Nataliia Kussul





doctor of science, Professor


Google Scholar




  • Taras Shevchenko National University of Kyiv (1987)
  • PhD: V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences (NAS) of Ukraine (1991)
  • Doctor of science: SRI NASU-SSAU (2001)

Career and organizational activity:

  • 1987-1996 – V. M. Hlushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine: software engineer, junior researcher, researcher, senior researcher
  • from 1996 – SRI NASU-SSAU: senior researcher, head of the department of information technologies and systems, deputy director for scientific work
  • from 1996 – NTUU “Igor Sikorsky Kyiv Polytechnic Institute”: associate professor, later professor of the Department of Information Security of Institute of Physics and Technology (IPT), from 2021 head of the Department of Mathematical Modeling and Data Analysis of IPT
  • from 2020 – representative of Ukraine in the high-level EuroGEO working group
  • scientific leader of international projects Horizon 2020, CRDF, INTAS, STCU, World Bank, European Space Agency
  • initiator of the creation and head of the regional support center of the UN-SPIDER program in Ukraine
  • coordinator of the Ukrainian Copernicus Academy laboratory

The following disciplines are currently being taught:

  • Methods of machine learning
  • Programming of effective algorithms
  • Models of sustainable development

Scientific interests:

  • Computational intelligence
  • Methods of machine learning
  • Information technologies of satellite monitoring
  • Risk analysis
  • Geospatial analysis

Monographs and books:

  • Howard, A., Chipanshi, A., Davidson, A., Desjardins, R., Kolotii, A., Kussul, N., McNairn, H., Skakun, S. and Shelestov, A. Chapter 18. Measurement Techniques. In Agroclimatology (eds J.L. Hatfield, M.V. Sivakumar and J.H. Prueger): Linking Agriculture to Climate, 2020. – Vol. 60. – P. 489-517
  • Шелестов А. Ю., Лавренюк М. С., Яйлимов Б. Я., Ткаченко О. М. Методи глибинного навчання для геопросторового аналізу та задач спостереження Землі, К.: “Наукова думка” – 2019. – 228 с.
  • Vladimir Lukin, Oleksii Rubel, Ruslan Kozhemiakin, Sergey Abramov, Andrii Shelestov, Mykola Lavreniuk, Mykola Meretsky, Benoit Vozel and Kacem Chehdi Despeckling of Multitemporal Sentinel SAR Images and Its Impact on Agricultural Area Classification, In Recent Advances and Applications in Remote Sensing. IntechOpen (Chapter 2). – 2018. – P. 21-40.
  • Куссуль Н.М., Скакун С.В., Шелестов А.Ю. Аналіз ризиків надзвичайних ситуацій на основі супутникових даних. Моделі і технології, К.: “Наукова думка” – 2014. – 184 с.
  • Куссуль Н. Н., Шелестов А. Ю. Использование РНР. Самоучитель.- М.: «Диалектика», 2005
  • Куссуль Н. М., Шелестов А. Ю., Лавренюк А. М. Інтелектуальні обчислення. Навчальний посібник (з грифом МОН України).- К.: «Наукова думка», 2006. — 186 с.
  • Куссуль Н. Н., Шелестов А. Ю., Скакун С. В., Кравченко А. Н. Интеллектуальные вычисления в задачах обработки данных наблюдения Земли.- К.: « Наукова думка», 2007. — 196 с.
  • Куссуль Н. Н., Шелестов А. Ю. Grid-системы для задач исследования Земли. Архитектура, модели и технологии.- К.: «Наукова думка», 2008. — 452 c.
  • Куссуль Н. М., Шелестов А. Ю., Скакун С. В., Кравченко О. М. Intelligent Data Processing in Global Monitoring for Environment and Security.- ITHEA, Київ-Софія, 2011

Основні публікації за останні роки:

