Vestnik of Orenburg State Pedagogical University. Electronic Scientific Journal. 2021. № 3(39). P. 35—48

 

BIOLOGICAL SCIENCES

UDC 574.3

Rakhmatullina Irina Rimilevna, Candidate of Biological Sciences, Associate Professor
Bashkir State Pedagogical University named after M. Akmulla
Rakhmatullin Zagir Zabirovich, Candidate of Agricultural Sciences, Associate Professor
Bashkir State Agrarian University
Tagirova Olesya Vasilyevna, Candidate of Biological Sciences, Associate Professor
Bashkir State Pedagogical University named after M. Akmulla
Khamidullina Gulnara Gizarovna, Candidate of Biological Sciences, Associate Professor
Bashkir State Pedagogical University named after M. Akmulla
Kulagin Aleksey Yurievich, Doctor of Biological Sciences, Professor
Ufa Institute of Biology of Ufa Federal Research Centre of the Russian Academy of Sciences

 

USING VEGETATION INDICES TO ASSESS THE CHARACTERISTICS OF PINE PLANTATIONS IN UFA AND ITS SUBURBS

Abstract

On the territory of the Ufa forestry 16 test plots were laid in the plantations of Scots pine, which are more than 50 years old. The test plots are divided into 3 groups: a control zone, a zone with a predominance of petrochemical pollution, and a zone with high traffic and recreational load. Based on the Sentinel-2 image, rasters of vegetation indices were constructed: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil-Adjusted Vegetation Index (SAVI), Normalized Difference Water Index (NDWI), and their characteristics were given. For each trial plot, the average values of these indices were obtained and analyzed. The interrelations of the NDVI, EVI, SAVI indices with the state and age of the plantings have been established, which makes it possible to distinguish stands in which the chlorophyll content decreases. The combined use of these indices makes it possible to distinguish more gradations in the state of plantations and to characterize the degree of their heterogeneity. There is no clear dependence of NDWI on the state of pine plantations, since additional studies are needed on the supply of plants with moisture.

Key words

Scots pine, Sentinel-2 satellite image, NDVI, SAVI, EVI, NDWI.

DOI: https://doi.org/10.32516/2303-9922.2021.39.3

The full text of the article PDF (Russian)

 

