Abstract
The results of the study of the condition of the territory and waste deposits of the Baikalsk Pulp and Paper Mill using radar and optical satellite data are presented. The Earth’s surface deformations in the area of waste deposits are analyzed using the method of differential radar interferometry applied to the ALOS-2 PALSAR-2 L-band radar satellite data. By processing the C-band radar data from the Sentinel-1B satellite using the method of multitemporal SBAS interferometric measurements, two blocks are found in the study area, one of which is rising and the other one of which is subsiding. The difference between deformations over the period from 2017 to 2020 reached 17–19 mm. A significant correlation in determining waste water content between radar-backscatter intensity measurements (Sentinel-1B satellite) and optical data (Sentinel-2A/B satellites) using the NDWI water index is revealed.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1134%2FS0001433821120045/MediaObjects/11485_2022_8575_Fig1_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1134%2FS0001433821120045/MediaObjects/11485_2022_8575_Fig2_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1134%2FS0001433821120045/MediaObjects/11485_2022_8575_Fig3_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1134%2FS0001433821120045/MediaObjects/11485_2022_8575_Fig4_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1134%2FS0001433821120045/MediaObjects/11485_2022_8575_Fig5_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1134%2FS0001433821120045/MediaObjects/11485_2022_8575_Fig6_HTML.png)
Similar content being viewed by others
REFERENCES
Akopian, S.Ts., Bondur, V.G., and Rogozhin, E.A., Technology for monitoring and forecasting strong earthquakes in Russia with the use of the seismic entropy method, Izv., Phys. Solid Earth, 2017, vol. 53, no. 1, pp. 32–51. https://doi.org/10.1134/S1069351317010025
Amani, M., Ghorbanian, A., Ahmadi, S.A., Kakooei, M., Moghimi, A., Mirmazloumi, S.M., Moghaddam, S.H.A., Mahdavi, S., Ghahremanloo, M., Parsian, S., Wu, Q., and Brisco, B., Google Earth engine cloud computing platform for remote sensing big data applications: A comprehensive review, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 2020, vol. 13, pp. 5326–5350. https://doi.org/10.1109/JSTARS.2020.3021052
Berardino, P., Fornaro, G., Lanari, R., and Sansosti, E., A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms, IEEE Trans. Geosci. Remote Sens., 2002, vol. 40, no. 11, pp. 2375–2383.
Bogdanov, A.V., Shatrova, A.S., and Kachor, O.L., Development of an environmentally friendly waste disposal technology at the Baikal PPM), Geoekol. Inzh. Geol., Gidrogeol., 2017, no. 2, pp. 47–53.
Bondur, V.G. and Gaponova, E.V., Remotely registering anomalous variations in lineament systems for the Baikal Rift zone during the M = 5.6 earthquake of September 21, 2020, Izv., Atmos. Ocean. Phys., 2021, vol. 57, no. 9, pp. 1012–1020. https://doi.org/10.1134/S0001433821090437
Bondur, V.G. and Smirnov, V.M., Method for monitoring seismically hazardous territories by ionospheric variations recorded by satellite navigation systems, Dokl. Earth Sci., 2005, vol. 403, no. 5, pp. 736–740.
Bondur, V.G. and Zverev, A.T., A method of earthquake forecast based on the lineament analysis of satellite images, Dokl. Earth Sci., 2005, vol. 402, no. 4, pp. 561–567.
Bondur, V.G., Garagash, I.A., Gokhberg, M.B., Lapshin, V.M., Nechaev, Yu.V., Steblov, G.M., and Shalimov, S.L., Geomechanical models and ionospheric variations related to strongest earthquakes and weak influence of atmospheric pressure gradients, Dokl. Earth. Sci., 2007, vol. 414, no. 1, pp. 666–669.
Bondur, V.G., Pulinets, S.A., and Kim, G.A., Role of variations in galactic cosmic rays in tropical cyclogenesis: Evidence of hurricane Katrina, Dokl. Earth Sci., 2008, vol. 422, pp. 1124–1128.
Bondur, V.G., Garagash, I.A., Gokhberg, M.B., Lapshin, V.M., and Nechaev, Yu.V., Connection between variations of the stress-strain state of the Earth’s crust and seismic activity: The example of Southern California, Dokl. Earth. Sci., 2010, vol. 430, no. 3, pp. 147–150.
