Andrii Shelestov





Doctor of Sciences, Professor


Google Scholar


  • 1984 – 1992: Student of KPI named after Igor Sikorskyi – M.Sc
    1992 – 1996: Postgraduate student of the Institute of Cybernetics of the National Academy of Sciences – candidate of technical sciences
    2005 – 2008: PhD student of SRI NASU-SSAU – Doctor of Technical Sciences


  • 1992 – 1996: Institute of Cybernetics of the National Academy of Sciences – software engineer, programmer, leading programmer, researcher
  • since 1996: Institute of Space Research of the National Academy of Sciences of Ukraine and SSA of Ukraine – researcher, senior researcher, leading researcher
  • 1996 – 2006: Computer publishing houses “Dialektyka”, “Junior” and Williams – translator and scientific editor
  • 1999 – 2000: Communico Ukraine LTD – leading system developer
  • 2003 – 2007: National Aviation University – associate professor of software engineering department
  • from 2003: NTUU “Igor Sikorsky Kyiv Polytechnic Institute” – associate professor, professor of the Department of Information Security, from 2021 – professor of the Department of Mathematical Modeling and Data Analysis
  • from 2010: National University of Bioresources and Nature Management of Ukraine – Head of the Department of Computer Sciences


  • 2015: Certificate of Honor of the Kyiv City Council for services to the Ukrainian people

Membership in professional communities:

  • since 2014: IEEE, EGU, AGU

Scientific interests:

  • Intelligent computing
  • Methods of satellite data processing
  • Information Technology
  • Cloud – computing
  • Development of distributed systems

The following disciplines are currently being taught:

  • Web programming
  • Special sections of programming (Data preparation and analysis tools)
  • Geospatial analysis
  • Inductive modeling


  • А.Ю. Шелестов, М.С. Лавренюк, Б.Я. Яйлимов, О.м, Ткаченко  Митоди глибинного навчання для геопросторового аналізу та задач спостереження Землі – Київ: «Наукова думка», 2019.-228с.
  • Shelestov A., Lavreniuk M. Recent Advances and Applications in Remote Sensing (Chapter) Despeckling of Multitemporal Sentinel Sar Images and Its Impact on Agricultural Area Classification (2018)
  • Kussul N., Shelestov A., Skakun S. Grid and Cloud Database Management Grid In Fiore, S.; Aloisio, G. (Eds.). — 2011, Springer / Technologies for Satellite Data Processing and Management Within International Disaster Monitoring Projects. p. 279–306
  • Kussul N., Shelestov A., Skakun S. Use of Satellite and In-Situ Data to Improve Sustainability F. Kogan, A. Powell, O. Fedorov (Eds.). — NATO Science for Peace and Security Series C: Environmental Security, Springer, 2011 / Flood Monitoring on the Basis of SAR Data. p. 19–29

Main publications in recent years:

  • Andrii Shelestov, Mykola Lavreniuk, Vladimir Vasiliev, Leonid Shumilo, Andrii Kolotii, Bohdan Yailymov, Nataliia Kussul, Hanna Yailymova  Cloud Approach to Automated Crop Classification Using Sentinel-1 Imagery IEEE Transactions on Big Data ( Early Access ) – 2019 – 1 p– DOI: 10.1109/TBDATA.2019.2940237 Electronic ISSN: 2332-7790 CD-ROM ISSN: 2372-2096.
  • Pierre Defourny et al. Near real-time agriculture monitoring at national scale at parcel resolution: Performance assessment of the Sen2-Agri automated system in various cropping systems around the world  Remote sensing of environment – 2019 – Volume 221  –  551-568 pp – DOI: 10.1016/j.rse.2018.11.007
  • Sergii Skakun, Christopher O Justice, Nataliia Kussul, Andrii Shelestov, Mykola Lavreniuk Satellite data reveal cropland losses in South-Eastern Ukraine under military conflict Frontiers in Earth Science – 2019 – 305 p – DOI: 10.3389/feart.2019.00305.
  • François Waldner et al. Conflation of expert and crowd reference data to validate global binary thematic maps Remote sensing of environment – 2019 – Volume 221 – 235-246 pp – DOI: 10.1016/j.rse.2018.10.039.
  • Kussul, N., Lavreniuk M., Shelestov, A., & Skakun, S. Crop inventory at regional scale in Ukraine: developing in season and end of season crop maps with multi-temporal optical and SAR satellite imagery. European Journal of Remote Sensing, 51 (1), 627-636 (2018).
  • Kussul, N., Lavreniuk, M., Skakun, S., & Shelestov, A. Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data, IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 5, pp. 778–782 (2017) .
  • Shelestov, A., Lavreniuk, M., Kussul, N., Novikov, A., & Skakun S.  Exploring Google Earth Engine Platform for Big Data Processing: Classification of Multi-Temporal Satellite Imagery for Crop Mapping, Frontiers in Earth Science, 5:17. doi:10.3389/feart.2017.00017 (2017).
  • Kussul, N., Lemoine, G., Gallego, J., Skakun, S., Lavreniuk, M., & Shelestov A. Parcel-based Crop Classification in Ukraine Using Landsat-8 Data and Sentinel-1A Data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 6, pp. 2500–2508 (2016).
  • Kussul, N. N., Lavreniuk, N. S., Shelestov, A. Y., Yailymov, B. Y., & Butko, I. N. Land cover changes analysis based on deep machine learning technique. Journal of Automation and Information Sciences, 48 (5), 42–54 (2016).
  • Skakun S., Kussul N., Shelestov A., Kussul O. The use of satellite data for agriculture drought risk quantification in Ukraine, Geomatics, Natural Hazards and Risk, vol. 7, no. 3, pp. 901–917 (2016).
  • Skakun, S., Kussul, N., Shelestov, A.Y., Lavreniuk, M., Kussul, O.  Efficiency Assessment of Multitemporal C-Band Radarsat-2 Intensity and Landsat-8 Surface Reflectance Satellite Imagery for Crop Classification in Ukraine, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 8, pp. 3712–3719 (2016).