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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 3, pp. 203-216

Geospatial analysis of technogenically disturbed ecosystems in Central Siberia using satellite data in the IR range

K.V. Krasnoshchekov 1 , A.V. Dergunov 1 , T.V. Pnomareva 2, 3 
1 Krasnoyarsk Science Center SB RAS, Krasnoyarsk, Russia
2 Sukachev Institute of Forest SB RAS, Krasnoyarsk, Russia
3 Siberian Federal University, Krasnoyarsk, Russia
Accepted: 02.06.2022
DOI: 10.21046/2070-7401-2022-19-3-203-216
The work is devoted to the study of changes in the state of vegetation and soil cover in technogenically disturbed areas of various types within the Krasnoyarsk Territory for the period from 2000 to 2020. For the study, 4 river basins were selected: the Yenashimo River, the Panimba River, the Norilskaya River and the Barga River, on which various technogenic objects are located (quarries, tailings, dumps). In order to detect damaged areas in the form of anomalies on heat maps of the surface, we used data in the thermal IR range of the MODIS/Terra instrument (product MOD11A1). A method has been developed for identifying disturbed areas on heat maps of the studied territories, based on a comparison of the alleged disturbed areas with background, undisturbed areas. This method is applied both for accurate analysis of selected technogenic objects and for areas within the boundaries of selected river basins. Analysis of the data showed that in all four studied territories, the surface temperature exceeds the background by an average of 1.5°. The dynamics of changes in the state of the underlying surface in the studied territories over a 20-year period is demonstrated. In technogenically disturbed areas in the Panimba River basin, there are no significant changes in the state of the underlying surface during the study period. Within the basins of the Yenashimo and Norilsk rivers, an increase in the area of the disturbed underlying surface is detected, and within the boundaries of the Barga River basin, on the contrary, there is a positive trend in the restoration of vegetation and soil cover, including due to the reclamation of disturbed surfaces. Using remote sensing data both for identifying a local technogenic disturbance and for determining the proportion of disturbed areas will make it possible to obtain more objective estimates of the anthropogenic load on ecosystems for specific industrial areas.
Keywords: technogenic objects, river basin, heat map of the surface, cryolithozone, Siberia, surface temperature anomalies, vegetation disturbance
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References:

