Skip to main content

Advertisement

SpringerLink
Log in

Detecting slow-moving landslides in parts of Darjeeling–Sikkim Himalaya, NE India: quantitative constraints from PSInSAR and its relation to the structural discontinuities

  • Original Paper
  • Published:
Landslides Aims and scope Submit manuscript

Abstract

The difficulty of monitoring slow-moving landslides is attributed to its highly dynamic spatial and temporal character, especially in a tectonic regime like the Himalayas, where the control of structural discontinuities to determine the risk at a local and regional scale is essential. Although many methods have been used for landslide monitoring in the past, the identification, measurement and categorization of landslide-induced relative surface displacements, its relevant relationship with relative slope and structural features, and forecasting remain elusive. The present work explores a holistic approach towards studying slow-moving landslides in and around the urban locales (Darjeeling, Kalimpong and Gangtok) of Darjeeling–Sikkim Himalaya. In order to establish an effective relationship, 109 successive C-band Sentinel-1A dataset acquired from February 2017 to October 2020 has been analysed using PSInSAR to identify the potential landslide risk zone in the selected blocks. Results indicate nearly 10.63% (~ 42km2) of the total Sikkim monitoring area (~ 395km2) is subjected to a 20-40 mm/yr of mean annual displacement rate and thus considered to be under the expression of potential risk. The contextual relationship between slope instabilities and regional thrusts/faults is also established. The derived time series displacement estimates are further integrated with corresponding slope estimates derived from the ALOS PALSAR DEM to determine the nature of Line of Sight (LOS) displacement followed by its classification into different categories and are further used in forecasting using ARIMA (1,1,1; 2,1,1) model. Results indicated that the area may experience cumulative displacement of 200-240 mm with a predicted 2.5–threefold increase between 2020 and 2023.

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

Similar content being viewed by others

References

  • Acharyya (1994) The Cenozoic foreland basin and tectonics of the eastern sub-Himalaya: problems and prospects. Him Geol 15:3–21

    Google Scholar 

  • Angeli M, Pasuto A, Silvano S (2000) A critical review of landslide monitoring experiences. Eng Geol 55:133–147

    Article  Google Scholar 

  • Aslan G, Foumelis M, Raucoules D, De MM, Bernardie S, Cakir Z (2020) Landslide mapping and monitoring using Persistent Scatterer Interferometry (PSInSAR) technique in the French Alps. Remote Sens 12:1305

    Article  Google Scholar 

  • Bakon M, Perissin D, Lazecky M, Papco J (2014) Infrastructure Non-linear Deformation Monitoring Via Satellite Radar Interferometry. Procedia Technol 16:294–300

    Article  Google Scholar 

  • Bamler R, Hartl P (1998) Synthetic aperture radar interferometry. Inverse Probl 14(4):1–54

    Article  Google Scholar 

  • Banerjee S (2016) Structure and kinematics of the Ramgarh Thrust Sheet, Darjiling-Sikkim Himalaya. Ph.D. Dissertation 226p. University of Calcutta

  • Banerjee S, Matin A, Mukul M (2015) Overburden-induced flattening structure in the Himalaya: mechanism and implication. Curr Sci 109:1814–1821

    Article  Google Scholar 

  • Banerjee S, Srivastava HB (2020) Tectonic Implications of Small-Scale Structures in the Main Central Thrust Zone of Garhwal Higher Himalaya. Structural Geometry of Mobile Belts of the Indian Subcontinent 213–232

  • Basu S K (2013) Geology of Sikkim state and Darjeeling district of West Bengal. Geol Soc Ind. Bangalore

  • Bhattacharyya K, Mitra G (2009) A new kinematic evolutionary model for the growth of a duplex—an example from the Rangit duplex, Sikkim Himalaya, India. Gond Res 16:697–715

    Article  Google Scholar 

  • Bhattacharyya K, Mitra G, Kwon S (2015) Geometry and kinematics of the Darjeeling-Sikkim Himalaya, India: Implications for the evolution of the Himalayan fold-thrust belt. J of Asian Earth Sci 113:778–796

    Article  Google Scholar 

  • Blasco JMD, Foumelis M, Stewart C, Hooper A (2019) Measuring Urban Subsidence in the Rome Metropolitan Area (Italy) with Sentinel-1 SNAP-StaMPS Persistent Scatterer Interferometry. Remote Sens 11:129

