Abstract
Possibilities of using radar polarimetry methods for identifying landslide zones are analyzed. The transformation of the dominant mechanism of signal scattering by the reflecting surface was used as a key feature of landslide zones. The polarimetric data from the PALSAR-2 radar of the ALOS-2 satellite are processed using the Freeman–Durden and Cloude–Pottier decompositions at four test sites selected in the region of the landslide caused by the collapse of the bank of the Bureya River. It is found that the results of decompositions are consistent with each other; however, in some areas there are significant differences due to the specific features of the basic model assumptions. It is shown that, before the descent of the landslide masses, three main mechanisms of radar signal scattering existed in the analyzed region: single surface, volumetric, and double scattering. After the collapse, this area was dominated by single scattering characteristic of the reflective surface with large-scale irregularities free of vegetation, due to which the landslide descent zone can be confidently recognized. The significant potential of using radar polarimetry for remote diagnostics of the consequences of landslide phenomena has been demonstrated.
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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
Bondur, V.G., Zakharova, L.N., Zakharov, A.I., et al., Long-term monitoring of the landslide process on Bureya riverbank based on interferometric L-band radar data, Sovr. Probl. Dist. Zond. Zemli Kosm. 2019, vol. 16, no. 5, pp. 113–119. https://doi.org/10.21046/2070-7401-2019-16-5-113-119
Bondur, V.G., Chimitdorzhiev, T.N., Dmitriev, A.V., and Dagurov, P.N., Spatial anisotropy assessment of the forest vegetation heterogeneity at different azimuth angles of radar polarimetric sensing, Izv., Atmos. Oceanic Phys., 2019, vol. 55, no. 9, pp. 926–934.https://doi.org/10.1134/S0001433819090093
Bondur, V.G. and Starchenkov, S.A., Methods and programs for aerospace imagery processing and classification, Izv. Vyssh. Uchebn. Zaved., Geod. Aerofotos’emka, 2001, no. 3, pp. 118–143.
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. and Zverev, A.T., Mechanisms underlying the formation of lineament systems registered in space images during the monitoring of seismic danger areas, Issled. Zemli Kosmosa, 2007, no. 1, pp. 47–56.
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. 4, 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., 2008a, vol. 422, no. 7, pp. 1124–1128. https://doi.org/10.1134/S1028334X08070283
Bondur, V.G. and Chimitdorzhiev, T.N., Texture analysis of radar images of vegetation, Izv. Vyssh. Uchebn. Zaved., Geod. Aerofotos’emka, 2008a, no. 5, pp. 9–14.
Bondur, V.G. and Chimitdorzhiev, T.N., Remote sensing of vegetation by optical microwave methods, Izv. Vyssh. Uchebn. Zaved., Geod. Aerofotos’emka, 2008b, no. 6, pp. 64–73.
Bondur, V.G., Pulinets, S.A., and Uzunov, D., Ionospheric effect of large-scale atmospheric vortex by the example of hurricane Katrina, Issled. Zemli. Kosmosa, 2008b, no. 6, pp. 3–11.
Bondur, V.G., Krapivin, V.F., and Savinykh, V.P., Monitoring i prognozirovanie prirodnykh katastrof (Monitoring and Forecasting of Natural Disasters), Moscow: Nauchnyi mir, 2009.
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. 1, pp. 147–150. https://doi.org/10.1134/S1028334X10010320
Bondur, V.G., Aerospace methods and technologies for monitoring oil and gas areas and facilities, Izv., Atmos. Oceanic Phys., 2011, vol. 47, no. 9, pp. 1007–1018. https://doi.org/10.1134/S0001433811090039
Bondur, V.G., Krapivin, V.F., Potapov, I.I., and Soldatov, V.Ju., Natural disasters and the environment, Probl. Okr. Sredy Prir. Resur., 2012, no. 1, pp. 3–160.
Bondur, V.G., Garagash, I.A., and Gokhberg, M.B., Large scale interaction of seismically active tectonic provinces: the example of Southern California, Dokl., Earth Sci., 2016a, vol. 466, no. 2, pp. 183–186. https://doi.org/10.1134/S1028334X16020100
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, 2016b, vol. 52, no. 1, pp. 117–128. https://doi.org/10.1134/S1069351316010043
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, pp. 016006–1–016006–12. https://doi.org/10.1117/1.JRS.10.016006
Cloude, S.R. and Pottier, E., A review of target decomposition theorems in radar polarimetry, IEEE Trans. Geosci. Remote Sens., 1996, vol. 34, no. 2, pp. 498–518. https://doi.org/10.1109/36.485127
Cloude, S.R. and Pottier, E., An entropy based classification scheme for land applications of polarimetric SAR, IEEE Trans. Geosci. Remote Sens., 1997, vol. 35, no. 1, pp. 68–78. https://doi.org/10.1109/36.551935
Cloude, S.R., Polarisation: Applications in Remote Sensing, New York: Oxford University Press, 2010.
