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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, 2025, V. 22, No. 5, pp. 167-177

The potential of using vegetation indices to assess post-pyrogenic succession of vegetation cover

L.V. Brodt 1 , N.V. Prikhod'ko 1 , A.V. Soromotin 1 
1 Tyumen State University, Tyumen, Russia
Accepted: 01.08.2025
DOI: 10.21046/2070-7401-2025-22-5-167-177
The article discusses the possibilities of using the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR) to assess post-pyrogenic succession of vegetation cover in the Arctic zone of the Yamalo-Nenets Autonomous Okrug. The research methodology included geobotanical field studies and analysis of multispectral satellite images of Landsat-5 Thematic Mapper (TM), Landsat-7 Enhanced Thematic Mapper Plus (ETM+), Landsat-8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) for the period 1990–2023. As the result of analysis of NDVI medial values of burnt areas and background for each year, we identified three periods in the post-pyrogenic succession of vegetation cover: rehabilitation (the first 6 years), progression (6–18 years) and sustainable development (after 18 years). As a result of field studies, it was found that in the post-pyrogenic period, the structure of the vegetation cover changes, which reliably shown by the NDVI. The NBR, in turn, does not reflect the restoration of vegetation, and therefore, it can be used to identify burn boundaries long after the fire. The methodology for assessing post-pyrogenic dynamics of vegetation cover using satellite data can be used to monitor Arctic ecosystems and predict their recovery after fires, which is confirmed by the results of field research.
Keywords: NDVI, NBR, vegetation, Landsat, vegetation indices, forest-tundra, Western Siberia, fire, succession
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References:

  1. Bartalev S. A., Stytsenko F. V., Khvostikov S. A., Loupian E. A., Methodology of post-fire tree mortality monitoring and prediction using remote sensing data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2017, V. 14, No. 6, pp. 176–193 (in Russian), DOI: 10.21046/2070-7401-2017-14-6-176-193.
  2. Ershov D. V., Sochilova E. N., Koroleva N. V., Shchepaschenko D. G., Improving the method of mapping organic carbon in the forest litter in Central Federal District, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, V. 21, No. 2, pp. 212–222 (in Russian), DOI: 10.21046/2070-7401-2024-21-2-212-222.
  3. Ivanova K. V., Dynamics of NDVI for different classes of territorial units of typical tundra vegetation, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, V. 16, No. 5, pp. 194–202 (in Russian), DOI: 10.21046/2070-7401-2019-16-5-194-202.
  4. Ivanov M. A., Gafurov A. M., Analysis of land use changes in the Middle Volga Region based on Landsat data to assess the potential of returning abandoned cropland into use, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2025, V. 22, No. 2, pp. 186–201 (in Russian), DOI: 10.21046/2070-7401-2025-22-2-186-201.
  5. Il’ina I. S., Lapshina E. I., Lavrenko N. N., Rastitel’nost’ Zapadno-Sibirskoi ravniny (Vegetation cover of the West Siberian plain), Novosibirsk: Nauka, 1985, 251 p. (in Russian).
  6. Kirsanov A. D., Komarov A. A., Using the NDVI index to assess the development of perennial grasses under conditions of spatial and temporal heterogeneity, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, V. 21, No. 2, pp. 143–155 (in Russian), DOI: 10.21046/2070-7401-2024-21-2-143-155.
  7. Kornienko S. G., Elsakov V. V., Assessment of informativeness of temperature-vegetation index as an indicator of moisture content of tundra ground vegetation cover, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, V. 21, No. 3, pp. 155–170 (in Russian), DOI: 10.21046/2070-7401-2024-21-3-155-170.
  8. Koroleva E. S., Razvitie mnogoletnemerzlykh poligonal’nykh torfyanikov pod vozdeistviem izmenenii prirodnykh uslovii Pur-Tazovskogo mezhdurech’ya Zapadnoi Sibiri: dis. … kand. geologo-mineral. nauk (Development of permafrost polygonal peatlands under the influence of changes in the natural conditions of the Pur-Taz interfluve of Western Siberia: Cand. geolog. mineralog. sci.), Tyumen, 2022, 136 p. (in Russian).
  9. Lavrenko E. M., Korchagina A. A., Polevaya geobotanika (Field geobotany), V. 3, Moscow, Leningrad, 1964, 530 p. (in Russian).