    Article  Google Scholar 

  • Box GEP, Jenkins G, Gregory RC, Ljung GM (2015) Time series analysis: forecasting and control. Wiley

    Google Scholar 

  • Bui DT, Tuan TA, Klempe H, Pradhan B, Revhaug I (2016) Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree. Landslides 16:361–377

    Google Scholar 

  • Calvello M, Peduto D, Arena L (2017) Combined use of statistical and D-InSAR data analyses to define the state of activity of slow-moving landslides. Landslides 14:1–17

    Article  Google Scholar 

  • Cao N, Lee H, Jung HC (2016) A Phase-Decomposition-Based PSInSAR Processing Method IEEE Transactions on Geosci and Remote Sens 54(2):1074–1090

    Google Scholar 

  • Chakraborty I, Ghosh S, Bhattacharya D, Bora A (2011) Earthquake induced landslides in the Sikkim-Darjeeling Himalayas-An aftermath of the 18th September 2011 Sikkim earthquake. Report of Geological Survey of India, Kolkata

  • Chakraborty S, Mukul M (2019) New insights into the position and geometry of the Main Central Thrust from Sikkim, eastern Himalaya. The J Geol 127(3):289–322

    Article  Google Scholar 

  • Chen W, Xie X, Peng J, Shahabi H, Hong H, Bui DT, Zhao D, Li S, Zhu A-X (2018) GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method. CATENA 164:135–149

    Article  Google Scholar 

  • Colesanti C, Ferretti A, Prati C, Rocca F (2003) Monitoring landslides and tectonic motions with the Permanent Scatterers Technique. Eng Geol 68:3–14

    Article  Google Scholar 

  • Corominas J, Moya J, Lloret A, Gili JA, Angeli MG, Pasuto A, Silavno S (2000) Measurement of landslide displacements using a wire extensometer. Eng Geol 55:149–166

    Article  Google Scholar 

  • Crosetto M, Monserrat O, Cuevas M, Crippa B (2011) Spaceborne differential SAR interferometry: data analysis tools for deformation measurement. Remote Sens 3:305–318

    Article  Google Scholar 

  • Crosetto M, Monserrat O, Cuevas-González M, Devanthéry N, Crippa B (2016) Persistent Scatterer Interferometry: A review. ISPRS J Photogramm Remote Sens 115:78–89

    Article  Google Scholar 

  • Cruden DM, Varnes DJ (1996) Landslide Types and Processes, Transportation Research Board, U.S. National Academy of Sciences Special Report 247:36–75

    Google Scholar 

  • DeCelles PG, Gehrels GE, Quade J, Ojha TP (1998) Eocene-early Miocene foreland basin development and the history of Himalayan thrusting, western and central Nepal. Tectonics 17(5):741–765

    Article  Google Scholar 

  • DeCelles PG, Robinson DM, Zandt G (2002) Implications of shortening in the Himalayan fold-thrust belt for uplift of the Tibetan Plateau. Tectonics 21(6):1062

  • Du G, Zhang Y, Yang Z, Guo C, Xin Y (2018) Landslide susceptibility mapping in the region of eastern Himalayan syntaxis, Tibetan Plateau, China: a comparison between analytical hierarchy process information value and logistic regression-information value methods. Bull Eng Geol and the Environ 78:4201–4215

    Article  Google Scholar 

  • Fanti R, Gigli G, Lombardi L, Tapete D, Canuti P (2012) Terrestrial laser scanning for rockfall stability analysis in the cultural heritage site of Pitigliano (Italy). Landslides 10(4):409–420

    Article  Google Scholar 

  • Farina P, Colombo D, Fumagalli A, Marks F, Moretti S (2006) Permanent Scatterers for landslide investigations: outcomes from the ESA-SLAM project. Eng Geol 88:200–217

    Article  Google Scholar 

  • Fattah J, Ezzine L, Aman Z, Moussami HE, Lachhab A (2018) Forecasting of demand using. ARIMA Model, Int J EnginBusiManag 10:1–9

    Google Scholar 

  • Ferretti A, Prati C, Rocca F (2000) Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE Trans Geosci Remote Sens 38:2202–2212

  • Ferretti A, Prati C, Rocca F (2001) Permanent Scatterers in SAR interferometry. IEEE Trans Geosci Remote Sens 39:8–20

