ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 4, pp. 141-149

Interactive map of active landslides and subsiding areas for the Central and Adler regions of the Big Sochi based on InSAR data for the period 2015–2021

E.I. Smolianinova 1 , V.O. Mikhailov 1 , P.N. Dmitriev 1 
1 Schmidt Institute of Physics of the Earth RAS, Moscow, Russia
Accepted: 25.07.2022
DOI: 10.21046/2070-7401-2022-19-4-141-149
We present an interactive map of surface deformations for the Central and Adler regions of the Big Sochi area based on the InSAR Sentinel-1A data from ascending 43A (167 images) and descending 123D (140 images) acquisitions for the period 2015–2021. SBAS ENVI SARScape v.5.3 software was used for processing. Methods of calculations and analysis of results are described in detail in 2019–2021. Evaluation version of the NextGIS QGIS software was incorporated for mapping. In the end of the InSAR processing displacements of the Earth’s surface and buildings in the satellite line of site direction (Ulos) were calculated and the mean displacement rates Vlos were mapped. The results are presented on the map as Vlos layers. Areas where absolute values of Vlos exceed 20 mm/Y are considered as Active Deformation Areas (ADA) and shown according to the direction of movements in red (from satellite) or blue (towards satellite). The most significant ADA are marked with numbers, and times series graphs of displacements for them are presented in popup windows. Brief interpretation of deformation character pictured in time series graphs can be found in Attributes tab. There is also a specific layer containing active landslide occurrences mapped in accordance with field data of FGBU Gidrospecgeologia. It was shown that InSAR and field data complement each other. This motivates joint usage of InSAR surface deformation maps together with landslides risk assessment maps based on field data. The presented visualization of InSAR data as an interactive map opens possibilities for complex use of InSAR data together with other GIS maps. In the Big Sochi area having high landslide risk and constant growing of man-made load, interactive maps based on InSAR and various field data make it possible to considerably improve the existing monitoring systems of landslides and areas of subsidence. The map is available at:

Keywords: SAR, InSAR, satellite monitoring, landslides, subsidence, interactive map, Sentinel-1A, Big Sochi
Full text