Czuchlewski, K.R., Weissel, J.K., and Kim, Y., Polarimetric synthetic aperture radar study of the Tsaoling landslide generated by the 1999 Chi-Chi earthquake, Taiwan, J. Geophys. Res., 2003, vol. 108, no. F1, p. 6006. https://doi.org/10.1029/2003JF000037
Dmitriev, A.V., Chimitdorzhiev, T.N., Gusev, M.A., et al., Basic products of Earth imaging by space radars with synthesized aperture, Issled. Zemli. Kosmosa, 2014, no. 5, pp. 83–91.
Dubina, B.A., Shamov, B.B., and Plotnikov, B.B., Catastrophic flood in Primorye in August 2018, Sovr. Probl. Dist. Zond. Zemli Kosmosa, 2018, vol. 15, no. 5, pp. 253–256.
Ferro-Famil, L., Pottier, E., and Jong-Sen, L., Unsupervised classification of multifrequency and fully polarimetric SAR images based on the H/A/Alpha-Wishart classifier, IEEE Trans. Geosci. Remote Sens., 2001, vol. 39, no. 11, pp. 2332–2342. https://doi.org/10.1109/36.964969
Freeman, A. and Durden, S.L., A three-component scattering model for polarimetric SAR data, IEEE Trans. Geosci. Remote Sens., 1998, vol. 36, no. 3, pp. 963–973. https://doi.org/10.1109/36.673687
Kramareva, L.S., Lupjan, E.A., Amel’chenko, Ju.A., et al., Observation of the hill collapse zone near the Bureya River on December 11, 2018, Sovr. Probl. Dist. Zond. Zemli Kosmosa, 2018, vol. 15, no. 7, pp. 266–271. http://omdoki.nextgis.com/resource/103/display
Lee, J.S., Grunes, M.R., and de Grandi, G., Polarimetric SAR speckle filtering and its implication for classification, IEEE Trans. Geosci. Remote Sens., 1999, vol. 37, no. 5, pp. 2363–2373. https://doi.org/10.1109/36.789635
Lee, J.-S. and Pottier, E., Polarimetric Radar Imaging: from Basics to Applications, New York: CRC Press, 2009.
Li, N., Wang, R., Deng, Y., Liu, Y., Li, B., Wang, C., and Balzc, T., Unsupervised polarimetric synthetic aperture radar classification of large-scale landslides caused by Wenchuan earthquake in hue-saturation-intensity color space, J. Appl. Remote Sens., 2014a, vol. 8, no. 1, pp. 083595-1–083595-8. https://doi.org/10.1117/1.JRS.8.083595
Li, N., Wang, R., Deng, Y., Liu, Y., Wang, C., Balz, T., and Li, B., Polarimetric response of landslides at X-band following the Wenchuan earthquake, IEEE Geosci. Remote Sens. Lett., 2014b, vol. 11, no. 10, pp. 1722–1726. https://doi.org/10.1109/LGRS.2014.2306820
Luo, S., Tong, L., Chen, Y., and Tan, L., Landslides identification based on polarimetric decomposition techniques using radarsat-2 polarimetric images, Int. J. Remote Sens., 2016, vol. 37, no. 12, pp. 2831–2843. https://doi.org/10.1080/01431161.2015.1041620
Mihajlov, V.O., Kiseleva, E.A., Smol’janinova, E.I., et al., Some problems of landslide processes monitoring using satellite radar images with different wavelengths on the example of two landslides in the Great Sochi, Fiz. Zemli, 2014, no. 4, pp. 120–130.
