Dynamics of state of former agricaltural lands taken out of agricatrure after the Chernobyl accident, according to remote sensing data

№1 (2024)

Perevolotskaya T.V., Perevolotsky A.N., Shubina O.A.

УДК 631.4:635.95
https://doi.org/10.47148/1609-364X-2024-1-68-77

AbstractAbout the AuthorsReferences
Results of assessment of condition (overgrowth of woody and shrubby vegetation), for example, of former agricultural land, taken out of agriculture, in western area of the European part of the Russian Federation (Bryansk region) using algorithms for automated detection of changes in multi-time multi-zone space images are presented. To perform the work, data from TM radiometers (Landsat 5) were selected from available data for study area, and two images of different times (2011 and 2018) were formed. Automated processing included following stages: preliminary processing of satellite images; determination of difference vegetation index (NDVI) based on index images assessment of changes in multi-time images by principal component method (РСА) based on formation of more informative combinations of source images obtained in different spectral zones and reduction of set of analyzed data; identification of changes by difference method based on difference in brightness of each pixel of first image and brightness of corresponding pixel of second image combined with first. Evaluation of use of algorithms for automated detection of changes in multi-time satellite images has shown that joint image processing makes it much better to assess the processes of changes that have occurred on former agricultural land, derived from agricultural turnover.

Tatiana V. Perevolotskaya
Candidate of Biological Sciences
Associate Professor, Senior Researcher
Russian Institute of Radiology and Agroecology (RIRAE)
1, build. 1, Kievskoe shosse, Obninsk, 249032, Russia
e-mail: forest_rad@mail.ru
ORCID: 0000-0001-8250-5536
SPIN-код: 4562-3671

Alexander N. Perevolotsky
Advanced Doctor of Biological Sciences
Leading Researcher
Russian Institute of Radiology and Agroecology (RIRAE)
1, build. 1, Kievskoe shosse, Obninsk, 249032, Russia
e-mail: Alex_Perevolotsky@mail.ru
ORCID: 0000-0002-6913-7609
SPIN-код: 1469-3199

Olga A. Shubina
Candidate of Biological Sciences
Deputy Director RIRAE for Scientific Work
Russian Institute of Radiology and Agroecology (RIRAE)
1, build. 1, Kievskoe shosse, Obninsk, 249032, Russia
e-mail: olgashu76@gmail.com
ORCID: 0000-0003-3055-9473
SPIN-код: 7036-8172

  1. Aivazyan S.A., Bukhshtaber V.M.,Enyukov I.S., Meshalkin L.D. Prikladnaya statistika. Klassifikatsiya i snizhenie razmernosti. [Applied statistics. Classification and dimensionality reduction]. Moscow: Finansy i statistika; 1989. 608 p.
  2.  Izraehl’ Yu.A., Bogdevich I.M. (eds.) Atlas sovremennykh i prognoznykh aspektov posledstvii avarii na Chernobyl’skoi AEHS na postradavshikh territoriyakh Rossii i Belarusi (ASPA Rossiya-Belarus’) [Atlas of recent and predictable aspects of consequences of Chernobyl accident on polluted territories of Russia and Belarus (ASPA Russia-Belarus)]. Moskva; Minsk: Fond Innosfera; NIA Priroda; 2009. 140 p.
  3. Bondur V.G. Up-to-date approach for bulky flows of hyperspectral aerospace data processing. Issledovanie Zemli iz kosmosa. 2014;(1):4–16. DOI: 10.7868/S0205961414010035.
  4. Vorob’ev G.T., Guchanov D.E., Markina Z.N., Novikov A.A., Kalatskii V.S., Karpechenko S.V. Radioaktivnoe zagryaznenie pochv Bryanskoi oblasti [Radioactive contamination of soils of the Bryansk region]. Bryansk: Grani; 1994. 177 p.
  5. Tsublova E.G., Lukashov S.V. (comp.) Gosudarstvennyi doklad o sostoyanii okruzhayushchei sredy Bryanskoi oblasti v 2020 godu [State report on the state of environment of the Bryansk region in 2020]. Bryansk: Department of Natural Resources and Ecology of Bryansk region; 2021. 250 p.
  6. Guk A.P., Evstratova L.G., Khlebnikova E.P., Altyntsev M.A., Arbuzov S.A., Gordienko A.S., Simonov D.P. Automated interpretation of space images. Detection of changes in the status of territories and objects on multispectral satellite images obtained at different dates. Geodeziya i kartografiya [Geodesy and cartography]. 2013;(8):39–47 (in Rus.).
  7. Guk A.P., Konechnyi G. Fotogrammetriya i distantsionnoe zondirovanie [Photogrammetry and remote sensing]. Novosibirsk: SGUGiT; 2018. 250 p.
  8. Guk A.P., Shlyakhova M.M. Analiz ehffektivnosti primeneniya metoda glavnykh komponent pri ispol’zovanii neparametricheskogo statisticheskogo podkhoda k deshifrirovaniyu snimkov [Analysis of the effectiveness of the principal component method when using a nonparametric statistical approach to image decoding]. In: Regional’nye problemy distantsionnogo zondirovaniya Zemli : materialy IV Mezhdunarodnoi nauchnoi konferentsii (Krasnoyarsk, 12-15 September 2017). Vaganov E.A. (ed.). Krasnoyarsk: SFU; 2017. pp. 89–94.
  9. Mozgovoi D.K., Kravets O.V. Ispol’zovanie mnogospektral’nykh snimkov dlya klassifikatsii posevov sel’khozkul’tur [The use of multispectral images for classification of crops]. Ecology and noospherology. 2009;20(1–2):54–58.
  10. Nichiporovich Z.A., Radevich E.A. Experience using the NDVI normalized difference vegetation index for monitoring Polesye agricultural land based on multispectral Ikonos satellite imaging data. Journal of Applied Spectroscopy. 2012;79(4):670–673. DOI: 10.1007/s10812-012-9656-5.
  11. Sanzharova N.I., Fesenko S.V. (eds.) Radioecological consequences of the Chernobyl accident: biological effects, migration, rehabilitation of contaminated areas. Moscow: RAN; 2018. 278 p.
  12. Eremeev V.V. (ed.) Sovremennye tekhnologii obrabotki dannykh distantsionnogo zondirovaniya Zemli [Modern technologies for processing Earth remote sensing data]. Moscow: Fizmatlit; 2015. 460 p.
  13. Terekhin E.A. Estimation of seasonal NDVI values for the detection and analysis of crop conditions. Issledovanie Zemli iz kosmosa. 2015;(1):23. DOI: 10.7868/S0205961415010108.
  14. Schowengerdt R.A. Remote sensing. Models and methods for image processing. 3rd edn. Amsterdam: Elsevier; 2007. 560 p.
  15. Sentinel Hub EO browser. Available at: https://apps.sentinel-hub.com/eo-browser (accessed 05.02.2024).

Key words: radioactive contamination, former agricultural lands, multi-time satellite images, remote sensing data

Section: Geoecology