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. 1, pp. 170-178

Assessment of changes in vegetation of the Norilsk industrial region with remote sensing data, based on the trend analysis of spectral indices

O.M. Zheleznyi 1 , O.V. Tutubalina 1 , V.I. Kravtsova 1 
1 Lomonosov Moscow State University, Moscow, Russia
Accepted: 20.01.2022
DOI: 10.21046/2070-7401-2022-19-1-170-178
The vegetation of the Norilsk industrial region, degraded over large areas under the influence of airborne industrial pollution, which varied at different stages of the metallurgical plant’s activity, is influenced by climate warming. To assess changes in vegetation, imagery from Landsat-5, -7, -8 satellites is used for the entire period of their operation since 1984, their analysis carried out by means of the cloud platform Google Earth Engine. The imagery was masked from clouds and snow, and cross-calibration of the imaging systems of different satellites was performed. The assessment of the state of vegetation was based on the maximum values of NDVI in each pixel for the summer season. Statistical tests were carried out on this series of data, including simple linear regression and analysis of Mann-Kendall trends; so, the analysis of changes is based on NDVI trends. To better account for the changes in tree and shrub cover, a similar analysis of NDMI was carried out. Analysis of the spatial structure of the trend showed that the maximum stable growth of both indices is observed southeast of Norilsk, in the Rybnaya River valley, the area most affected by pollution in the past. Validation via modern very high-resolution images confirms the appearance of grass and shrubs in the areas of the strong positive trend. A similar study based on MODIS/Terra-Aqua data for 2000–2020 confirmed the existence of significant NDVI trend in the Rybnaya valley. Analysis of changes in vegetation based on very high resolution images showed that the greatest increase in NDVI is observed for vegetation in ravines and gullies.
Keywords: satellite images, vegetation index, NDVI, vegetation recovery, Norilsk, Arctic
Full text


  1. Isachenko A. G., Landshaftnaya karta SSSR (Landscape map of the USSR), Sovremennye problemy geografii: Nauchye soobshcheniya sovetskikh geografov po programme 20-go Mezhdunarodnogo geograficheskogo kongressa, London, 1964, Moscow: Nauka, 1964, 416 p., pp. 395–399 (in Russian).
  2. Karpenko L. V., Ecological assessment of the state of bog ecosystems of background territories and in the zone of technogenic impacts, Vestnik Krasnoyarskogo argarnogo universiteta, 2006, Vol. 14, pp. 145–150 (in Russian).
  3. Korets M. A., Ryzhkova V. A., Danilova I. V., GIS-Based Approaches to the Assessment of the State of Terrestrial Ecosystems in the Norilsk Industrial Region, Contemporary Problems of Ecology, 2014, Vol. 7, No. 6, pp. 643–653.
  4. Telyatnikov M. Y., Prystyazhnyuk S. A., Anthropogenous Influence of Norilsk Industrial Area on Plant Vegetation Cover of the Tundra and Forest Tundra, Contemporary Problems of Ecology, 2014, Vol. 7, No. 6. pp. 654–668.
  5. Boyte S., Wylie B., Rigge M., Dahal D., Fusing MODIS with Landsat-8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands, USA, GIScience and Remote Sensing, 2017, Vol. 55, Issue 3, pp. 376–399, DOI 10.1080/15481603.2017.1382065.
  6. Fassnacht F. E., Schiller C., Kattenborn T., Zhao X., Qu J., A Landsat-based vegetation trend product of the Tibetan Plateau for the time-period 1990–2018, Scientific Data, 2019, Vol. 6(78), pp. 1–11, DOI: 10.1038/s41597-019-0075-9.
  7. Gorelick N., Hancher M., Dixon M., Ilyushchenko S., Thau D., Moore R., Google Earth Engine: Planetary-scale geospatial analysis for everyone, Remote Sensing of Environment, 2017, Vol. 202, pp. 18–27, DOI: 10.1016/j.rse.2017.06.031.
  8. Kirdyanov A. V., Krusic P. J., Shishov V. V., Vaganov E. A., Fertikov A. I., Myglan V. S., Barinov V. V., Browse J., Esper J., Ilyin V. A., Knorre A. A., Korets M. A., Kukarskikh V. V., Mashukov D. A., Onuchin A. A., Piermattei A., Pimenov A. V., Prokushkin A. S., Ryzhkova V. A., Shishikin A. S., Smith K. T., Taynik A. V., Wild M., Zorita E., Büntgen U., Ecological and conceptual consequences of Arctic pollution, Ecology Letters, 2020, Vol. 23(19), pp. 1827–1837, DOI: 10.1111/ele.13611.
  9. Nyland K. E., Shiklomanov N. I., Streletskiy D. A., Climatic- and anthropogenic-induced land cover change around Norilsk, Russia, Polar Geography, 2017, Vol. 40(4), pp. 257–272, DOI: 10.1080/1088937X.2017.1370503.
  10. Roy D. P., Kovalskyy V., Zhang H. K., Vermote E. F., Yan L., Kumar S. S., Egorov A. V., Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity, Remote Sensing of Environment, 2016, Vol. 185, pp. 57–70, DOI: 10.1016/j.rse.2015.12.024.
  11. Schmidt G., Jenkerson C. B., Masek J., Vermote E., Gao F., Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) Algorithm Description, U. S. Geological Survey Open-File Report 2013–1057, Reston, VA, 2013, 27 p.,
  12. Serreze M. C., Barrett A. P., Stroeve J. C., Kindig D. M., Holland M. M., The emergence of surface-based Arctic amplification, Cryosphere, 2009, Vol. 3, pp. 11–19, DOI: 10.5194/tc-3-11-2009.
  13. Toutoubalina O., Rees G., Remote sensing of industrial impact on arctic vegetation around Noril’sk, northern Siberia: preliminary results, Intern. J. Remote Sensing, 1999, Vol. 20, pp. 2979–2990, DOI: 10.1080/014311699211561.
  14. Tutubalina O., Rees G., Vegetation degradation in a permafrost region as seen from space: Noril’sk (1961–1999), Cold Regions Science and Technology, 2001, Vol. 32, pp. 191–203, DOI: 10.1016/S0165-232X(01)00049-0.