    Article  Google Scholar 

  • Fertl WH (1976) Abnormal Formation Pressures: Developments in Petroleum Science. Elsevier, New York

    Google Scholar 

  • Froude MJ, Petley DN (2018) Global Fatal Landslide Database Web Application: non-seismic landslide events between 2004 and 2016. Nat Hazards Earth Sys Sci 18:2161–2181

    Article  Google Scholar 

  • Gansser A (1964) Geology of the Himalayas. Wiley London

  • Geological Survey of India (GSI) (2021) Landslide hazard. https://www.gsi.gov.in/webcenter/portal/OCBIS/pageGeoInfo/pageLANDSLIDEHAZRD?_adf.ctrl-state=bo468vfqm_34&_afrLoop=35747241032559044#!

  • Ghosh P, Bhattacharyya K, Parui C (2020) Tracking progressive deformation of an orogenic wedge through two successive internal thrusts: Insights from structure, deformation profile, strain, and vorticity of the Main Central thrust (MCT) and the Pelling-Munsiari thrust (PT), Sikkim Himalayan fold thrust belt. J Str Geol 140:104–120

    Article  Google Scholar 

  • Gili JA, Corominas J, Rius J (2000) Using Global Positioning System techniques in landslide monitoring. Eng Geol 55:167–192

    Article  Google Scholar 

  • Hilley GE, Burgmann R, Ferretti A, Novali F, Rocca F (2004) Dynamics of slow-moving landslides from permanent scatterer analysis. Science 304:1952–1955

    Article  Google Scholar 

  • Hooper A (2008) A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches.Geophys Res Lett 35:1–5

  • Hooper A, Segall P, Zebker H (2007) Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos. J Geophys Res 112:B07407

  • Hu Z, Mallorquí JJ (2019) An Accurate Method to Correct Atmospheric Phase Delay for InSAR with the ERA5 Global Atmospheric Model. Remote Sens 11(17):1969

    Article  Google Scholar 

  • Jia H, Liu L (2016) A technical review on persistent scatterer interferometry. J Mod Trans 24(2):153–158

    Article  Google Scholar 

  • Junior DS de, OS, de Oliver, JFL, Neto PSG, de M (2019) An intelligent hybridization of ARIMA with machine learning models for time series forecasting. Know Bas Sys 175:72–86

  • Kaab A (2000) Photogrammetry for early recognition of high mountain hazards: New techniques and applications. Phys Chem Earth 25:765–770

    Article  Google Scholar 

  • KrishnaKumar V, Monserrat O, CrosettoM,Crippa B (2018) Atmosphere Phase Delay In Sentinel SAR Interferometry. In ISPRS TC III Mid-term Symp 7–10 May Beijing China 741–744

  • Kundu A, Matin A, Mukul M (2012) Depositional environment and provenance of Middle Siwalik sediments in Tista valley, Darjiling District, Eastern Himalaya. India J of Earth Sys Sci 121(1):73–89

    Article  Google Scholar 

  • Li B, Wang N, Chen J (2021) GIS-Based Landslide Susceptibility Mapping Using Information, Frequency Ratio, and Artificial Neural Network Methods in Qinghai Province, Northwestern China. Advances in Civil Eng 4758062. https://doi.org/10.1155/2021/4758062

  • Li Z, Cao Y, Wei J, Duan M, Wu L, HouJ, Zhu J (2019) Time series InSAR ground displacement monitoring: Atmospheric delay modeling and estimating, Earth-Sci Rev 192L258–284

  • Liao MS, Tang J, Wang T, Balz T, Zhang L (2012) Landslide monitoring with high-resolution SAR data in the Three Gorges region. Sci China Earth Sci 55:590–601

    Article  Google Scholar 

  • Lu L, Liao M (2008) Subsidence measurement with PSInSAR techniques in Shanghai Urban. Int Arch Photogramm Remote Sens Spat Inf Sci 37:173–178

    Google Scholar 

  • Lu P, Catani F, Tofani V, Casagli N (2014) Quantitative hazard and risk assessment for slow moving landslides from persistent scatterer interferometry. Landslides 11:685–696

    Article  Google Scholar 

  • Mantovani F, Soeters R, Westen CJV (1996) Remote sensing techniques for landslide studies and hazard zonation in Europe. Geomorphology 15(3–4):2130225

