Environmental impact on forest ecosystems using remote sensing data: case study of Novhorod-Siverske Polissia (Ukraine)

Remote Sensing for Environmental Monitoring

Authors

First and Last Name Academic degree E-mail Affiliation
Tamara Dudar Sc.D. dtv.nau [at] gmail.com State University “Kyiv Aviation Institute”
Kyiv, Ukraine
Sergey Stankevich Sc.D. st [at] casre.kiev.ua State Institution "Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine"
Kyiv, Ukraine
Olga Titarenko Ph.D. olgatitarenko [at] casre.kiev.ua State Institution "Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine"
Kyiv, Ukraine
Denys Malyi No denis.malyi.k [at] gmail.com State University “Kyiv Aviation Institute”
Kyiv, Ukraine

I and my co-authors (if any) authorize the use of the Paper in accordance with the Creative Commons CC BY license

First published on this website: 02.07.2026 - 18:44
Abstract 

The aim of the study is to present the research results on long-term anthropogenic and military operation impacts on forest ecosystems of Novgorod-Siverske Polissia to improve management of border areas and understand further natural resource management. To achieve this goal, natural and anthropogenic forest covers were considered and analyzed, as well as existing objects of the nature reserve fund located on the territory of Novgorod-Siverske Polissia. Analysis of time series of remote data for mapping long-term trends and periodic components of the studied area showed that one of the most informative for detecting long-term changes are the average values for the entire analysis period and the average increments of leaf area index for a certain observation period. Changes in the leaf area index are considered on the example of the studied border area. Using the original multispectral satellite images, maps of the spatial distribution of the rate of leaf area index changes, integrated over 6 years due to both indirect and direct anthropogenic impact, complicated by hostilities, were constructed.

References 

 

Chen, B.Z.; Chen, J.M.; Ju, W.M. (2007). Remote sensing-based ecosystem-atmosphere simulation scheme (EASS) - Model formulation and test with multiple-year data. Ecol. Modell. 209,277-300.

 

Cleugh, H.A.; Leuning, R.; Mu, Q.; Running, S.W. (2007). Regional evaporation estimates from flux tower and MODIS satellite data. Remote Sens. Environ. 106, 285-304.

 

Dietz, J.; Hölscher, D.; Leusc hnerb, C.; Hendrayanto, (2006). Rainfall partitioning in relation to forest structure in differently managed montane forest stands in Central Sulawesi, Indonesia. For. Ecol. Manage. 237, 170-178.

 

Duchemin, B. & Hadria, R. & Erraki, S. & Boulet, G. & Maisongrande, P. & Chehbouni, A. & Escadafal, R. & Ezzahar, J. & Hoedjes, J.C.B. & Kharrou, M.H. & Khabba, S. & Mougenot, B. & Olioso, A. & Rodrig. (2006). "Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely-sensed vegetation indices," Agricultural Water Management, Elsevier, vol. 79(1), 1-27, January.

 

Dudar, T. V., Stankevich, S. А., & Titarenko, O. V. (2026). Remote eco-monitoring of disturbed forest ecosystems using satellite data time-series: case study of the borderline Novgorod-Siverske Polissia (Ukraine). Journal of Geology, Geography and Geoecology, 35(1), 83-94. https://doi.org/10.15421/112608

 

Jongschaap, R.E.E. (2006). Run-time calibration of simulation models by integrating remote sensing estimates of leaf area index and canopy nitrogen. Eur. J. Agron. 24, 316-324.

 

Johnson, E. C., Musso, A., Cullingham, C., & Lewis, M. A. (2024). Biological barriers to forest pest invasions: A novel host tree slows mountain pine beetle range expansion.
https://doi.org/10.48550/arXiv.2412.08778

 

Jung, M., Koirala, S., Weber, U., Ichii, K., Gans, F., Camps-Valls, G., Papale, D., Schwalm, C., Tramontana, G., & Reichstein, M. (2019). The FLUXCOM ensemble of global land-atmosphere energy fluxes. Scientific Data, 6, Article 74. https://doi.org/10.1038/s41597-019-0076-8

 

Leuning, R.; Cleugh, H.A.; Zegelin, S.J.; Hughes, D. (2005). Carbon and water fluxes over a temperate Eucalyptus forest and a tropical wet/dry savanna in Australia: measurements and comparison with MODIS remote sensing estimates. Agric. For. Meteorol. 129, 151-173.

 

Tran, B. N., van der Kwast, J., Seyoum, S., Uijlenhoet, R., Jewitt, G., & Mul, M. (2023). Uncertainty assessment of satellite remote-sensing-based evapotranspiration estimates: A systematic review of methods and gaps. Hydrology and Earth System Sciences, 27, 4505–4528. https://doi.org/10.5194/hess-27-4505-2023

 

Uruskyi, O., Stankevich, S., Dudar, T., Mosov, S., & Prysiazhnyi, V. (2024). Integrated assessment of disturbed ecosystems using remote sensing technique. Science and Innovation, 20(5), 3–15. https://doi.org/10.15407/scine20.05.003

 

Wulder, M.A.; Franklin, S.E. (2003). Remote sensing of forest environments: concepts and case studies. Kluwer Academic Publishers: Boston, USA, 2003 (2)