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Long-term InSAR, borehole inclinometer, and rainfall records provide insight into the mechanism and activity patterns of an extremely slow urbanized landslide

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Abstract

New radar satellites provide global coverage and the possibility of long-term, regular frequency (days-weeks) surface displacement measurements through the application of high precision multi-temporal InSAR (Synthetic Aperture Radar Interferometry) techniques. This represents an excellent opportunity to investigate and improve our understanding of the behavior of extremely slow landslides, as well as of the long- to short-term controls of their activity. In urban settings, such landslides deserve special attention, as their cumulative movements can cause significant socio-economic damage. Here, we re-examine the case of a long-lived, deep-seated landslide in the Apennine Mountains (Italy) which was urbanized between the late 1970s and early 2000s. The case provides a rare opportunity to highlight the benefits of the integrated analysis of long-term (several years) borehole inclinometer measurements with 15 years of multi-temporal InSAR displacement data. We present evidence of the landslide composite nature and asymmetry, and draw attention to the recent period of accelerated movement that coincided with the foot failure event. This helps constraining the interpretation of the borehole and InSAR data and demonstrating the predominantly rotational landslide mechanism. We show how a detailed analysis of sparse inclinometer and more spatially continuous InSAR measurements, when combined with local rainfall records, can reveal long- to short-term patterns of temporal variability in landslide motions and allow anticipating the consequences of future landslide activity.

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References

  • Annali idrologici http://www.protezionecivile.puglia.it/centro-funzionale/analisielaborazione-dati and http://93.57.89.4:8081/temporeale/meteo/stazioni (last accessed 30.04.2019) (in Italian)

  • Baum R, Messerich J, Fleming R (1998) Surface deformation as a guide to kinematics and three-dimensional shape of slow-moving, clay-rich landslides, Honolulu, Hawaii. Environ Eng Geosci IV(3):283–306

    Article  Google Scholar 

  • Bovenga F, Refice A, Nutricato R, Guerriero L, Chiaradia MT (2005) SPINUA: a flexible processing chain for ERS/ ENVISAT long term Interferometry. Proceedings of ESA- ENVISAT Symposium, September 6–10, 2004, Salzburg, Austria. ESA Special Publication SP-572, CD-ROM

  • Bovenga F, Nutricato R, Refice A, Wasowski J (2006) Application of multi-temporal differential interferometry to slope instability detection in urban/peri-urban areas. Eng Geol 88(3–4):218–239

    Article  Google Scholar 

  • Bovenga F, Wasowski J, Nutricato R, Nitti DA, Chiaradia MT (2012) Using Cosmo/SkyMed X-band and ENVISAT C-band SAR Interferometry for landslide analysis. Remote Sens Environ 119:272–285

    Article  Google Scholar 

  • Calò F, Ardizzone F, Castaldo R, Lollino P, Tizzani P, Guzzetti F, Lanari L, Angeli M-C, Pontoni F, Manunta M (2014) Enhanced landslide investigations through advanced DInSAR techniques: the Ivancich case study, Assisi, Italy. Remote Sensing Environment 142:69–82

    Article  Google Scholar 

  • Carey JM, Moore R, Petley DN (2015) Patterns of movement in the Ventor landslide complex, Isle of Wight, southern England. Landslides 12:1107–1118

    Article  Google Scholar 

  • CARG (2011) Carta Geologica d’Italia at a 1:50,000 scale, Sheet 421 Ascoli Satriano, 2011. CARG Project, ISPRA, SystemCart, Roma

  • Colesanti C, Wasowski J (2006) Investigating landslides with space-borne Synthetic Aperture Radar (SAR) interferometry. Eng Geol 88(3–4):174–199

    Google Scholar 

  • Cotecchia F, Vitone C, Petti R, Soriamo I, Santaloia F, Lollino P (2016) Slow landslides in urbanised clayey slopes: an emblematic case from the south of Italy. In: Aversa et al (eds) Landslides and engineered slopes. Experience, theory and practice. CRC Press, pp 691–698

