causative factors, i.e., elevation, slope, geology, aspect, distance to fault, distance to roads, and distance to streams. The results reveal that landslide occurrence increased from 2016 to 2021 and that the coverage of areas of relatively high susceptibility has increased in the study area.

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

Similar content being viewed by others

Data availability

In this study, the generated and analyzed data are available from the corresponding author on reasonable request.

References

  • Aksoy, B., & Ercanoglu, M. (2012). Landslide identification and classification by object-based image analysis and fuzzy logic: An example from the Azdavay region (Kastamonu, Turkey). Computers & Geosciences, 38(1), 87–98. https://doi.org/10.1016/j.cageo.2011.05.010

    Article  Google Scholar 

  • Bacha, A. S., Shafique, M., & van der Werff, H. (2018). Landslide inventory and susceptibility modelling using geospatial tools, in Hunza-Nagar valley, northern Pakistan. Journal of Mountain Science, 15(6), 1354–1370. https://doi.org/10.1007/s11629-017-4697-0

    Article  Google Scholar 

  • Bacha, A. S., Van Der Werff, H., Shafique, M., & Khan, H. (2020). Transferability of object-based image analysis approaches for landslide detection in the Himalaya Mountains of northern Pakistan. International Journal of Remote Sensing, 41(9), 3390–3410. https://doi.org/10.1080/01431161.2019.1701725

    Article  Google Scholar 

  • Baig, M. S., Lawrence, R. D., & Snee, L. W. (1988). Evidence for late Precambrian to early Cambrian orogeny in northwest Himalaya. Pakistan. Geological Magazine, 125(1), 83–86. https://doi.org/10.1017/S0016756800009390

    Article  Google Scholar 

  • Basharat, M., Shah, H. R., & 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), 1–19. https://doi.org/10.1007/s12517-016-2308-y

    Article  Google Scholar 

  • Behling, R., Roessner, S., Kaufmann, H., & Kleinschmit, B. J. R. S. (2014). Automated Spatiotemporal Landslide Mapping over Large Areas Using Rapideye Time Series Data. 6(9), 8026–8055.

    Google Scholar 

  • Benz, U. C., Hofmann, P., Willhauck, G., Lingenfelder, I., & Heynen, M. (2004). Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry and Remote Sensing, 58(3), 239–258. https://doi.org/10.1016/j.isprsjprs.2003.10.002

    Article  Google Scholar 

  • Blaschke, T., Feizizadeh, B., & Hölbling, D. (2014). Object-based image analysis and digital terrain analysis for locating landslides in the Urmia Lake Basin, Iran. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(12), 4806–4817. https://doi.org/10.1109/JSTARS.2014.2350036

  • Calkins, J., Offield, T., Abdullah, S., & Ali, S. (1975). Geology of South Himalyan in Hazara, Pakistan, and adjacent areas. Retrieved from USA.

  • Crozier, M. J., & Glade, T. (2005). Landslide hazard and risk: Issues, concepts and approach. Landslide Hazard Risk. https://doi.org/10.1002/9780470012659.ch1

    Article  Google Scholar 

  • Derbyshire, E., Fort, M., & Owen, L. A. (2001). Geomorphological hazards along the Karakoram highway: Khunjerab pass to the Gilgit River, northernmost Pakistan (Geomorphologische hazards entlang des Karakorum highway: Khunjerab Paß bis zum Gilgit River, nördlichstes Pakistan). Erdkunde, 49–71. http://www.jstor.org/stable/25647347

  • Dou, J., Tien Bui, D. P., Yunus, A., Jia, K., Song, X., Revhaug, I., Xia, H., Zhu, Z., & Kumar, L. (2015). Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata Japan. PLOS ONE, 10(7), e0133262. https://doi.org/10.1371/journal.pone.0133262

  • Drăguţ, L., Csillik, O., Eisank, C., & Tiede, D. (2014). Automated parameterisation for multi-scale image segmentation on multiple layers. ISPRS Journal of Photogrammetry and Remote Sensing, 88, 119–127. https://doi.org/10.1016/j.isprsjprs.2013.11.018

    Article  Google Scholar 

  • Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., & Bargellini, P. (2012). Sentinel-2: ESA’s optical high-resolution mission for GMES operational services. Remote Sensing of Environment, 120, 25–36. https://doi.org/10.1016/j.rse.2011.11.026

    Article  Google Scholar 

  • Duro, D. C., Franklin, S. E., & Dubé, M. G. (2012). Multi-scale object-based image analysis and feature selection of multi-sensor earth observation imagery using random forests. International Journal of Remote Sensing, 33(14), 4502–4526. https://doi.org/10.1080/01431161.2011.649864

  • eCognition Developer, T. (2014). 9.0 user guide. Trimble Germany GmbH: Munich, Germany.

