Integration of Sentinel-2 data and the Google Earth Engine platform for spatiotemporal monitoring of peat extraction locations

Authors

  • V. L. Rasiun Senior Lecturer Lesya Ukrainka Volyn National University
  • O. V. Melnyk Ph.D. in Engineering, Associate Professor Lesya Ukrainka Volyn National University
  • V. F. Radzii Ph.D. in Geography, Associate Professor Lesya Ukrainka Volyn National University

DOI:

https://doi.org/10.36910/6775-2410-6208-2026-15(25)-14

Keywords:

remote sensing, industrial peatlands, NDVI, Sentinel-2 multispectral data, Google Earth Engine (GEE), vegetation dynamics

Abstract

This study presents a comprehensive spatiotemporal analysis of the ecological transformation and dynamics of the vegetation cover at the “Koz-Berezina” peat deposit (Volyn Oblast, Ukraine) under the influence of anthropogenic pressure. Given the intensive industrial exploitation of peatlands in the Ukrainian Polissya, which is inevitably accompanied by a radical change in the hydrological regime, degradation of natural habitats, the formation of a loose layer of peat crumbs, and an increased fire hazard, the need for continuous cross-scale monitoring of such areas has become extremely urgent. The aim of this study is to quantitatively and spatially assess the extent of ecosystem devastation resulting from open-pit peat extraction, as well as to identify processes of natural flora recovery (secondary succession) over a 9-year period (2017–2025).
Multispectral images with high spatial and temporal resolution from the Sentinel-2 satellite mission were used as the primary source of geospatial data. Data processing was performed in the Google Earth Engine (GEE) cloud environment and GIS QGIS. The normalized difference vegetation index (NDVI) served as the primary biophysical indicator of the state and volume of phytomass. For in-depth spatial modeling of ecosystem development vectors and visualization of area transitions between different NDVI classes from year to year, flow analysis using a Sankey diagram was applied.
The results of long-term monitoring indicate a heterogeneous response of the wetland ecosystem to anthropogenic intervention. A distinct spatial localization of the focal point of ecological devastation was recorded directly within the quarry zone (Dolyna tract), where NDVI values dropped critically (below 0.1–0.2) as a result of vegetation removal. An analysis of transition dynamics confirms that the highest level of degradation and spatial expansion of areas with exposed peat will occur in 2023–2024.
At the same time, the study revealed high ecological plasticity and strong regenerative potential of the deposit’s background ecosystem. It was established that the overall linear trend of NDVI values for the entire study period remains stable with a positive slope. As of 2025, the territorial expansion of peat extraction has ceased. Analysis of the Sankei diagram clearly visualizes macro-stabilization and an upward trend at the end of the period: significant areas of vegetation have massively shifted to higher NDVI classes (0.8–1.0). 
It has been established that the integration of open Sentinel-2 multispectral optical data, the capabilities of the GEE platform, and methods for visualizing transition dynamics is an objective, reliable, and highly effective approach for environmental monitoring of active peatlands, enabling the optimization of strategies for sustainable natural resource use and wetland management.

Downloads

Download data is not yet available.

References

1. Расюн, В., Волошин В., Рудик, О., та ін. Дослідження використання методів ДЗЗ для моніторингу та картографування торфовищ. Сучасні досягнення геодезичної науки та виробництва : збірник наукових праць. Львів: Видавництво Львівської політехніки, 2025. № 1(49). С. 201—211.

2. Lyalko V.I., Dugin S.S., Sybirtseva O.M., та ін. On the possibility of identifying peatland features using remote sensing data. Geological Journal. 2023. № 4. С. 61—78. DOI: 10.30836/igs.1025-6814.2023.4.288929.

3. Lischenko L., Shevchuk R., Filipovich V. The technique for satellite monitoring of peatlands in order to determinate their fire hazard and combustion risks. Ukrainian journal of remote sensing. 2022. Т. 9, № 1. С. 16—25. DOI: 10.36023/ujrs.2022.9.1.210.

4. Czapiewski S., Szumińska D. An Overview of Remote Sensing Data Applications in Peatland Research Based on Works from the Period 2010–2021. Land. 2021. Т. 11, № 1. С. 24. DOI: 10.3390/land11010024.

5. Melnyk O., Brunn A. Analysis of Spectral Index Interrelationships for Vegetation Condition Assessment on the Example of Wetlands in Volyn Polissya, Ukraine. Earth (Switzerland). Multidisciplinary Digital Publishing Institute (MDPI), 2025. Т. 6, № 2. DOI: 10.3390/earth6020028.

6. Melnyk O., Brunn A. Seasonal and Long-Term Water Regime Trends of Cheremsky Wetland: Analysis Based on Sentinel-2 Spectral Indices and Composite Indicator Development. Remote Sensing. Multidisciplinary Digital Publishing Institute (MDPI), 2025. Т. 17, № 14. DOI: 10.3390/rs17142363.

7. Радзій В.Ф., Коцун Л.О., Мельник О.В., Сухомлін К.Б. Польові дослідження флори, фауни та біорізноманіття, оселищ, міграція на території планованої діяльності «Видобування торфу на родовищі «Коза-Березина». Луцьк: Волинський національний університет імені Лесі Українки, 2021. 111 с.

8. European Space Agency. Sentinel Online - ESA [Електронний ресурс]. European Space Agency - Earth Online. 2020.

9. Reynolds N., Mota B., Nightingale J.M. Open-access satellite data for peatland condition and restoration monitoring in the UK: a review. Frontiers in Environmental Science. 2025. Т. Volume 13-2025. DOI: 10.3389/fenvs.2025.1685165.

10. Boiaryn M., Nekos A., Radzii V., та ін. Impact of peat extraction from the peatlands of upper Pripyat basin on the environment. Visnyk of V. N. Karazin Kharkiv National University. Series Geology. Geography. Ecology. 2025. № 62. С. 401—411. DOI: 10.26565/2410-7360-2025-62-30.

11. Gatti A., Naud C., Castellani C., Carriero F. Sentinel-2 Products Specification Document. Thales Alenia Space. 2018.

12. Gandhi G.M., Parthiban S., Thummalu N., Christy A. Ndvi: Vegetation Change Detection Using Remote Sensing and Gis – A Case Study of Vellore District. Procedia Computer Science. 2015. Т. 57. С. 1199—1210. DOI: https://doi.org/10.1016/j.procs.2015.07.415.

13. Valor E., Environment V.C.-R. sensing of, 1996 undefined. Mapping land surface emissivity from NDVI: Application to European, African, and South American areas. Elsevier. 1995. Т. 57. С. 167—184.

14. Zheng Y., Han J., Huang Y., та ін. Vegetation response to climate conditions based on NDVI simulations using stepwise cluster analysis for the Three-River Headwaters region of China. Ecological Indicators. 2018. Т. 92. С. 18—29. DOI: https://doi.org/10.1016/j.ecolind.2017.06.040.

Published

2026-05-29

How to Cite

Rasiun, V. L., Melnyk, O. V., & Radzii, V. F. (2026). Integration of Sentinel-2 data and the Google Earth Engine platform for spatiotemporal monitoring of peat extraction locations. Modern Technologies and Methods of Calculations in Construction, 25, 178-196. https://doi.org/10.36910/6775-2410-6208-2026-15(25)-14

Most read articles by the same author(s)