Bondur, V.G., Garagash, I.A., Gokhberg, M.B., and Rodkin, M.V., The evolution of the stress state in Southern California based on the geomechanical model and current seismicity, Izv., Phys. Solid Earth, 2016, vol. 52, no. 1, pp. 117–128. https://doi.org/10.1134/S1069351316010043
Bondur, V.G., Zakharova, L.N., Zakharov, A.I., Chimitdorzhiev, T.N., Dmitriev, A.V., and Dagurov, P.N., Monitoring landslide processes by means of L-band radar interferometric observations: Using the example of the Bureya River bank caving, Izv., Atmos. Ocean. Phys., 2020, vol. 56, no. 9, pp. 1053–1061.
Bondur, V.G., Chimitdorzhiev, T.N., Tubanov, Ts.A., Dmitriev, A.V., and Dagurov, P.N., Analysis of the block-fault structure dynamics in the area of earthquakes in 2008 and 2020 near southern Lake Baikal by the methods of satellite radiointerferometry, Dokl. Earth Sci., 2021, vol. 499, no. 2, pp. 648–653.
Chebykin, E.P., Dambinov, Yu. A., and Suturin, A.N., Multi-element analysis of above-sludge water in accumulation cells of the Baykalsk pulp and paper mill for the strategy of its territorial remediation, Voda Ekol.: Probl. Resheniya, 2020, no. 4, pp. 67–80. https://doi.org/10.23968/2305-3488.2020.25.4.67-80
Chimitdorzhiev, T.N., Dagurov, P.N., Bykov, M.E., Dmitriev, A.V., and Kirbizhekova, I.I., Comparison of ALOS PALSAR interferometry and field geodetic leveling for marshy soil thaw/freeze monitoring, case study from the Baikal Lake region, Russia, J. Appl. Remote Sens., 2016, vol. 10, no. 1, p. 016006.
Cigna, F. and Tapete, D., Satellite InSAR survey of structurally-controlled land subsidence due to groundwater exploitation in the Aguascalientes Valley, Mexico, Remote Sens. Environ., 2021, vol. 254, id 112254. https://doi.org/10.1016/j.rse.2020.112254
Dagurov, P.N., Chimitdorzhiev, T.N., Dmitriev, A.V., and Dobrynin, S.I., Estimation of snow water equivalent from L-band radar interferometry: Simulation and experiment, Int. J. Remote Sens., 2020, vol. 41, no. 24, pp. 9328–9359.
D’Aranno, P.J.V., Di Benedetto, A., Fiani, M., Marsella, M., Moriero, I., and Palenzuela Baena, J.A., An application of Persistent Scatterer Interferometry (PSI) technique for infrastructure monitoring, Remote Sens., 2021, vol. 13, no. 6, p. 1052. https://doi.org/10.3390/rs13061052
DeVriesa, B., Huang, C., Armston, J., Huang, W., Jones, J.W., and Lang, M.W., Rapid and robust monitoring of flood events using Sentinel-1 and Landsat data on the Google Earth engine, Remote Sens. Environ., 2020, vol. 240, id 111664.
Ferretti, A., Prati, C., and Rocca, F., Permanent scatterers in SAR interferometry, IEEE Trans. Geosci. Remote Sens., 2001, vol. 39, no. 1, pp. 8–20. https://doi.org/10.1109/36.898661
Gabriel, A., Goldstein, R., and Zebker, H.A., Mapping small elevation changes over large areas: Differential radar interferometry, J. Geophys. Res., 1989, vol. 94, no. B7, pp. 9183–9191.