References

1. Atlas Respubliki Bashkortostan [Atlas of the Republic of Bashkortostan]. Omsk, Omskaya kartograf. fabrika Publ., 2005. (In Russian)
2. Belova E. I., Ershov D. V. Opyt otsenki estestvennogo lesovosstanovleniya na sploshnykh vyrubkakh po vremennym ryadam Landsat [Assessing reforestation on clear cuts based on Landsat time series]. Lesovedenie — Russian Journal of Forest Science, 2015, no. 5, pp. 339—345. (In Russian)
3. Bratkov V. V., Kravchenko I. V., Tuaev G. A., Ataev Z. V., Abdulzhalimov A. A. Primenenie vegetatsionnykh indeksov dlya kartografirovaniya landshaftov Bol’shogo Kavkaza [Application of vegetation indices for mapping the landscapes of the Greater Caucasus]. Izvestiya Dagestanskogo pedagogicheskogo universiteta. Estestvennye i tochnye nauki, 2016, vol. 10, no. 4, pp. 97—111. (In Russian)
4. Vorob’ev O. N., Kurbanov E. A. Monitoring sostoyaniya rastitel’nogo pokrova na territorii Respubliki Marii El s ispol’zovaniem ENVISAT MERIS [Monitoring the state of vegetation on the territory of the Mari El Republic using ENVISAT MERIS]. Lesnoi vestnik — Forestry Bulletin, 2013, no. 7 (99), pp. 42—45. (In Russian)
5. Gopp N. V., Kulikova E. A., Pestunov I. A., Sinyavskii Yu. N., Smirnov V. V. Raspoznavanie formatsii lesnoi rastitel’nosti s blizkimi spektral’no-yarkostnymi kharakteristikami po dannym s’’emki so sputnika Landsat 7 ETM+ [Recognition of forest vegetation formations with similar spectral-brightness characteristics based on imagery data from the Landsat 7 ETM+ satellite]. Vychislitel’nye tekhnologii — Computational Technologies, 2007, vol. 12, no. 2, pp. 194—201. (In Russian)
6. Gopp N. V., Smirnov V. V. Ispol’zovanie vegetatsionnogo indeksa (NDVI) dlya otsenki zapasov nadzemnoi fitomassy tundrovykh soobshchestv rastenii [Use of the vegetation index (NDVI) for estimation the above-ground biomass in Tundra plant communities]. Interekspo Geo-Sibir’, 2009, vol. 4, no. 1, pp. 187—191. (In Russian)
7. Gusev A. P. Distantsionnye indikatory degradatsii lesnykh geosistem yugo-vostoka Belarusi [Remote indicators of degradation of forest geosystems in the South-East of Belarus]. Vestsі BDPU, Ser. 3. 2020, no. 1, pp. 46—50. (In Russian)
8. Ezhegodnik sostoyaniya zagryazneniya atmosfery v gorodakh na territorii Rossii za 2019 g. [Yearbook of the state of air pollution in cities on the territory of Russia for 2019]. St. Petersburg, Rosgidromet Publ., 2020. (In Russian)
9. Zhigunova S. N., Mikhailenko O. I., Fedorov N. I. Ispol’zovanie dannykh distantsionnogo zondirovaniya Zemli dlya analiza vliyaniya gorodskoi sredy na sezonnoe razvitie drevesnoi rastitel’nosti [Using Earth Remote Sensing Data to Analyze the Impact of the Urban Environment on the Seasonal Development of Woody Vegetation]. Ekologiya i geografiya rastenii i rastitel’nykh soobshchestv: materialy IV Mezhdunar. nauch. konf. [Ecology and Geography of Plants and Plant Communities. Proceedings of the IV Internat. sci. conf.]. Yekaterinburg, Gumanitarnyi un-t Publ., 2018, pp. 286—290. (In Russian)
10. Zaitsev G. A., Kulagin A. Yu. Sosna obyknovennaya i neftekhimicheskoe zagryaznenie: dendroekologicheskaya kharakteristika, adaptivnyi potentsial i ispol’zovanie [Scots pine and petrochemical pollution: dendroecological characteristics, adaptive potential and use]. Moscow, Nauka Publ., 2006. 124 p. (In Russian)
11. Lesokhozyaistvennyi reglament Ufimskogo lesnichestva Respubliki Bashkortostan [Forestry regulations of the Ufa forestry of the Republic of Bashkortostan]. Ufa, In-t strategicheskikh issledovanii Respubliki Bashkortostan Publ., 2018. 198 p. (In Russian)
12. Myachina K. V. Analiz kosmicheskikh izobrazhenii s raschetom NDVI dlya izucheniya dinamiki landshaftnogo pokrova territorii neftyanogo mestorozhdeniya v Orenburgskoi oblasti [Analysis of satellite images with calculation of NDVI for studying the dynamics of landscape cover of the oil fields territory in the Orenburg region]. Izvestiya Orenburgskogo gosudarstvennogo agrarnogo universiteta, 2013, no. 4 (42), pp. 206—209. (In Russian)
13. Opletaev A. S., Zhigulin E. V., Kosov V. A. Ispol’zovanie vegetatsionnogo indeksa NDVI dlya otsenki sostoyaniya lesnykh nasazhdenii na narushennykh zemlyakh [Using the NDVI vegetation index to assess the state of forest plantations on disturbed land]. Lesa Rossii i khozyaistvo v nikh, 2019, no. 3 (70), pp. 15—23. (In Russian)
14. Petrishchev V. P., Dubrovskaya S. A., Ryakhov R. V. Sravnitel’nyi analiz sostoyaniya rastitel’nosti v g. Orenburge po rezul’tatam obrabotki mul’tispektral’nykh kosmicheskikh snimkov [A comparative analysis of the vegetation in the Orenburg city on the results of the processing of multispectral space images]. Problemy regional’noi ekologii, 2014, no. 4, pp. 213—217. (In Russian)