  1. Androkhanov V. A., Berlyakova O. G., Condition of forest crops and soil cover at reclaimed dump of coal mine, Siberian Forest J., 2016, No. 2, pp. 22–31 (in Russian), DOI: 10.15372/SJFS20160202.
  2. Bartalev S. A., Stytsenko F. V., Egorov V. A., Loupian E. A., Satellite-based assessment of Russian forest fire mortality, Lesovedenie, 2015, No. 2, pp. 83–94 (in Russian).
  3. Vorobev O. N., Kurbanov E. A., Remote monitoring of vegetation regeneration dynamics on burnt areas of Mari Zavolzhje forests, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2017, Vol. 14, No. 2, pp. 84–97 (in Russian), DOI: 10.21046/2070-7401-2017-14-2-84-97.
  4. Vorobiev O. N., Kurbanov E. A., Polevshchikova Yu. A., Lezhnin S. A., Assessment of dynamics and disturbance of forest cover in the Middle Povolzhje by Landsat images, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2016, Vol. 13, No. 4, pp. 124–134 (in Russian), DOI: 10.21046/2070-7401-2016-13-4-124-134.
  5. Vokhmina D. A., Chernetskaya A. Yu., Subsurface use and mineral resource potential Krasnoyarsk Territory, Innovatsionnye tendentsii razvitiya rossiiskoi nauki, 2020, pp. 381–385 (in Russian).
  6. Zenkov I. V., Nefedov B. N., Zhukova V. V., Kiryushina E. V., Vokin V. N., The Results of the Ecology Assessment of Disturbed Lands by the Abansky Coal Mine in the Krasnoyarsk Territory, Ugol’, 2019, No. 9, pp. 116–119 (in Russian).
  7. Kalabin G. V., Moiseenko T. I., Gorny V. I., Kritsuk S. G., Soromotin A. V., Satellite monitoring of natural environment at Olimpiada gold open-cut mine, J. Mining Science, 2013, Vol. 49, No. 1, pp. 160–166.
  8. Krasnoshchekov K. V., Dergunov A. V., Ponomarev E. I., Evaluation of underlying surface temperature maps on logging sites using Landsat data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 2, pp. 87–97 (in Russian), DOI: 10.21046/2070-7401-2019-16-2-87-97.
  9. Kurbanov E. A., Nureeva T. V., Vorobyev O. N., Gubaev A. V., Lezhnin S. A., Miftakhov T. F., Nezamayev S. A., Polevshchikova Yu. A., Remote monitoring of disturbances in forest cover, reforestation and afforestation of Mari Zavolzhje, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2011, No. 3, pp. 17–24 (in Russian).
  10. Nekrasova N. A., Geologiya i genezis mestorozhdeniya Panimba (Eniseiskii kryazh): Diss. kand. geol.-mineral. nauk (Geology and genesis of the Panimba deposit (Yenisei ridge), Cand. geol. and mineral. sci. thesis), 2019, 171 p. (in Russian).
  11. Ponomarev E. I., Ponomareva T. V., The effect of postfire temperature anomalies on seasonal soil thawing in the permafrost zone of Central Siberia evaluated using remote data, Contemporary Problems of Ecology, 2018, Vol. 11, No. 4, pp. 420–427, DOI: 10.1134/S1995425518040066.
  12. Ponomareva T. V., Kovaleva N. M., Ponomarev E. I., Malkevich V. V., Biodiversity assessment in the area of Olimpiada mining and processing plant, Polyus Krasnoyarsk, Gornyi zhurnal, 2020, No. 10, pp. 18–53 (in Russian), DOI 10.17580/gzh.2020.10.02.
  13. Tarasov A. V., Traditional and modern methods of satellite images processing for operational mapping of forest cover disturbances, Vestnik Sibirskogo gosudarstvennogo universiteta geosistem i tekhnologii, 2020, Vol. 25, No. 3, pp. 201–213 (in Russian), DOI: 10.33764/2411-1759-2020-25-3-201-213.
  14. Tarasov A. V., Shikhov A. N., Shabalina T. V., Detection of forest disturbances in Sentinel-2 images with convolutional neural networks, Sovremennyye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2021, Vol. 18, No. 3, pp. 51–64 (in Russian), DOI: 10.21046/2070-7401-2021-18-3-51-64.
  15. Terekhin E. A., Estimation of forest ecosystems disturbance in the southwest of Central Russian Upland using remote sensing data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2017, Vol. 14, No. 4, pp. 112–124 (in Russian), DOI: 10.21046/2070-7401-2017-14-4-112-124.
  16. Terekhin E. A. (2019a), Disturbance of coniferous forests in the forest-steppe zone of Russia at the beginning of the XXI century, Lesnye ekosistemy v usloviyakh izmeneniya klimata: biologicheskaya produktivnost’ i distantsionnyi monitoring, 2019, No. 5, pp. 33–41 (in Russian), DOI: 10.25686/2367.2019.5.58814.
  17. Terekhin E. A. (2019b), Detection of disturbed forest ecosystems in the forest-steppe zone using reflectance values, Komp’yuternaya optika, 2019, Vol. 43, No. 3, pp. 412–418 (in Russian), DOI: 10.18287/0134-2452-2019-43-3-412-418.
  18. Brown J., Ferrians O. J., Heginbottom J. A., Melnikov E. S., Circum-Arctic Map of Permafrost and Ground Ice Conditions, Reston, VA, US Geological Survey, 1997, 45 p., DOI: 10.13140/RG.2.1.2994.9040.
  19. Coppin P. R., Bauer M. E., Digital change detection in forest ecosystems with remote sensing imagery, Remote Sensing Reviews, 1996, Vol. 13, pp. 207–234, DOI: 10.1080/02757259609532305.
  20. Häme T., Spectral interpretation of changes in forest using satellite scanner images, Acta Forestalia Fennica, 1991, Vol. 222, Art. ID 7668, 111 p.
  21. Lehner B., Grill G., Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems, Hydrological Processes, 2013, Vol. 27, No. 15, pp. 2171–2186, DOI: 10.1002/hyp.9740.
  22. Ponomareva T. V., Litvintsev K. Y., Finnikov K. A., Yakimov N. D., Sentyabov A. V., Ponomarev E. I., Soil Temperature in Disturbed Ecosys-tems of Central Siberia: Remote Sensing Data and Numerical Simulation, Forests, 2021, Vol. 12, No. 8, Art. No. 994, 22 p., DOI: 10.3390/f12080994.
  23. Wang W., Liang S., Meyers T., Validating MODIS land surface temperature products using long-term nighttime ground measurements, Remote Sensing of Environment, 2008, Vol. 112, No. 3, pp. 623–635, DOI: 10.1016/j.rse.2007.05.024.
  24. Yakimov N., Ponomarev E., Dynamics of Post-Fire Effects in Larch Forests of Central Siberia Based on Satellite Data, E3S Web Conf., 2020, Vol. 149, p. 03008, DOI: 10.1051/e3sconf/202014903008.
  25. Yang Y., Erskine P. D., Lechner A. M., Mulligan D., Zhang S., Wang Z., Detecting the dynamics of vegetation disturbance and recovery in surface mining area via Landsat imagery and LandTrendr algorithm, J. Cleaner Production, 2018, Vol. 178, pp. 353–362, DOI: 10.1016/j.jclepro.2018.01.050.