Plank, S., Twele, A., and Martinis, S., Landslide mapping in vegetated areas using change detection based on optical and polarimetric SAR data, Remote Sens., 2016, vol. 8, no. 4, p. 307. https://earth.esa.int/web/polsarprohttps://doi.org/10.3390/rs8040307PolSARpro
Shibayama, T., Yamaguchi, Y., and Yamada, H., Polarimetric scattering properties of landslides in forested areas and the dependence on the local incidence angle, Remote Sens., 2015, vol. 7, no. 11, pp. 15424–15442. https://doi.org/10.3390/rs71115424
Shimada, M., Watanabe, M., Kawano, N., Ohki, M., Motooka, T., and Wada, Y., Detecting mountainous landslides by sar polarimetry: a comparative study using Pi-SAR-L2 and X-band SARs, Trans. JSASS Aerospace Tech. Jpn., 2014, vol. 12, no. 29, pp. 9–15. https://doi.org/10.2322/tastj.12.Pn_9
Shirzaei, M., Burgmann, R., and Fielding, E.J., Applicability of Sentinel-1 Terrain Observation by Progressive Scans multitemporal interferometry for monitoring slow ground motions in the San Francisco Bay Area, Geophys. Res. Lett., 2017, no. 44, pp. 2733–2742. https://doi.org/10.1002/2017GL072663
Verba, V.S., Neronskii, L.B., Osipov, I.G., and Turuk, V.E., Radiolokatsionnye sistemy zemleobzora kosmicheskogo bazirovaniya (Space-Based Radar Systems for Earth Observation), Moscow: Radiotekhnika, 2010.
Wang, C., Mao, X., and Wang, Q., Landslide displacement monitoring by a fully polarimetric SAR offset tracking method, Remote Sens., 2016, vol. 8, no. 8, p. 624. https://doi.org/10.3390/rs8080624
Watanabe, M., Yonezawa, C., Iisaka, J., and Sato, M., ALOS/PALSAR full polarimetric observations of the Iwate–Miyagi Nairiku earthquake of 2008, Int. J. Remote Sens., 2012, vol. 33, no. 4, pp. 1234–1245. https://doi.org/10.1080/01431161.2011.554453
Watanabe, M., Thapa, R.B., and Shimada, M., Pi-SAR-L2 observation of the landslide caused by typhoon Wipha on Izu Oshima Island, Remote Sens., 2016, vol. 8, no. 4, p. 282. https://doi.org/10.3390/rs8040282
Yamaguchi, Y., et al., Four-component scattering model for polarimetric SAR image decomposition, IEEE Trans. Geosci. Remote Sens., 2005, vol. 43, no. 8, pp. 1699–1706. https://doi.org/10.1109/TGRS.2005.852084
Yonezawa, C., Watanabe, M., and Saito, G., Polarimetric decomposition analysis of alos palsar observation data before and after a landslide event, Remote Sens., 2012, vol. 4, no. 8, pp. 2314–2328. https://doi.org/10.3390/rs4082314
Zakharov, A.I., Yakovlev, O.I., and Smirnov, V.M., Sputnikovyi monitoring Zemli: Radiolokatsionnoe zondirovanie poverhnosti (Satellite Monitoring of the Earth: Radar Imaging of the Surface, Moscow: Librokom, 2012.
Zakharov, A.I., Zakharova, L.N., and Krasnogorskij, M.G., Landslide activity monitoring by radar interferometry methods using trihedral corner reflectors, Issled. Zemli Kosmosa, 2018, no. 3, pp. 80–92.
Zakharova, L.N., Zakharov, A.I., and Mitnik, L.M., First results of the assessment of the landslide consequences on the Bureya River bank using Sentinel-1 radar data, Sovr. Probl. Dist. Zond. Zemli Kosm., 2019, vol. 16, no. 2, pp. 69–74.
Zakharova, L.N. and Zakharov, A.I., Interferometric observation of landslide area dynamics on the Bureya River by means of Sentinel-1 radar data in 2017–2018, Sovr. Probl. Dist. Zond. Zemli Kosm., 2019, vol. 16, no. 2, pp. 273–277.
ACKNOWLEDGMENTS
We are grateful to the Japan Aerospace Exploration Agency (JAXA) for the ALOS‑2 PALSAR‑2 radar data provided within the ALOS‑2 RA‑6 projects (PI 3402 and PI 3092).
Funding
This work was performed as part of the framework of state assignments of the Institute of Physical Materials Science, Siberian Branch, Russian Academy of Sciences; the Kotelnikov Institute of Radioengineering and Electronics, Russian Academy of Sciences; and AEROCOSMOS Research Institute for Aerospace Monitoring.
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Bondur, V.G., Chimitdorzhiev, T.N., Dmitriev, A.V. et al. Application of Radar Polarimetry to Monitor Changes in Backscattering Mechanisms in Landslide Zones Using the Example of the Collapse of the Bureya River Bank. Izv. Atmos. Ocean. Phys. 56, 916–926 (2020). https://doi.org/10.1134/S0001433820090054
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DOI: https://doi.org/10.1134/S0001433820090054