15. Rakhmatullin Z. Z., Rakhmatullina I. R., Gabdelkhakov A. K., Martynova M. V., Sultanova R. R. Dinamika NDVI rastitel’nogo pokrova lesoparka im. Lesovodov Bashkirii [Dynamics of NDVI vegetation cover in the forest park named after Foresters of Bashkiria]. Lesnye ekosistemy v usloviyakh izmeneniya klimata: biologicheskaya produktivnost’ i distantsionnyi monitoring: sbornik nauch. statei [Forest ecosystems in conditions of climate change: biological productivity and remote monitoring. Collect. of sci. articles]. Ioshkar-Ola, Povolzhskii gos. tekhnol. un-t Publ., 2019, pp. 104—113. DOI: 10.25686/6157.2019.5.58821. (In Russian)
16. Rakhmatullina I. R., Rakhmatullin Z. Z., Iskhakov F. F., Serova O. V. Dinamika vegetatsionnogo indeksa NDVI nasazhdenii sosny obyknovennoi (Pinus sylvestris L.) v usloviyakh zagryazneniya Ufimskogo promyshlennogo tsentra [Dynamics of the NDVI vegetation index of pine forest plantations (Pinus sylvestris L.) under pollution in industrial center of Ufa]. Vestnik Permskogo natsional’nogo issledovatel’skogo politekhnicheskogo universiteta. Prikladnaya ekologiya. Urbanistika, 2019, no. 2 (34), pp. 116—117. DOI: 10.15593/2409-5125/2019.02.09. (In Russian)
17. Rysin L. P., Savel’ev L. I. Sosnovye lesa Rossii [Pine forests of Russia]. Moscow, KMK Publ., 2008. 289 p. (In Russian)
18. Strel’nikov I. I., Glukhov A. Z., Nikolaeva A. V., Mudretsova K. V. Podgotovka tsifrovykh kart dlya obespecheniya ekologicheskikh issledovanii v Donbasse [The digital maps preparation for support of ecological research in Donbass]. Promyshlennaya botanika, 2018, is. 18, no. 3, pp. 42—50. (In Russian)
19. Chashchin A. N., Kondratova M. A. Ispol’zovanie dannykh distantsionnogo zondirovaniya dlya otsenki tempov samozarastaniya ugol’nykh otvalov Kizelovskogo basseina [Using remote sensing data to assess the self-overgrowth rates of coal dumps in the Kizel basin]. Geograficheskii vestnik — Geographical Bulletin, 2019, no. 2 (49), pp. 135—147. DOI: 10.17072/2079-7877-2019-2-135-147. (In Russian)
20. Sharyi P. A., Sharaya L. S. Izmenenie NDVI lesnykh ekosistem Severnogo Kavkaza kak funktsiya rel’efa i klimata [Change in NDVI of forest ecosystems in Northern Caucasus as a function of topography and climate]. Lesovedenie — Russian Journal of Forest Science, 2014, no. 5, pp. 83—90. (In Russian)
21. Conrad O., Bechtel B., Bock M., Dietrich H., Fischer E., Gerlitz L., Wehberg J., Wichmann V., Böhner J. System for Automated Geoscientific Analyses (SAGA) v. 2.1.4. Geoscientific Model Development, 2015, vol. 8. DOI: 10.5194/gmd-8-1991-2015. Available at: http://www.geosci-model-dev.net/8/1991/2015/gmd-8-1991-2015.html.
22. Copernicus. Europe’s eyes on Earth. Available at: https://www.copernicus.eu/en.
23. Copernicus Open Access Hub. Available at: https://scihub.copernicus.eu/
24. Gao B. NDWI — A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing Environment, 1996, vol. 58, no. 3, pp. 257—266. DOI: 10.1016/s0034-4257(96)00067-3.
25. Huete A. R., Jackson R. D., Post D. F. Spectral response of a plant canopy with different soil backgrounds. Remote Sensing of Environment, 1985, vol. 17, no. 1, pp. 37—53. DOI: 10.1016/0034-4257(85)90111-7.
26. Huete A. R. Soil-Adjusted Vegetation Index (SAVI). Remote Sensing of Environment, 1988, vol. 25, no. 3, pp. 295—309. DOI: 10.1016/0034-4257(88)90106-X.
27. Hui Qing Liu, Huete A. A feedback based modification of the NDVI to minimize canopy background and atmospheric noise. IEEE Transactions on Geoscience and Remote Sensing, 1995, vol. 33, no. 2, pp. 457—465. DOI: 10.1109/TGRS.1995.8746027.
28. Main R., Cho M. A., Mathieu R., O’Kennedy M. M., Ramoelo A., Koch S. An investigation into robust spectral indices for leaf chlorophyll estimation. ISPRS Journal of Photogrammetry and Remote Sensing, 2011, vol. 66, no. 6, pp. 751—761. DOI: 10.1016/j.isprsjprs.2011.08.001.
29. Merzlyak M. N., Gitelson A. A., Chivkunova O. B., Solovchenko A. E., Pogosyan S. I. Application of reflectance spectroscopy for analysis of higher plant pigments. Russian Journal of Plant Physiology, 2003, vol. 50, no. 5, pp. 704—710.
30. Rouse J. W., Haas R. H., Schell J. A., Deering D. W. Monitoring vegetation systems in the Great Plains with ERTS. 3rd ERTS Symposium, 1973. NASA SP-351, pp. 309—317.
31. Szabo S., Gácsi Z., Balazs B. Specific features of NDVI, NDWI and MNDWI as reflected in land cover categories. Landscape & Environment, 2016, vol. 10, no. 3—4, pp. 194—202.
32. Xue J., Su B. Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications. Journal of Sensors, 2017, vol. 2017, pp. 1—17. DOI: 10.1155/2017/1353691.

 

Bibliography link to this article:

Rakhmatullina I. R., Rakhmatullin Z. Z., Tagirova O. V., Khamidullina G. G., Kulagin A. Yu. Using vegetation indices to assess the characteristics of pine plantations in Ufa and its suburbs. Vestnik of Orenburg State Pedagogical University. Electronic Scientific Journal, 2021, no. 3 (39), pp. 35—48. DOI: https://doi.org/10.32516/2303-9922.2021.39.3.