  • 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., Mondini, A. C., Cardinali, M., Fiorucci, F., Santangelo, M., & Chang, K. T. (2012). Landslide Inventory Maps: New Tools for an Old Problem. 112(1–2), 42–66. https://doi.org/10.1016/j.earscirev.2012.02.001

    Article  Google Scholar 

  • Huete, A. R. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3), 295–309. https://doi.org/10.1016/0034-4257(88)90106-X

  • Kamp, U., Growley, B. J., Khattak, G. A., & Owen, L. A. (2008). GIS-based landslide susceptibility mapping for the 2005 Kashmir earthquake region. Geomorphology, 101(4), 631–642.

    Article  Google Scholar 

  • Kamp, U., Owen, L. A., Growley, B. J., & Khattak, G. A. (2010). Back analysis of landslide susceptibility zonation mapping for the 2005 Kashmir earthquake: An assessment of the reliability of susceptibility zoning maps. Natural Hazards, 54(1), 1–25. https://doi.org/10.1007/s11069-009-9451-7

    Article  Google Scholar 

  • Keyport, R. N., Oommen, T., Martha, T. R., & Sajinkumar, K. (2018). A comparative analysis of pixel-and object-based detection of landslides from very high-resolution images. International Journal of Applied Earth Observation and Geoinformation, 64, 1–11. https://doi.org/10.1016/j.jag.2017.08.015

    Article  Google Scholar 

  • Khan, S. F., Kamp, U., & Owen, L. A. (2013). Documenting five years of landsliding after the 2005 Kashmir earthquake, using repeat photography. Geomorphology, 197, 45–55. https://doi.org/10.1016/j.geomorph.2013.04.033

    Article  Google Scholar 

  • Khattak, G. A., Owen, L. A., Kamp, U., & Harp, E. L. (2010). Evolution of earthquake-triggered landslides in the Kashmir Himalaya, northern Pakistan. Geomorphology, 115(1–2), 102–108. https://doi.org/10.1016/j.geomorph.2009.09.035

    Article  Google Scholar 

  • Kirschbaum, D., Stanley, T., & Zhou, Y. (2015). Spatial and temporal analysis of a global landslide catalog. Geomorphology, 249, 4–15. https://doi.org/10.1016/j.geomorph.2015.03.016

    Article  Google Scholar 

  • Lahousse, T., Chang, K. T., & Lin, Y. H. (2011). Landslide mapping with multi-scale object-based image analysis – a case study in the Baichi watershed Taiwan. Natural Hazards and Earth System Sciences, 11(10), 2715–2726. https://doi.org/10.5194/nhess-11-2715-2011

  • Li, W., Du, Z., Ling, F., Zhou, D., Wang, H., Gui, Y., & Zhang, X. J. R. S. (2013). A comparison of land surface water mapping using the normalized difference water index from TM, ETM+ and ALI. 5(11), 5530–5549.

  • Li, X., Cheng, X., Chen, W., Chen, G., & Liu, S. (2015). Identification of forested landslides using LiDar data, object-based image analysis, and machine learning algorithms. Remote Sensing, 7(8), 9705–9726. https://doi.org/10.3390/rs70809705

    Article  Google Scholar 

  • Lu, P., Stumpf, A., Kerle, N., & Casagli, N. (2011). Object-oriented change detection for landslide rapid mapping. IEEE Geoscience and Remote Sensing Letters, 8(4), 701–705. https://doi.org/10.1109/LGRS.2010.2101045

    Article  Google Scholar 

  • Mahmood, I., Qureshi, S. N., Tariq, S., Atique, L., & Iqbal, M. F. (2015). Analysis of landslides triggered by October 2005. Kashmir Earthquake. Plos Currents. https://doi.org/10.1371/currents.dis.0bc3ebc5b8adf5c7fe9fd3d702d44a99

    Article  Google Scholar 

  • Martha, T. R., Kerle, N., Jetten, V., van Westen, C. J., & Kumar, K. V. (2010). Characterising spectral, spatial and morphometric properties of landslides for semi-automatic detection using object-oriented methods. Geomorphology, 116(1–2), 24–36. https://doi.org/10.1016/j.geomorph.2009.10.004

    Article  Google Scholar 

  • Martha, T. R., van Westen, C. J., Kerle, N., Jetten, V., & Vinod Kumar, K. (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

    Article  Google Scholar 

  • Mezughi, T. H., Akhir, J. M., Rafek, A. G., & Abdullah, I. (2011). Landslide susceptibility assessment using frequency ratio model applied to an area along the EW highway (Gerik-Jeli). American Journal of Environmental Sciences, 7(1), 43. https://doi.org/10.3844/ajessp.2011.43.50

    Article  Google Scholar 

  • Mora, O. E., Lenzano, M. G., Toth, C. K., Grejner-Brzezinska, D. A., & Fayne, J. V. (2018). Landslide change detection based on multi-temporal airborne LiDAR-derived DEMs. Geosciences, 8(1), 23. https://doi.org/10.3390/geosciences8010023

    Article  Google Scholar 

  • Owen, L. A., Kamp, U., Khattak, G. A., Harp, E. L., Keefer, D. K., & Bauer, M. A. (2008). Landslides triggered by the 8 October 2005 Kashmir earthquake. Geomorphology, 94(1–2), 1–9. https://doi.org/10.1016/j.geomorph.2007.04.007

    Article  Google Scholar 

  • Qasim, M., Khan, M. A., & Haneef, M. (2014). Stratigraphic characterization of the Early Cambrian Abbottabad Formation in the Sherwan area, Hazara region, N. Pakistan: Implications for Early Paleozoic stratigraphic correlation in NW Himalayas, Pakistan. Himalayan Earth Sciences, 47(1), 25.

