ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2023, Vol. 20, No. 2, pp. 184-201

Characteristics of anthropogenic transformations of the ground cover in the area of Yamburg gas field based on Landsat satellite data

S.G. Kornienko 1 
1 Oil and Gas Research Institute RAS, Moscow, Russia
Accepted: 28.03.2023
DOI: 10.21046/2070-7401-2023-20-2-184-201
The study results of anthropogenic transformations of the ground vegetation cover in the areas of construction and operation of the Yamburgskoye oil and gas condensate field facilities on the Tazovsky Peninsula are presented. The study was conducted using 10 summer Landsat 5, -7, -8 satellite images from 1988 to 2019 on the basis of parameters characterizing land surface temperature (LST), albedo (Alb), chlorophyll content (NDVI), and moisture (NDWI) of the ground cover. The description of multiyear trends and local changes in LST, Alb, NDVI, and NDWI was performed using the technique of relative radiometric normalization of images, which makes it possible to increase the sensitivity of multi-temporal data analysis by reducing the influence of factors not related to anthropogenic impact. In the area of longer development (since 1984), dominant growth trends of average NDVI, Alb, and NDWI values were revealed, indicating an increase in the volume of green phytomass in the process of revegetation after its disturbance during construction and maintenance of technical facilities. The absence of significant trends in changes in the average LST values in the area as a whole is explained by the parity of local processes of surface temperature decrease and increase caused by different responses of the landscapes to anthropogenic impact. The absence of significant trends in NDVI and NDWI in the area of later development indicates relative stability of the vegetation cover, which may be an evidence of more rational and environmentally friendly approaches to the construction of facilities and field development. Fragments of detailed maps describing the change of parameters over 31 years confirm these conclusions. The trends of increasing green phytomass volumes revealed against the background of the climatic trend are associated with anthropogenic impact and may be a consequence of local microclimate development, which, together with global warming, may lead to intensification of permafrost degradation processes and growth of biogenic gas emission.
Keywords: albedo, anthropogenic impact, remote sensing, cryogenic landscapes, ground vegetation, temperature, transformations, trends, tundra, Yamburgskoye field, NDVI, NDWI
Full text


