Mapping the modern land cover of the Tunka hollow using Sentinel-2 satellite imagery

Geoinformatics

UDC:

528.9:528.8

DOI:

10.22389/0016-7126-2025-1021-7-44-54

1 Rasputina Е.А.

2 Kapitulin O.V.

Year:

2025

№:

1021

Pages:

44-54

Sochava Institute of Geography SB RAS

1,

Irkutsk State University

2,

Abstract:

Maps of land cover/use are essential for studying morphological and functional changes occurring in Earth’s ecosystems and the environment, including climatic change and carbon circulation. Based on field research data conducted in 2021–2022, satellite imagery from Sentinel-2 with a spatial resolution of 10 meters and the cloud-based computing platform Google Earth Engine were used to perform large-scale mapping and make the Tunka hollow (Irkutsk oblast and Buryat Republic, RF) land cover analysis. The Random Forest method and 198 training polygons, derived from field research and remote sensing data were used for supervised classification of the images. As a result, 15 classes of land cover were identified. The classification accuracy was 95 %, as estimated by Kappa; the error matrix was calculated and analyzed. The results showed that forests predominated in the study area, but they were significantly disturbed. Steppe zones would be used for grazing. Arable lands mainly turned into pastures, hayfields and are gradually covered with young growth of pine and birch. A comparative analysis of different maps of land cover showed that they generally corresponded to each other but had differences in the source images and classification methods

Keywords:

Arshan village, Google Earth Engine, land cover, mapping, Sentinel-2, supervised classification

The study was carried out at the expense of the state assignment № ААА-А-А21-121012190056-4

References:

1. Atutova Zh. V. Rekonstruktsiya landshaftnoi struktury Tunkinskoi kotloviny. Geografiya i prirodnye resursy, 2011, no. 1, pp. 107–111.

2. Atutova Zh. V. Sovremennye landshafty Tunkinskoi kotloviny. Geografiya i prirodnye resursy, 2018, no. 1, pp. 103–114.

3. Voropai N. N., Istomina E. A., Vasilenko O. V. Issledovanie temperaturnogo polya zemnoi poverkhnosti Tunkinskoi kotloviny s ispol'zovaniem kosmicheskikh snimkov Landsat. Optika atmosfery i okeana, 2011, Vol. 24, no. 1, pp. 67–73.

4. Istomina E.A. (2012) GIS-mapping of the Tunkinskaya hollow landscapes based on factor-dynamic classification method. Geodezia i Kartografia, 73(4), pp. 32–38.

5. Makarov S. A., Cherkashina A. A., Atutova Zh.V, Bardash A. V., Voropai N. N., Kichigina N. V., Mutin B. F., Osipova O. P., Ukhova N. N. Katastroficheskie selevye potoki, proizoshedshie v poselke Arshan Tunkinskogo raiona Respubliki Buryatiya 28 iyunya 2014 g.. Otvetstvennyi redactor V. M. Plyusnin. Irkutsk: Izdatel’stvo Instituta geografii imeni V. B. Sochavy Sibirskogo otdeleniya RAN, 2014, 111 p.

6. Brown C. F., Brumby S. P., Guzder-Williams B., et al. (2022) Dynamic World, Near real-time global 10 m land use land cover mapping. Scientific Data, Volume 9, no. 251, DOI: 10.1038/s41597-022-01307-4.

7. Chughtai A. H., Abbasi H., Karas I. R. (2021) A review on change detection method and accuracy assessment for land use land cover. Remote Sensing Applications: Society and Environment, Volume 22, no. 100482, DOI: 10.1016/j.rsase.2021.100482.

8. Danko L. V., Bilichenko I. N. (2010) Landscape-ecological investigations in Baikal Siberia. Land-scape ecology – methods, applications and interdisciplinary approach. Bratislava: Slovak Academy of Sciences. pp. 375–385.

9. Hansen M. C., Potapov P. V., Moore R., Hancher M., Turubanova S. A., Tyukavina A., Thau D., Stehman S. V. (2013) High-resolution global maps of 21st-century forest cover change. Science, Volume 6160, no. 342 , pp. 850–853. DOI: 10.1126/science.1244693.

10. Karra A., Kontgis C., Statman-Weil Z., Mazzariello J. C., Mathis M., Brumby S. P. (2021) Global land use / land cover with Sentinel 2 and deep learning, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium. pp. 4704-4707. DOI: 10.1109/IGARSS47720.2021.9553499.

11. Kuklina V., Sizov O., Rasputina E., Bilichenko I., Krasnoshtanova N., Bogdanov V., Petrov A. (2022) Fires on Ice: Emerging Permafrost Peatlands Fire Regimes in Russia’s Subarctic Taiga. Land, no. 11 (3), DOI: 10.3390/land11030322.

12. Liang J., Chen Ch., Song Y., Sun W., Yang G. (2023) Long-term mapping of land use and cover changes using Landsat images on the Google Earth Engine Cloud Platform in bay area – A case study of Hangzhou Bay, China. Sustainable Horizons, Volume 7, no. 100061, DOI: 10.1016/j.horiz.2023.100061.

13. Phiri D., Simwanda M., Salekin S., Nyirenda V. R., Murayama Y., Ranagalage M. (2020) Sentinel-2 Data for Land Cover/Use Mapping: A Review. Remote Sensing, no. 12 (14) 2291, DOI: 10.3390/rs12142291.

14. Potapov P., Hansen M. C., Pickens A., et al. (2022) The global 2000–2020 land cover and land use change dataset derived from the Landsat archive: first results. Frontiers in Remote Sensing, Volume 3, no. 856903, DOI: 10.3389/frsen.2022.856903.

15. Prishchepov A. V., Myachina K. V., Kamp J., Smelansky I., Dubrovskaya S., Ryakhov R., Grudinin D., Yakovlev I., Urazaliyev R. (2021) Multiple trajectories of grassland fragmentation, degradation, and recovery in Russia’s steppes. Land Degradation and Development, no. 32, pp. 3220–3235.

Citation:

Rasputina Е.А.,

Kapitulin O.V.,

(2025) Mapping the modern land cover of the Tunka hollow using Sentinel-2 satellite imagery. Geodesy and cartography = Geodeziya i Kartografiya, 86(7), pp. 44-54. (In Russian). DOI: 10.22389/0016-7126-2025-1021-7-44-54