    Google Scholar 

  • McQuarrie N, Ehlers TA, Bames JB, Meade B (2008) Temporal Variation in Climate and Tectonic Coupling in Central Andes. Geology 36(12):999–102

    Article  Google Scholar 

  • Mukherjee A, Sharma P K (2013) Geology and mineral resources of West Bengal; Report; Geol Sur of Ind, West Bengal Kolkata

  • Mukul M (2010) First-order kinematics of wedge-scale active Himalayan deformation; insights from Darjiling–Sikkim–Tibet (DaSiT) wedge. J of Asian Ear Sci 39(6):645–657

    Article  Google Scholar 

  • Mukul M, Jade S, Ansari K, Matin A (2014) Seismotectonic implications of strike-slip earthquakes in the Darjiling-Sikkim Himalaya. Curr Sci 106:198–210

    Google Scholar 

  • Nath SK, Sengupta A, Srivastava A (2021) Remote sensing GIS-based landslide susceptibility & risk modeling in Darjeeling-Sikkim Himalaya together with FEM-based slope stability analysis of the terrain. Nat Haz 108:3271–3304

    Article  Google Scholar 

  • Nelson KD, Zhao W, Brown LD, Kuo J, Che J, Liu X, Klemperer SL, Makovsky Y, Meissner RJ, Mechie J, Kind R (1996) Partially molten middle crust beneath southern Tibet: Synthesis of project INDEPTH results. Sci 274(5293):1684–1688

    Article  Google Scholar 

  • Onagh M, Kumra VK, Rai PK (2012) Landslide Susceptibitily Mapping in a Part of Uttarkashi District (India) by Multiple Linear Regression Method. Int J Geo. Earth and Environ Sci 2(2):102–120

  • Osmanoglu B, Sunar F, Wdowinski S, Cana-Cabral E (2016) Time series analysis of InSAR data: Methods and trends, ISPRS J of Photogram and Remote Sens 11590–102

  • Pal R, Biswas SS, Mondal B, Pramanik MK (2016) Landslides and floods in the Tista Basin (Darjeeling and Jalpaiguri Districts): historical evidence, causes and consequences. J IndGeophyUni 20(2):66–72

    Google Scholar 

  • Parui C, Bhattacharyya K (2018) Duplex and along-strike structural variation: A case study from Sikkim Himalayan fold thrust belt. J of Structural Geol 113:62–75

    Article  Google Scholar 

  • Pancioli V, Raetzo H, Campolmi T, Casagli N (2008) Terrafirma Landslide Services for Europe based on Space-borne InSAR Data. In Proceedings of the First World Landslide Forum Tokyo Japan 81–84

  • Pearson ON, DeCelles PG (2005) Structural geology and regional tectonic significance of the Ramgarh thrust, Himalayan fold‐thrust belt of Nepal. Tectonics, 24(4):TC4008

  • Perissin D, Wang T (2012) Repeat-pass SAR interferometry with partially coherent targets. IEEE Trans Geosci Remote Sens 50:271–280

    Article  Google Scholar 

  • Pradhan B (2013) A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS. Comp & Geosci 51:350–365

    Article  Google Scholar 

  • Qiu Z, Ma Y, Guo X (2016) Atmospheric phase screen correction in ground-based SAR with PS technique. Springer plus 5:1594

    Article  Google Scholar 

  • Rahman G, Rahman, A-U, Bacha A, Mahmood S, Moazzam M, Lee B (2021) Assessment of Landslide Susceptibility using Weight of Evidence and Frequency Ratio Model in Shahpur Valley, Eastern Hindu Kush. Nat Haz and Earth Sys Sci https://doi.org/10.5194/nhess-2020-167

  • Rubinkiewicz J (2007) Fold-thrust-belt geometry and detailed structural evolution of the Silesian nappe–eastern part of the Polish Outer Carpathians (Bieszczady Mts.). Acta Geol Pol 57(4):479–508

  • Shang Y, Park HD, Yang Z, Yang J (2005) Distribution of landslides adjacent to the northern side of the YarluTsangpo Grand Canyon in Tibet, China. Environ Geol 48:721–741

    Article  Google Scholar 

  • Sibson R (1977) Fault rock s and fault mechanisms. Geol Soc Lond J 133:191–231

    Article  Google Scholar 

  • Singhroy V, Molch K (2004) Characterizing and monitoring rockslides from SAR techniques. Adv Space Res 33:290–295