  1. Elsakov V. V., Spectral differences in vegetation cover characteristics of tundra communities by Landsat sensors, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2021, Vol. 18, No. 4, pp. 92–101 (in Russian), DOI: 10.21046/2070-7401-2021-18-4-92-101.
  2. Kornienko S. G., Characteristics of anthropogenic transformations of landscapes in the area of Bovanenkovo gas field based on Landsat satellite data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 2, pp. 106–129 (in Russian), DOI: 10.21046/2070-7401-2022-19-2-106-129.
  3. Lavrinenko I. A., Map of technogenic disturbance of Nenets Autonomous District, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 2, pp. 128–136 (in Russian), DOI: 10.21046/2070-7401-2018-15-2-128-136.
  4. Moskovchenko D. V., Arefyev S. P., Glazunov V. A., Tigeev A. A., Changes in vegetation and geocryological conditions of the Tazovsky peninsula (eastern part) for the period of 1988–2016, Kriosfera Zemli, 2017, Vol. 21, No. 6, pp. 3–13 (in Russian), DOI: 10.21782/KZ1560-7496-2017-6(3-13).
  5. Pavlunin V. B., Bykova A. V., Lobastova S. A., Monitoring of technogenic ravine formation at hydrocarbon production objects in the permafrost conditions, Inzhenernye izyskaniya, 2015, No. 3, pp. 60–68 (in Russian).
  6. Tishkov A. A., Belonovskaya E. A., Vaisfeld M. A., Glazov P. M., Krenke A. N., Tertitsky G. M., “The greening” of the tundra as a driver of the modern dynamics of Arctic biota, Arktika: ekologiya i ekonomika, 2018, No. 2(30), pp. 31–44 (in Russian), DOI: 10.25283/2223-4594-2018-2-31-44.
  7. Ardelean F., Onaca A., Chetan M.-A., Dornik A., Georgievski G., Hagemann S., Timofte F., Berzescu O., Assessment of spatio-temporal landscape changes from VHR images in three different permafrost areas in the Western Russian Arctic, Remote Sensing, 2020, Vol. 12, No. 23, Art. No. 3999, DOI: 10.3390/rs12233999.
  8. Canty M. J., Nielsen A. A., Automatic radiometric normalization of multitemporal satellite imagery with the iteratively Re-weighted MAD transformation, Remote Sensing of Environment, 2008, Vol. 112, No. 3, pp. 1025–1036,
  9. Gao B., NDWI — A normalized difference water index for remote sensing of vegetation liquid water from space, Remote Sensing of Environment, 1996, Vol. 58, pp. 257–266, DOI: 10.1016/S0034-4257(96)00067-3.
  10. Jacob F., Olioso A., Gu X. F., Su Z., Seguin B., Mapping surface fluxes using airborne visible, near infrared, thermal infrared remote sensing data and a spatialized surface energy balance model, Agronomie, 2002, Vol. 22, pp. 669–680, DOI: 10.1051/agro:2002053.
  11. Liang S., Narrowband to broadband conversions of land surface albedo I — Algorithms, Remote Sensing of Environment, 2000, Vol. 76, pp. 213–238, DOI: 10.1016/S0034-4257(00)00205-4.
  12. Mann H. B., Nonparametric tests against trend, Econometrica, 1945, Vol. 13, pp. 245–259.
  13. Nelson P. R., Maguire A. J., Pierrat Z., Orcutt E. L., Yang D., Serbin S. et al., Remote sensing of tundra ecosystems using high spectral resolution reflectance: Opportunities and challenges, J. Geophysical Research: Biogeosciences, 2022, Vol. 127, Art. No. e2021JG006697,
  14. Nill L., Grünberg I., Ullmann T., Gessner M., Boike J., Hostert P., Arctic shrub expansion revealed by Landsat derived multitemporal vegetation cover fractions in the Western Canadian Arctic, Remote Sensing of Environment, 2022, Vol. 281, Art. No. 113228,
  15. O’Donnell J. A., Romanovsky V. E., Harden J. W., McGuire A. D., The effect of moisture content on the thermal conductivity of moss and organic soil horizons from black spruce ecosystems in interior Alaska, Soil Science, 2009, Vol. 174, No. 12, pp. 646–651, DOI: 10.1097/SS.0b013e3181c4a7f8.
  16. Rahman M. M., Hay G. J., Couloigner I., Hemachandran B., Bailin J., An Assessment of Polynomial Regression Techniques for the Relative Radiometric Normalization (RRN) of High-Resolution Multi-Temporal Airborne Thermal Infrared (TIR) Imagery, Remote Sensing, 2014, Vol. 6, pp. 11810–11828, DOI: 10.3390/rs61211810.
  17. Roy D. P., Kovalskyy V., Zhang H. K., Vermote E. F., Yan L., Kumar S. S., Egorov A., 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,
  18. Schieldge J. P., Kahle A. B., Alley R. E., Gillespie A. R., Use of thermal inertia properties for material identification, SPIE Image Processing for Missile Guidance, 1980, Vol. 238, pp. 350–357.
  19. Tucker C. J., Red and photographic infrared linear combinations for monitoring vegetation, Remote Sensing of Environment, 1979, Vol. 8, pp. 127–150, DOI: 10.1016/0034-4257(79)90013-0.
  20. Weng Q., Lu D., Schubring J., Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies, Remote Sensing of Environment, 2004, Vol. 89, pp. 467–483, DOI: 10.1016/j.rse.2003.11.005.
  21. Xu H., Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery, Intern. J. Remote Sensing, 2006, Vol. 27, No. 14, pp. 3025–3033, DOI: 10.1080/01431160600589179.
  22. Yan L., Yang J., Zhang Y., Zhao A., Li X., Radiometric Normalization for Cross-Sensor Optical Gaofen Images with Change Detection and Chi-Square Test, Remote Sensing, 2021, Vol. 13, Art. No. 3125,
  23. Yu Q., Epstein H. E., Engstrom R., Shiklomanov N., Strelestskiy D., Land cover and land use changes in the oil and gas regions of Northwestern Siberia under changing climatic conditions, Environmental Research Letters, 2015, Vol. 10, No. 12, Art. No. 124020.