  • Qingqing, H., Yu, M., Jingbo, C., Anzhi, Y., & Lei, L. (2017). Landslide change detection based on spatio-temporal context. Paper presented at the IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

  • Rehman, M. U., Zhang, Y., Meng, X., Su, X., Catani, F., Rehman, G., & Ahmad, I. (2020). Analysis of landslide movements using interferometric synthetic aperture radar: A case study in Hunza-Nagar Valley. Pakistan. Remote Sensing, 12(12), 2054. https://doi.org/10.3390/rs12122054

    Article  Google Scholar 

  • Saba, S. B., 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

    Article  Google Scholar 

  • Sato, H. P., Hasegawa, H., Fujiwara, S., Tobita, M., Koarai, M., Une, H., & Iwahashi J. (2007). Interpretation of landslide distribution triggered by the 2005 Northern Pakistan earthquake using SPOT 5 imagery. Landslides, 4(2), 113–122. https://doi.org/10.1007/s10346-006-0069-5

  • Shafique, M. (2020a). Spatial and temporal evolution of co-seismic landslides after the 2005 Kashmir earthquake. Geomorphology. https://doi.org/10.1016/j.geomorph.2020.107228

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Smith, A. (2010). Image segmentation scale parameter optimization and land cover classification using the Random Forest algorithm. Journal of Spatial Science, 55(1), 69–79. https://doi.org/10.1080/14498596.2010.487851

    Article  Google Scholar 

  • Stumpf, A., Malet, J.-P., & Delacourt, C. (2017a). Correlation of satellite image time-series for the detection and monitoring of slow-moving landslides. Remote Sensing of Environment, 189, 40–55. https://doi.org/10.1016/j.rse.2016.11.007

    Article  Google Scholar 

  • Stumpf, A., Marc, O., Malet, J. -P., & Michea, D. (2017b). Sentinel-2 for rapid operational landslide inventory mapping, 23–28 April 2017. Paper presented at the EGU General Assembly Conference.

  • Van Westen, C., Van Asch, T. W., & Soeters, R. (2006). Landslide hazard and risk zonation—Why is it still so difficult? Bulletin of Engineering Geology and the Environment, 65(2), 167–184. https://doi.org/10.1007/s10064-005-0023-0

    Article  Google Scholar 

  • Wang, H., Zhang, L., Yin, K., Luo, H., & Li, J. (2021). Landslide identification using machine learning. Geoscience Frontiers, 12(1), 351–364. https://doi.org/10.1016/j.gsf.2020.02.012

    Article  Google Scholar 

  • Yang, W., Qi, W., Wang, M., Zhang, J., & Zhang, Y. (2017). Spatial and temporal analyses of post-seismic landslide changes near the epicentre of the Wenchuan earthquake. Geomorphology, 276, 8–15. https://doi.org/10.1016/j.geomorph.2016.10.010

    Article  Google Scholar 

  • Yang, W., Wang, Y., Sun, S., Wang, Y., & Ma, C. (2019). Using Sentinel-2 time series to detect slope movement before the Jinsha River landslide. Landslides, 16(7), 1313–1324. https://doi.org/10.1007/s10346-019-01178-8

    Article  Google Scholar 

  • Yue, J., Tian, Q., Tang, S., Xu, K., & Zhou, C. (2019). A dynamic soil endmember spectrum selection approach for soil and crop residue linear spectral unmixing analysis. International Journal of Applied Earth Observation and Geoinformation, 78, 306–317. S0303243418306937. https://doi.org/10.1016/j.jag.2019.02.001

Download references

Acknowledgements

The authors are thankful to the Higher Education Commission of Pakistan project number 7445/KPK/NRPU/R&D/HEC/2017 for supporting this study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alam Sher Bacha.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's Note

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

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 3524 KB)

Rights and permissions

Springer Nature or its licensor 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

Bacha, A.S., Shafique, M., van der Werff, H. et al. Spatio-temporal landslide inventory and susceptibility assessment using Sentinel-2 in the Himalayan mountainous region of Pakistan. Environ Monit Assess 194, 845 (2022). https://doi.org/10.1007/s10661-022-10514-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-022-10514-w

Keywords

Navigation