  • Andrii ShelestovHanna YailymovaBohdan Yailymov, Nataliia Kussul Air Quality Estimation in Ukraine Using SDG 11.6.2 Indicator Assessment, Remote sensing. – 2021. – No. 13(23), 4769. 
  • Leonid Shumilo, Mykola Lavreniuk, Sergii Skakun, Nataliia Kussul Is Soil Bonitet an Adequate Indicator for Agricultural Land Appraisal in Ukraine?, Міжнародний науковий журнал «Sustainability» видавництва MDPI. – 2021. – N0. 13, 12096. 
  • Deininger, K., Ali, D. A., Kussul, N., Lavreniuk, M., & Nivievskyi, O. Using Machine Learning to Assess Yield Impacts of Crop Rotation: Combining Satellite and Statistical Data for Ukraine, Policy research working papers. – 2020. DOI: 10.1596/1813-9450-9306
  • Nataliia Kussul, Mykola Lavreniuk, Andrii Kolotii, Sergii Skakun, Olena Rakoid, Leonid Shumilo A workflow for Sustainable Development Goals indicators assessment based on high-resolution satellite data, International Journal of Digital Earth. – 2020. – Vol. 2, No. 13. – P. 309-321.
  • 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 – 2020. – Vol. 6, No. 3. – 572-582 pp.
  • 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. – P. 305.
  • Sergii Skakun, Eric Vermote, Belen Franch, Jean-Claude Roger, Nataliia Kussul, Junchang Ju, Jeffrey Masek Winter Wheat Yield Assessment from Landsat 8 and Sentinel-2 Data: Incorporating Surface Reflectance, Through Phenological Fitting, into Regression Yield Models, Remote Sensing. – 2019. – Vol. 11, No. 15. – P. 1768. 
  • Kussul, N., Lavreniuk M., Shelestov, A., & Skakun, S. (2018). 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.
  • Kussul, N., Lavreniuk, M., Skakun, S., & Shelestov, A. (2017) “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.
  • Shelestov, A., Lavreniuk, M., Kussul, N., Novikov, A., & Skakun S. (2017) “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.
  • Kussul, N., Lemoine, G., Gallego, J., Skakun, S., Lavreniuk, M., & Shelestov A. (2016) “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.
  • Kussul, N. N., Lavreniuk, N. S., Shelestov, A. Y., Yailymov, B. Y., & Butko, I. N. (2016). Land cover changes analysis based on deep machine learning technique. Journal of Automation and Information Sciences, 48(5), 42–54.
  • Skakun S., Kussul N., Shelestov A., Kussul O. (2016) “The use of satellite data for agriculture drought risk quantification in Ukraine”, Geomatics, Natural Hazards and Risk, vol. 7, no. 3, pp. 901–917.
  • Skakun, S., Kussul, N., Shelestov, A.Y., Lavreniuk, M., Kussul, O. (2016) “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.
  • Skakun S., Kussul N., Shelestov A., Kussul O. (2014) “Flood Hazard and Flood Risk Assessment Using a Time Series of Satellite Images: A Case Study in Namibia”, Risk Analysis, Vol. 34, No. 8, pp. 1521–1537.
  • Kogan, F., Kussul, N., Adamenko, T., Skakun, S., Kravchenko O., Kryvobok O., Shelestov A., Kolotii A., Kussul O. & Lavrenyuk A. Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models.-International Journal of Applied Earth Observation and Geoinformation, 2013 vol. 23, pp. 192—203.
  • Kussul N., Mandl D., Moe K., Mund J.P., Post J., Shelestov A., Skakun S., Szarzynski J., Van Langenhove G., Handy M. Interoperable Infrastructure for Flood Monitoring: SensorWeb, Grid and Cloud.- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2012 vol. 5, no. 6, pp. 1740—1745.
  • Kussul N., Shelestov A., Skakun S., Li G., Kussul O. The Wide Area Grid Testbed for Flood Monitoring Using Earth Observation Data.- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2012, vol. 5, no. 6, pp. 1746—1751.
  • Kussul N., Shelestov A., Skakun S. Technologies for Satellite Data Processing and Management Within International Disaster Monitoring Projects// In . Grid and Cloud Database Management Grid — Fiore, S.; Aloisio, G. (Eds.). — 2011, Springer — Р. 279—306.
  • Kussul N., Shelestov A., Skakun S., Kravchenko O. High-performance Intelligent Computations for Environmental and Disaster Monitoring/ In Intelligent Data Processing in Global Monitoring for Environment and Security — ITHEA, Kiev-Sofia, 2011 — P. 76-103.
  • Kussul N., Shelestov A., Skakun S. Flood Monitoring on the Basis of SAR Data/ In 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. — P. 19-29.
  • Lecca G., Petitdidier M., Hluchy L., Ivanovic M., Kussul N., Ray N., Thieron V.: Grid computing technology for hydrological applications. Grid computing technology for hydrological applications.- Journal of Hydrology, 2011, Volume 403, Issues 1-2, 6 June 2011, P. 186—199.