SubscribeSWIFTT’s findings are communicated at scientific conferences and published in open-access journals. Find below the current list of publications.
Access all publication on the project's Zenodo community clicking here.
Satellite information technologies for the creation of the Ukrainian segment of the international GEOSS system
The paper describes the results of research and examples of creating information technologies based on satellite data in the fields of agricultural monitoring, assessment of the state of the Earth's cover and land degradation, monitoring of forests, assessment of fire danger, air quality, and monitoring of the water surface.
OP Fedorov, NM Kussul, AYu. Shelestov, LM Kolos, LV Pidgorodetska, BYa. Yailymov, HO Yailymova, VI Prysiazhnyi, VS Moroz, Space Sci. & Technol. 2025, 31(3), pp. 42-62. DOI: 10.15407/knit2025.03.042
Satellite-Based Analysis of Forest Damage in Ukraine’s Protected Areas
This study introduces an innovative satellite-based approach for rapid forest damage detection, providing a scalable, resource-efficient solution with minimal data and computational needs.
S. Drozd, N. Kussul and A. Shelestov, 2025 IEEE 13th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Gliwice, Poland, 2025, pp. 56-60, doi: 10.1109/IDAACS68557.2025.11322406.
Semi-Supervised European Forest Types Mapping using High-Fidelity Satellite Data
This study introduces an innovative semi-supervised approach for mapping European forest types by harnessing the power of high-resolution Sentinel-1 and Sentinel-2 satellite data from the Copernicus program.
Bohdan Yailymov, Hanna Yailymova, Nataliia Kussul and Andrii Shelestov, in Proceedings of the 4th International Workshop of IT-professionals on Artificial Intelligence (ProfIT AI 2024) 2024.
Semi-Supervised Forest Type Mapping in Europe on Satellite Data
This work describes the results of a forest map creation within HORIZON Europe project “Satellites for Wilderness Inspection and Forest Threat Tracking” (SWIFTT) for the territory of Europe for 2022 based on Sentinel-l,2 satellite data of the Copernicus program with a high spatial resolution of 10 meters.
N. Kussul, A. Shelestov, B. Yailymov and H. Yailymova, 2023 IEEE 12th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Dortmund, Germany, 2023, pp. 454-458, DOI: 10.1109/IDAACS58523.2023.10348948.
SILVIA: An eXplainable Framework to Map Bark Beetle Infestation in Sentinel-2 Images
This study explores the achievements of machine learning to perform the inventory mapping of bark beetle infestation hotspots in Sentinel-2 images.
G. Andresini, A. Appice and D. Malerba, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI: 10.1109/JSTARS.2023.3312521.
Statistical methods of feature engineering for the problem of forest state classification using satellite data
In this paper, the application of Bhattacharyya distance and Spearman’s rank correlation coefficient for feature selection from satellite images was investigated.
Y.V. Salii, A.M. Lavreniuk, N.M. Kussul, System research and information technologies, 1 (2024), doi: 10.20535/SRIT.2308-8893.2024.1.07
