Bozhena Omelianska

Mrs. Bozhena Omelianska

Geoinformatics, Cartography and Remote Sensing, University of Warsaw, Warsaw, Mazowieckie, Poland
orcid

Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 June 2023 in Remote Sensing
Verified
Journal Article
Open access
PDF file
Anna JarocińskaAnna Jarocińska
Anna Jarocińska
Jan NiedzielkoJan Niedzielko
Jan Niedzielko
Dominik KopećDominik Kopeć
Dominik Kopeć
JWJustyna Wylazłowska
Justyna Wylazłowska
BOBozhena Omelianska
Bozhena Omelianska
JCJakub Charyton
Jakub Charyton
One of the key issues in wetland monitoring is mapping vegetation. Remote sensing and machine learning are used to acquire vegetation maps, which, due to the development of sensors and data processing and analysis methods, have increasingly high accuracy. The objectives of this study were to test: (i) which of the textural information (TI) features have the highest information potential for identifying wetland communities; and (ii) whether the use of TI improves the accuracy of wetland communities mapping using hyperspectral (HS) and Airborne Laser Scanning (ALS) data. The analysis indicated that the mean and entropy features of the Gray Level Co-occurrence Matrix had the highest potential to differentiate between various wetland communities. Adding these features to the dataset resulted in a small increase (0.005) in average F1 accuracy based on HS data and 0.011 for HS and ALS scenarios in wetland communities classification, and adding TI improved the delineation of patch boundaries. A higher increase was noted for forest and scrub vegetation (by 0.019 for the HS scenario and 0.022 for the HS and ALS scenario) and rushes (only for the HS and ALS scenario 0.017). It can be concluded that it is reasonable to use textural information for mapping wetland communities, especially for areas with a high proportion of scrub and forest and rushes vegetation included in the analysis.

22 January 2026 in NeoBiota
Verified
Journal Article
Open access
EREdyta Regulska
Edyta Regulska
MZMartyna A. Zarzycka
Martyna A. Zarzycka
AOArtur Obidziński
Artur Obidziński
EKEwa Kołaczkowska
Ewa Kołaczkowska
AKAnna Kowalska
Anna Kowalska
AAAndrzej Norbert Affek
Andrzej Norbert Affek
North American goldenrods ( Solidago spp.) rank among the most ecologically impactful invasive plants in Europe, Asia, and other regions. Their spread is driven by high ecological plasticity, rapid growth, and allelopathic effects. While the number of publications on Solidago invasions has grown substantially in recent decades, existing reviews tend to be narrative and focus on single species or few mechanisms. In this systematic review, we analyze 180 peer-reviewed empirical studies to assess global trends, methodological approaches, and research biases in studies addressing interactions between invasive Solidago and the environment. Most studies applied a single methodological approach, with ex situ experiments dominating, while field observations and in situ manipulative experiments were less common. Long-term studies were rare, and research primarily addressed current conditions rather than future scenarios. The taxonomic focus was centered on S. canadensis L., with other species being much less studied. Geographically, research was concentrated in Europe and Asia, with field-based studies more common in Europe and ex situ experiments dominating in Asia. Solidago spp. served as either a response or an explanatory variable, reflecting both its response to environmental conditions and its impact on the invaded ecosystem.