  • Cruden DM, Lan H-X (2015) Using the working classification of landslides to assess the danger from a natural slope. In: Lollino G et al (eds) Engineering geology for society and territory, vol 2. Springer International Publishing, pp 3–12

  • Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Turner AK, Schuster RL (eds) Landslides investigation and mitigation. Transportation research board, US National Research Council. Special Report 247, Washington, DC, pp 36–75

    Google Scholar 

  • Del Gaudio V, Pierri P, Wasowski J (2003) An approach to time-probabilistic evaluation of seismically induced landslide hazard. Bull Seismol Soc Am 93(2):557–569

    Article  Google Scholar 

  • Del Soldato M, Riquelme A, Bianchini S, Tomàs R, Di Martire D, De Vita P, Moretti S, Calcaterra D (2018) Multisource data integration to investigate one century of evolution for the Agnone landslide (Molise, southern Italy). Landslides 15:2113–2128

    Article  Google Scholar 

  • Ferrari A, Ledesma A, Gonzales DA, Corominas (2011) Effects of the foot evolution on the behavior of slow-moving landslides. Engineering Geology 117:217–228

    Article  Google Scholar 

  • Geudtner D, Torres R, Snoeij P, Davidson M, Rommen B (2014) Sentinel-1 System capabilities and applications. IEEE Geoscience and Remote Sensing Symposium pp 1457–1460

  • Glastonbury JP, Fell R (2008) Geotechnical characteristics of large slow, very slow, and extremely slow landslides. Can Geotech J 45:984–1005

    Article  Google Scholar 

  • IGM (GAI-IGMI flight 1954) (n.d.) Italian Military Geographical Institute. https://www.igmi.org/geoprodotti#b_start=0 (last accessed 30.04.19) (in Italian)

  • Mancini F, Ceppi C, Ritrovato G (2010) GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy. Nat Hazards Earth Syst Sci 10:1851–1864

    Article  Google Scholar 

  • Mancini F, Capra A, Castagnetti C, Ceppi C, Bertacchini E, Rivola R (2015) Contribution of geomatics engineering and VGI within the landslide risk assessment procedures. In: O. Gervasi et al. (Eds.): ICCSA 2015, Part II, LNCS 9156, pp. 635–647. © Springer International Publishing Switzerland 2015

    Chapter  Google Scholar 

  • Mansour M, Morgenstern N, Martin C (2011) Expected damage from displacement of slow moving slides. Landslides 8:117–131

    Article  Google Scholar 

  • Massey CI, Petley DN, McSaveney MJ (2013) Patterns of movement in reactivated landslides. Eng Geol 159:1–19

    Article  Google Scholar 

  • Nutricato R, Wasowski J, Bovenga F, Refice A, Pasquariello G, Nitti DO, Chiaradia MT (2013) C/X-Band SAR interferometry used to monitor slope instability in Daunia, Italy. In: Margottini C et al (eds) Landslide science and practice, vol 2. © Springer-Verlag, Berlin Heidelberg, pp 423–430

    Chapter  Google Scholar 

  • Palmisano F, Vitone C, Cotecchia F (2016) Landslide damage assessment at the intermediate to small scale. In: Aversa et al (eds) Landslides and engineered slopes. Experience, theory and practice. CRC Press, pp 1549–1557

  • Plank S (2014) Rapid damage assessment by means of multi-temporal SAR — a comprehensive review and outlook to sentinel-1. Remote Sens 26:4870–4906

    Article  Google Scholar 

  • Refice A, Spalluto L, Bovenga F, Fiore A, Miccoli MN, Muzzicato P, Nitti DO, Nutricato R, Pasquariello G (2019) Integration of persistent scatterer interferometry and ground data for landslide monitoring: the Pianello landslide (Bovino, Southern Italy). Landslides 16:447–468