    Article  Google Scholar 

  • Srivastava P, Mitra G (1994) Thrust geometries and deep structure of the outer and inner Lesser Himalaya, Kumaun and Garhwal (India): Implications for evolution of the Himalayan foldandthrust belt. Tectonics 13(1):89109

    Article  Google Scholar 

  • Strozzi T, Delaloye R, Kääb A, Ambrosi C, Perruchoud E, Wegmüller U (2010) Combined observations of rock mass movements using satellite SAR interferometry, differential GPS, airborne digital photogrammetry, and airborne photography interpretation. J Geophys Res 115:F1

    Google Scholar 

  • Tamburini A, Bianchi M, Giannico C, Novali F (2010) Retrieving surface deformation by PSInSAR TM technology: A powerful tool in reservoir monitoring. Int J Greenh Gas Control 4:928–937

    Article  Google Scholar 

  • Tofani V, Raspini F, Catani F, Casagli N (2013) Persistent Scatterer Interferometry (PSInSAR) Technique for Landslide Characterization and Monitoring. Remote Sens 15(3):1545–1565

    Google Scholar 

  • Valdiya KS (2016) The making of India: Geodynamic evolution. Springer, Cham

    Book  Google Scholar 

  • Wasowski J, Bovenga F (2012) Investigating landslides and unstable slopes with satellite Multi Temporal Interferometry. Current Issues and Future Perspectives 174:103–138

    Google Scholar 

  • Woodhouse IH (2005) Introduction to Microwave Remote Sensing. Taylor & Francis

    Google Scholar 

  • Xiao R, He X (2013) GPS and InSAR Time Series Analysis: Deformation Monitoring Application in a Hydraulic Engineering Resettlement Zone, Southwest China. Mathematical Probl in Eng 601209:1–11

    Google Scholar 

  • Yazici BV, Gormus ET (2020) Investing persistent scatterer InSAR (PSInSAR) technique efficiency for landslides mapping: a case study in Artvin dam areain Turkey. Geocarto Int. https://doi.org/10.1080/10106049.2020.1818854

    Article  Google Scholar 

  • Yin A (2006) Cenozoic tectonic evolution of the Himalayan orogen as constrained by along-strike variation of structural geometry, exhumation history, and foreland sedimentation. Ear Sci Rev 76:1–131

    Article  Google Scholar 

  • Yu C, Li Z, Penna NT (2018) Interferometric synthetic aperture radar atmospheric correction using a GPS-based iterative tropospheric decomposition model. Remote Sens Environ 204:109–121

    Article  Google Scholar 

  • Zebker HA, Rosen PA, Hensley S (1997) Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps. J Geophys Res 102:7547–7563

    Article  Google Scholar 

  • Zhang Y, Guo C, Lan H, Zhou N, Yao X (2015) Reactivation mechanism of ancient giant landslides in the tectonically active zone: a case study in Southwest China. Environ Earth Sci 74(2):1719–1729

    Article  Google Scholar 

Download references

Acknowledgements

The authors acknowledge the Institute of Eminence (IoE), Banaras Hindu University (BHU), for extending the financial and administrative support to conduct this work. The authors would also thank Alaska Satellite Facility-Distributed Active Archive Centre (ASF DAAC) for providing multiple scenes of the Sentinel-1A dataset. The present investigation contains data related to the PhD work of SS.

Author information

Authors and Affiliations

  1. Remote Sensing & GIS Lab, Department of Geology, Institute of Science, Banaras Hindu University, Varanasi, 221005, India

    Saurabh Singh & Ashwani Raju

  2. Laboratory for Analyses of Magnetic and Petrofabric, Department of Geology, Institute of Science, Banaras Hindu University, Varanasi, 221005, India

    Sayandeep Banerjee

Authors
  1. Saurabh Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ashwani Raju
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sayandeep Banerjee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ashwani Raju.

Ethics declarations

Conflict of interest

No potential competing interest was reported by the authors.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singh, S., Raju, A. & Banerjee, S. Detecting slow-moving landslides in parts of Darjeeling–Sikkim Himalaya, NE India: quantitative constraints from PSInSAR and its relation to the structural discontinuities. Landslides 19, 2347–2365 (2022). https://doi.org/10.1007/s10346-022-01900-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10346-022-01900-z

Keywords

Search

Navigation