  1. Vozhik A. A., Risk assessment of exogenetic geological processes in the course of state monitoring of the state of the subsurface, 8 sth Vserossiiskii s″ezd geologov 26–28 oktyabrya 2016 g. Prezentatsionnye materially kruglogo stola “Gosudarstvennyi monitoring sostoyaniya nedr i regional’nye gidrogeologicheskie raboty” (8th All-Russia Congress of Geologists 26–28 October 2016. Presentations of the round table meeting “State monitoring of the state of the subsurface and regional hydrogeological projects”), Moscow, 2016, 71 p., available at: (accessed 20.05.2021) (in Russian).
  2. Dmitriev P. N., Golubev V. I., Isaev Yu. S., Kiseleva E. A., Mikhailov V. O., Smolianinova E. I., On processing and interpretation of SAR interferometry data in case of landslide monitoring), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2012, Vol. 9, No. 2, pp. 130–142 (in Russian).
  3. Zakharov A. I., Zakharova L. N., Long-term monitoring of the Bureya Landslide area by Radar Interferometry, Materialy 18-i Vserossiiskoi otkrytoi konferentsii “Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa”(Proc. 18th All-Russia Open Conf.“Current Problems in Remote Sensing of the Earth from Space“), 16–20 Nov. 2020, Moscow: IKI RAN, 2020, p. 285 (in Russian), DOI: 10.21046/18DZZconf-2020a.
  4. Zakharov A. I., Zakharova L. N., Krasnogorskii M. G., Monitoring Landslide Activity by Radar Interferometry Using Trihedral Corner Reflectors,  Issledovaniya Zemli iz kosmosa, 2018, No. 3, pp. 80–92 (in Russian), DOI: 10.7868/S0205961418030065.
  5. Zakharova L. N., Zakharov A. I., Interferometric Observation of Landslide Area Dynamics on the Bureya River by Means of Sentinel-1 Radar Data in 2017–2018, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 2, pp. 273–277 (in Russian), DOI: 10.21046/2070-7401-2019-16-2-273-277.
  6. Kazakov E. E., Kiselev R. V., NextGIS platform: a complex solution for enterprise spatial data infrastructure, Geoprofi, 2021, No. 6, pp. 11–15 (in Russian), available at:
  7. Smolianinova E. I., Mikhailov V. O., Interactive map of active landslides and subsiding areas for the Central and Adler regions of the Big Sochi based on InSAR data for the period 2015–2021, Materialy 19-i mezhdunaronoi konferentsii “Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa” (Proc. 19th Intern. Conf. “Current Problems in Remote Sensing of the Earth from Space”), 15–19 Nov. 2021, Moscow: IKI RAN, 2021, p. 111 (in Russian), DOI: 10.21046/19DZZconf-2021a.
  8. Smolianinova E. I., Kiseleva E. A., Mikhailov V. O., Sentinel-1 InSAR for Investigation of Active Deformation Areas: Case Study of the coastal region of the Big Sochi, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 5, pp. 147–155 (in Russian), DOI: 10.21046/2070-7401-2019-16-5-147-155.
  9. Smolianinova E. I., Mikhailov V. O., Dmitriev P. N., Subsidence monitoring in the Imereti lowland (the Big Sochi region) using multifrequency INSAR data for 2007–2019, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 5, pp. 103–117 (in Russian), DOI: 10.21046/2070-7401-2020-17-5-103-113.
  10. Smolianinova E. I., Mikhailov V. O., Dmitriev P. N., Detection and monitoring of active deformation areas in the Adler region of the Big Sochi area based on multifrequency InSAR data for the period 2007–2020, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2021, Vol. 18, No. 4, pp. 55–65, DOI: 10.21046/2070-7401-2021-18-4-55-65.
  11. Berardino P., Fornaro G., Lanari R., Sansosti E., A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms, IEEE Trans. Geoscience and Remote Sensing, 2002, Vol. 40. No. 11, pp. 2375–2383, DOI: 10.1109/TGRS.2002.803792.
  12. Bianchini S., Herrera G., Mateos R., Notti D., Garcia I., Mora O., Moretti S., Landslide activity maps generation by means of Persistent Scatterer Interferometry, Remote Sensing, 2013, Vol. 5, pp. 6198–6222,
  13. Bondur V., Chimitdorzhiev T., Dmitriev A., Dagurov P., Fusion of SAR Interferometry and Polarimetry Methods for Landslide Reactivation Study, the Bureya River (Russia) Event Case Study, Remote Sensing, 2021, Vol. 13, No. 24, Art. No. 5136, 20 p.,
  14. Cigna F., Bianchini S., Casagli N., How to assess landslide activity and intensity with Persistent Scatterer Interferometry (PSI): The PSI-based matrix approach, Landslides, 2013, Vol. 10, pp. 267–283,
  15. Crosetto M., Monserrat O., Cuevas-González M., Devanthéry N., Crippa B., Persistent Scatterer Interferometry: A review, ISPRS J. Photogrammetry and Remote Sensing, 2016, Vol. 115, pp. 78–89,
  16. Mondini A., Guzzetti F., Chang K.-T., Monserrat O., Martha T. R., Manconi A., Landslide failures detection and mapping using Synthetic Aperture Radar: Past, present and future, Earth-Science Reviews, 2021, Vol. 216, Art. No. 103574, 33 p.,
  17. Moretto S., Bozzano F., Mazzanti P., The Role of Satellite In-SAR for Landslide Forecasting: Limitations and Openings, Remote Sensing, 2021, Vol. 13, Art. No. 3735, 33 p.,
  18. Petley D., Using InSAR to create a landslide inventory for the Pacific Northwest, The Landslide Blog, 1 Oct. 2021, available at: (accessed 27.03.2022).
  19. Rosi A., Tofani V., Tanteri L., Tacconi Stefanelli C., Agostini A., Catani F., Casagli N., The new landslide inventory of Tuscany (Italy) updated with PS-InSAR: geomorphological features and landslide distribution, Landslides, 2018, Vol. 15, pp. 5–19, DOI: 10.1007/s10346-017-0861-4.
  20. Solari L., Del Soldato M., Montalti R., Bianchini S., Raspini F., Thuegaz P., Bertolo D., Tofani V., Casagli N., A Sentinel-1 based hot-spot analysis: landslide mapping in northwestern Italy, Intern. J. Remote Sensing, 2019, Vol. 40, No. 20, pp. 7898–7921, DOI: 10.1080/01431161.2019.1607612.
  21. Solari L., Del Soldato M., Raspini F., Barra A., Bianchini S., Confuorto P., Casagli N., Crosetto M., Review of Satellite Interferometry for Landslide Detection in Italy, Remote Sensing, 2020, Vol. 12, No. 8, Art. No. 1351, 29 p.,
  22. Zhou S., Ouyang C., Huang Y., An InSAR and depth-integrated coupled model for potential landslide hazard assessment, Acta Geotechnica, 2022, Vol. 17, pp. 3613–3632,
  23. Zinno I., Bonano M., Buonanno S., Casu F., De Luca C., Manunta M., Manzo M., Lanari R., National Scale Surface Deformation Time Series Generation through Advanced DInSAR Processing of Sentinel-1 Data within a Cloud Computing Environment, IEEE Trans. Big Data, 2020, Vol. 6, No. 3, pp. 558–571, DOI: 10.1109/TBDATA.2018.2863558.