  10. Moskovchenko D. V., Moskovchenko M. D., Assessment of modern landscape dynamics of the Zapolyarnoe gas field using satellite data, Tyumen state university herald. Natural resource use and ecology, 2018, V. 4, No. 2, pp. 6–16 (in Russian).
  11. Moskovchenko D. V., Aref’ev S. P., Moskovchenko M. D., Yurtaev A. A., Spatiotemporal analysis of wildfires in the forest tundra of Western Siberia, Contemporary Problems of Ecology, 2020, V. 13, No. 2, pp. 193–203, DOI: 10.1134/S1995425520020092.
  12. Sochava V. B., The success of thematic mapping and vegetation maps, Geobotanicheskoe kartografirovanie, 1967, pp. 3-9 (in Russian).
  13. Sochava V. B., Rastitel’nyi pokrov na tematicheskikh kartakh (Vegetation cover on thematic maps), Novosibirsk: Nauka, Sibirskoe otdelenie, 1979, 190 p. (in Russian).
  14. Stepanov A. S., Fomina E. A., Verkhoturov A. L., Illarionova L. V., Crops monitoring in the south of the Far East in 2021–2023 using Sentinel-2 data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2025, V. 22, No. 2, pp. 120–133 (in Russian), DOI: 10.21046/2070-7401-2025-22-2-120-133.
  15. Tarasova L. V., Kurbanov E. A., Vorobiev O. N. et al., Monitoring forest cover in riparian zones along the rivers of Mari El Republic using satellite data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, V. 21, No. 2, pp. 177–195 (in Russian), DOI: 10.21046/2070-7401-2024-21-2-177-195.
  16. Tokareva O. S., Alshaibi A. D. A., Pas’ko O. A., Assessment of restoration dynamics of burnt forest area vegetation using Landsat satellite data, Bull. Tomsk polytechnic university. Geo assets engineering, 2021, V. 332, No. 7, pp. 191–199 (in Russian), DOI: 10.18799/24131830/2021/07/3283.
  17. Fiziko-geograficheskoe raionirovanie Tyumenskoi oblasti (Physical and geographical zoning of the Tyumen region), Gvozdetskii N. A. (ed.), Moscow: Izd. Moskovskogo universiteta, 1973, 246 p. (in Russian).
  18. Khomutov A. V., Babkin E. M., Tikhonravova Ya.V. et al., Complex studies of the cryolithozone of the northeastern part of the Pur-Taz Interfluve, Scientific Bulletin of the Yamal-Nenets Autonomous District, 2019, V. 1, No. 102, pp. 53–64 (in Russian), DOI: 10.26110/ARCTIC.2019.102.1.008.
  19. Shabanov N. V., Bartalev S. A., Eroshenko F. V., Plotnikov D. E., Development of capabilities for remote sensing estimate of Leaf Area Index from MODIS data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, V. 15, No. 4, pp. 166–178 (in Russian), DOI: 10.21046/2070-7401-2018-15-4-166-178.
  20. Shary P. A., Sharaya L. S., Regular spatial changes in the vegetation index of deciduous forests in the Volga basin, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2025, V. 22, No. 2, pp. 134–144 (in Russian), DOI: 10.21046/2070-7401-2025-22-2-134-144.
  21. Shpanev A. M., Rusakov D. V., Application of spectral indices to assess the influence of crop weeds and nitrogen nutrition on the activity of the photosynthetic apparatus of plants and the yield of winter triticale, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, V. 21, No. 2, pp. 235–247 (in Russian), DOI: 10.21046/2070-7401-2024-21-2-235-247.
  22. Yakimov N. D., Ponomarev N. D., Zabrodin A. N., Ponomareva T. V., The features of post-fire dynamics of spectral characteristics of larch stands in the permafrost zone of Siberia, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2025, V. 22, No. 1, pp. 106–115 (in Russian), DOI: 10.21046/2070-7401-2025-22-1-106-115.
  23. Cuevas-González M., Gerand F., Balzler H., Riaño D., Analysing forest recovery after wildfire disturbance in boreal Siberia using remotely sensed vegetation indices, Global Change Biology, 2009, V. 15, No. 3, pp. 561–577, DOI: 10.1111/j.1365-2486.2008.01784.x.
  24. de Groot W. J., Wein R. W., Effects of fire severity and season of burn on Betula glandulosa growth dynamics, Intern. J. Wildland Fire, 2004, V. 13, No. 3, pp. 287–295, DOI: 10.1071/WF03048.