    Article  Google Scholar 

  • Rucci A, Ferretti A, Monti Guarnieri A, Rocca F (2012) Sentinel 1 SAR interferometry applications: the outlook for sub millimeter measurements. Remote Sens Environ 120:156–163

    Article  Google Scholar 

  • Tofani V, Raspini F, Catani F, Casagli N (2013) Persistent Scatterer Interferometry (PSI) technique for landslide characterization and monitoring. Remote Sens 5:1045–1065

    Article  Google Scholar 

  • Van Asch TWJ, Van Beek LPH, Bogaard TA (2006) Problems in predicting the mobility of slow-moving landslides. Eng Geol 91:46–55

    Article  Google Scholar 

  • Wasowski J, Bovenga F (2014) Investigating landslides and unstable slopes with satellite multitemporal interferometry: current issues and future perspectives. Eng Geol 174:103–138

    Article  Google Scholar 

  • Wasowski J, Bovenga F (2015) Remote sensing of landslide motion with emphasis on satellite multitemporal interferometry applications: an overview. In: Shroder JF, Davies T (eds) Landslide hazards, risks and disasters. Elsevier Inc, Amsterdam, pp 345–403. https://doi.org/10.1016/B978-0-12-396452-6.00011-2

    Chapter  Google Scholar 

  • Wasowski J, Casarano D, Bovenga F, Refice A, Conte D, Nutricato R, Nitti DO (2008) Landslide-prone towns in Daunia (Italy): PS-interferometry based investigation. In: Chen, Z. et al. (Eds.), Proceedings of the 10th International Symposium on Landslides and Engineered Slopes, Xi’an, pp 513–518

  • Wasowski J, Lamanna C, Gigante G, Casarano D (2012) High resolution satellite imagery analysis for inferring surface-subsurface water relationships in unstable slopes. Remote Sens Environ 124:135–148. https://doi.org/10.1016/j.rse.2012.05.007

    Article  Google Scholar 

  • Wasowski J, Bovenga F, Nutricato R, Nitti DO, Chiaradia MT (2017) Detection and monitoring of slow landslides using sentinel-1 multi-temporal interferometry products. In: Mikos et al. (eds) Advancing culture of living with landslides, vol. 2 Advances in Landslide Science. pp 249–256. ISBN 978–3–319-53497-8

    Google Scholar 

  • Wasowski J, Lamanna C, Casarano D (2010) Influence of land-use change and precipitation patterns on landslide activity in the Daunia Apennines, Italy. Quarterly Journal of Engineering Geology and Hydrogeology 43 (4):387–401

    Article  Google Scholar 

Download references

Acknowledgments

Sentinel-1 and ENVISAT data are provided by ESA (European Space Agency). We thank Raffaele Nutricato and Davide Oscar Nitti of GAPsrl for providing InSAR processing through SPINUA algorithm, and Fabio Bovenga, Salvatore Galicchio, Giuseppe Rampino, and Francesca Santaloia for useful discussions. Constructive comments by the editor and an anonymous reviewer are much appreciated.

Funding

This research is in part supported by Regione Puglia-Civil Protection Department, within the project “Integrated assessment of geo-hydrological instability phenomena in the Apulia region, interpretative models and definition of rainfall thresholds for landslide triggering” funded by P.O.R. Puglia 2014-2020, Asse V-Azione 5.1. Project number: B82F16003840006.

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  1. Research Institute for the Geo-hydrological Protection (IRPI), National Research Council (CNR), Bari, Italy

    Janusz Wasowski & Luca Pisano

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  1. Janusz Wasowski
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  2. Luca Pisano
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Correspondence to Janusz Wasowski.

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Wasowski, J., Pisano, L. Long-term InSAR, borehole inclinometer, and rainfall records provide insight into the mechanism and activity patterns of an extremely slow urbanized landslide. Landslides 17, 445–457 (2020). https://doi.org/10.1007/s10346-019-01276-7

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