Ge, P., Gokonb, H., and Meguroc, K., A review on synthetic aperture radar-based building damage assessment in disasters, Remote Sen. Environ., 2020, vol. 240, id 111693. https://doi.org/10.1016/j.rse.2020.111693
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R., Google Earth engine: Planetary-scale geospatial analysis for everyone, Remote Sens. Environ., 2017, vol. 202, pp. 18–27. https://doi.org/10.1109/JSTARS.2020.3021052
Grandin, R., Vallée, M., and Lacassin, R., Rupture process of the Mw 5.8 Pawnee, Oklahoma, earthquake from Sentinel-1 InSAR and seismological data, Seismol. Res. Lett., 2017, vol. 88, no. 4, pp. 994–1004. https://doi.org/10.1785/0220160226
Huang, Z., Zhang, G., Shan, X., Gong, W., Zhang, Y., and Li, Y., Co-seismic deformation and fault slip model of the 2017 Mw 7.3 Darbandikhan, Iran–Iraq earthquake inferred from D-InSAR measurements, Remote Sens., 2019, vol. 11, no. 21, p. 2521. https://doi.org/10.3390/rs11212521
Ji, L., Zhang, W., Liu, C., Zhu, L., Xu, J., and Xu, X., Characterizing interseismic deformation of the Xianshuihe fault, eastern Tibetan Plateau, using Sentinel-1 SAR images, Adv. Space Res., 2020, vol. 66, no. 2, pp. 378–394. https://doi.org/10.1016/j.asr.2020.03.043
Laperdin, V.K., Measures for the disposal and storage of lignin-containing industrial and liquid household waste in the Lake Baikal region), Geoekol. Inzh. Geol., Gidrogeol., 2018, no. 3, pp. 77–85. https://doi.org/10.7868/S0869780318030092
Le Cozannet, G., Kervyn, M., Russo, S., Ifejika Speranza, C., Ferrier, P., Foumelis, M., Lopez, T., and Modaressi, H., Space-based earth observations for disaster risk management, Surv. Geophys., 2020, vol. 41, pp. 1209–1235. https://doi.org/10.1007/s10712-020-09586-5
Liu, X., Tong, X., Ding, K., Zhao, X., Zhu, L., and Zhang, X.D., Measurement of long-term periodic and dynamic deflection of the long-span railway bridge using microwave interferometry, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 2015, vol. 8, pp. 4531–4538.
McFeeters, S.K., The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features, Int. J. Remote Sens., 1996, vol. 17, no. 7, pp. 1425–1432.
Milillo, P., Giardina, G., DeJong, M.J., Perissin, D., and Milillo, G., Multi-temporal InSAR structural damage assessment: The London crossrail case study, Remote Sens., 2018, vol. 10, id 287.
Object of accumulated environmental damage (the Baikal PPM), 2021. https://network.bellona.org/content/uploads/sites/4/2021/04/2021_BCBK.pdf.
Pawluszek-Filipiak, K. and Borkowski, A., Integration of DInSAR and SBAS techniques to determine mining-related deformations using Sentinel-1 data: The case study of Rydułtowy mine in Poland, Remote Sens., 2020, vol. 12, no. 2, id 242. https://doi.org/10.3390/rs12020242
Rosen, P.A., Henseley, S., Joughin, I.R., Li, F.K., Madsen, S.N., Rodriguez, E., and Goldstein, R., Synthetic aperture radar interferometry, Proc. IEEE, 2000, vol. 88, no. 3, pp. 333–382.
Sousa, J.J. and Bastos, L., Multi-temporal SAR interferometry reveals acceleration of bridge sinking before collapse, Nat. Hazard. Earth Syst., 2013, vol. 13, pp. 659–667.
Tay, C.W.J., Yun, S.-H., Chin, S.T., Bhardwaj, A., Jung, J., and Hill, E.M., Rapid food and damage mapping using synthetic aperture radar in response to Typhoon Hagibis, Japan, Sci. Data, 2020, vol. 7, id 100. https://doi.org/10.1038/s41597-020-0443-5
ACKNOWLEDGMENTS
We thank the Japan Aerospace Exploration Agency JAXA for providing ALOS-1/2 PALSAR-1/2 radar data, project no. PI 3402. We are grateful to the German Aerospace Center for providing data from the TerraSAR-X/TanDEM-X, satellite radar-interferometric system project no. XTI_HYDR0485, “Study of Cryogenic Processes in Siberia by TanDEM-X Interferometry.”
Funding
This work was supported by the Ministry of Science and Higher Education of the Russian Federation, project no. 075-15-2020-776.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
The authors declare that they have no conflict of interest.
Additional information
Translated by O. Pismenov
Rights and permissions
About this article
Cite this article
Bondur, V.G., Chimitdorzhiev, T.N., Dmitriev, A.V. et al. Methods of Radar Interferometry and Optical Satellite Image Processing to Study Negative Effects on the Environment (a Case Study of the Baikalsk Pulp and Paper Mill). Izv. Atmos. Ocean. Phys. 57, 1527–1537 (2021). https://doi.org/10.1134/S0001433821120045
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S0001433821120045