  25. Forgani A., Reddy S., Thankappan M., Cechet B., Validation of MODIS and AVHRR fire detections in Australia, Intern. J. Geoinformatics, 2021, V. 17, No. 3, pp. 117–131, DOI: 10.52939/ijg.v17i3.1907.
  26. Gaglioti B. V., Berner L. T., Jones B. M. et al., Tussocks enduring or shrubs greening: Alternate responses to changing fire regimes in the Noatak River valley, Alaska, J. Geophysical Research: Biogeosciences, 2021, V. 126, No. 4, Article e2020JG006009, DOI: 10.1029/2020JG006009.
  27. Gough L., Neighbor effects on germination, survival, and growth in two arctic tundra plant communities, Ecography, 2006, V. 29, No. 1, pp. 44–56, DOI: 10.1111/j.2005.0906-7590.04096.x.
  28. Heim R. J., Bucharova A., Brodt L. et al., Post‐fire vegetation succession in the Siberian subarctic tundra over 45 years, Science of the Total Environment, 2021, V. 760, Article 143425, DOI: 10.1016/j.scitotenv.2020.143425.
  29. Higuera P. E., Brubaker L. B., Anderson P. M. et al., Frequent fires in ancient shrub tundra: Implications of paleorecords for Arctic environmental change, PLoS ONE, 2008, V. 3, No. 3, Article e0001744, 7 p., DOI: 10.1371/journal.pone.0001744.
  30. Key C. H., Benson N. C., Measuring and remote sensing of burn severity: the CBI and NBR. Poster abstract, In: Proc. Joint Fire Science Conf. and Workshop, L. F. Neuenschwander, K. C. Ryan (eds.), V. II, Boise, ID: University of Idaho and Intern. Association of Wildland Fire, 1999, p. 284.
  31. Lopez-Garcia M., Caselles V., Mapping burns and natural reforestation using Thematic Mapper data, Geocarto Intern., 1991, V. 6, No. 1, pp. 31–37.
  32. Racine C., Jandt R., Meyers C., Dennis J., Tundra fire and vegetation change along a hillslope on the Seward Peninsula, Alaska, U. S.A., Arctic, Antarctic, and Alpine Research, 2004, V. 36, pp. 1–10, DOI: 10.1657/1523-0430(2004)036[0001:TFAVCA]2.0.CO;2.
  33. Rietze N., Heim R. J., Troeva E. et al., Pre‐fire vegetation conditions and topography shape burn mosaics of Siberian tundra fire scars, J. Geophysical Research: Biogeosciences, 2025, V. 130, No. 3, Article e2024JG008608, DOI: 10.1029/2024JG008608.
  34. Rouse J. W., Jr., Haas R. H., Shell J. A., Deering D. W., Monitoring vegetation systems in the Great Plains with ERTS, In: Proc. 3rd Earth Resources Technology Satellite-1 Symp., V. 1, Washington, DC, 1974, pp. 309–317.
  35. Shur Y. L., Jorgenson M. T., Patterns of permafrost formation and degradation in relation to climate and ecosystems, Permafrost and Periglacial Processes, 2007, V. 18, pp. 7–19, DOI: 10.1002/ppp.582.
  36. Sizov O., Ezhova E., Tsymbarovich P. et al., Fire and vegetation dynamics in northwest Siberia during the last 60 years based on high-resolution remote sensing, Biogeosciences, 2021, V. 18, pp. 207–228, DOI: 10.5194/bg-18-207-2021.
  37. Telesca L., Lasaponara R., Fire‐induced variability in satellite SPOT‐VGT NDVI vegetational data, Intern. J. Remote Sensing, 2006, V. 27, No. 14, pp. 3087–3095, DOI: 10.1080/01431160600564644.
  38. Wookey P. A., Aerts R., Bargett R. D. et al., Ecosystem feedbacks and cascade processes: Understanding their role in the responses of Arctic and alpine ecosystems to environmental change, Global Change Biology, 2009, V. 15, pp. 1153–1172, DOI: 10.1111/j.1365-2486.2008.01801.x.
  39. Zhao G., Xu E., Yi X. et al., Comparison of forest restorations with different burning severities using various restoration methods at Tuqiang forestry bureau of greater Hinggan mountains, Remote Sensing, 2023, V. 15, No. 10, Article 2683, DOI: 10.3390/rs15102683.