Dr. Sergii Skakun is a Associate Professor with a joint appointment at the Department of Geographical Sciences and the College of Information Studies (iSchool). He joined UMD in October 2015. From 2013 to 2015, he was a Senior Engineer at Samsung SDI (South Korea), where he was responsible for developing industrial vision inspection systems. From 2006 to 2013, he has held multiple positions (latest Senior Scientist) at the Space Research Institute (Ukraine), where he was performing research in remote sensing. He received PhD in Computer Science from National Academy of Sciences of Ukraine in 2005.
Dr. Skakun has participated as a PI or Co-I in projects funded by NASA, NSF, Google, European Commission (EC), EC Joint Research Center (JRC), U.S. Civilian Research & Development Foundation (CRDF), National Academy of Sciences of Ukraine, State Space Agency of Ukraine and Science & Technology Center in Ukraine (STCU).
He is a two-time recipient as a PI of the Future Investigators in NASA Earth and Space Science and Technology (FINESST) grants "Agriculture Velocity of Winter Wheat" (2022-2025, Leonid Shumilo) and "Climate induced agriculture change hotspots and its implication to global food security in the former Soviet Union (Russia and Ukraine)" (2021-2024, Abdul Qadir).
His recent projects include "Artillery Craters and Unexploded Ordnance Mapping in Ukraine using High Resolution Satellite Imagery" (NASA, 2023-2024), "High-Impact Hot Spots of Land Cover Land Use Change: Ukraine and Neighboring Countries" (NASA, 2021-2023), "FAI: Advancing Deep Learning Towards Spatial Fairness" (NSF, 2022-2025) and "Maintenance and refinement of the Suomi NPP and NOAA-20 VIIRS Land Surface Reflectance product suite" (NASA, 2021-2024). He is currently a Co-I on two NASA Agricultural Programs: Harvest and Acres.
Within Committee on Earth Observation Satellites (CEOS), he is co-leading a Cloud Masking Inter-comparison Exercise (CMIX, https://calvalportal.ceos.org/cmix). He is currently an Associate Editor for the journal Remote Sensing of Environment. As of now, he authored or co-authored >70 papers in peer-reviewed journals, 3 books (in Ukrainian/Russian), and 6 chapters in edited books.
His current research focus is to advance methods, models and emerging technologies in the area of data science for heterogeneous remote sensing data fusion, processing and analysis, and their applications to Earth System Science and areas of societal benefit.
- Qadir, A., Skakun, S., Eun, J., Prashnani, M., Shumilo, L. (2023). Sentinel-1 time series data for sunflower (Helianthus annuus) phenology monitoring. Remote Sensing of Environment, 295, art. num. 113689. https://doi.org/10.1016/j.rse.2023.113689
- Duncan, E. C., Skakun, S., Kariryaa, A., & Prishchepov, A. V. (2023). Detection and mapping of artillery craters with very high spatial resolution satellite imagery and deep learning. Science of Remote Sensing, 7, art. num. 100092. https://doi.org/10.1016/j.srs.2023.100092
- Doxani, G., Vermote, E. F., Roger, J. C., Skakun, S., Gascon, F., Collison, A., ... & Yin, F. (2023). Atmospheric Correction Inter-comparison eXercise, ACIX-II Land: An assessment of atmospheric correction processors for Landsat 8 and Sentinel-2 over land. Remote Sensing of Environment, 285, art. num. 113412. https://doi.org/10.1016/j.rse.2022.113412
- Skakun, S., Wevers, J., Brockmann, C., Doxani, G., Aleksandrov, M., Batič, M., Frantz, D., Gascon, F., Gómez-Chova, L., Hagolle, O., López-Puigdollers, D., Louis, J., Lubej, M., Mateo-García, G., Osman, J., Peressutti, D., Pflug, B., Puc, J., Richter, R., Roger, J.-C., Scaramuzza, P., Vermote, E., Vesel, N., Zupanc, A., Žust, L. (2022). Cloud Mask Intercomparison eXercise (CMIX): An evaluation of cloud masking algorithms for Landsat 8 and Sentinel-2. Remote Sensing of Environment, 274, art. num. 112990. https://doi.org/10.1016/j.rse.2022.112990
- Zhang, Y., Skakun, S., Adegbenro, M.O., & Ying, Q. (2022). Leveraging the use of labeled benchmark datasets for urban area change mapping and area estimation: a case study of the Washington DC–Baltimore region. International Journal of Digital Earth, 15(1), 1169-1186. https://doi.org/10.1080/17538947.2022.2094001
- Abys, C., Skakun, S., & Becker-Reshef, I. (2022). The Rise and Volatility of Russian Winter Wheat Production. Environmental Research Communications, 4(10), art. num. 101003. https://doi.org/10.1088/2515-7620/ac97d2
- Prudente, V.H.R., Skakun, S., Oldoni, L.V., Xaud, H.A., Xaud, M.R., Adami, M., & Sanches, I.D.A. (2022). Multisensor approach to land use and land cover mapping in Brazilian Amazon. ISPRS Journal of Photogrammetry and Remote Sensing, 189, 95–109. https://doi.org/10.1016/j.isprsjprs.2022.04.025
- Eun, J., & Skakun, S. (2022). Characterizing land use with night-time imagery: the war in Eastern Ukraine (2012–2016). Environmental Research Letters, 17, art. num. 095006. https://doi.org/10.1088/1748-9326/ac8b23
- Skakun, S., Vermote, E. F., Artigas, A. E. S., Rountree, W. H., & Roger, J. C. (2021). An experimental sky-image-derived cloud validation dataset for Sentinel-2 and Landsat 8 satellites over NASA GSFC. International Journal of Applied Earth Observation and Geoinformation, 95, art. num. 102253. https://doi.org/10.1016/j.jag.2020.102253
- Skakun, S., Kalecinski, N.I., Brown, M.G.L., Johnson, D.M., Vermote, E.F., Roger, J.-C., & Franch, B. (2021). Assessing within-Field Corn and Soybean Yield Variability from WorldView-3, Planet, Sentinel-2, and Landsat 8 Satellite Imagery. Remote Sensing, 13, art. num. 872. https://doi.org/10.3390/rs13050872
- Gitelson, A., Arkebauer, T., Viña, A., Skakun, S., & Inoue Y. (2021). Evaluating plant photosynthetic traits via absorption coefficient in the photosynthetically active radiation region. Remote Sensing of Environment, 258, art. num. 112401. https://doi.org/10.1016/j.rse.2021.112401
He is teaching the following courses:
- GEOG461 “Machine Learning for Computational Earth Observation Science (CEOS)”,
- INST156 “How NASA Sees the Earth” (GenEd course),
- GEOG371 “Programming for Image Analysis”,
- GEOG272/GEOG372 "Remote Sensing".
As part of the NASA Harvest team, results of his research on the impact of the war in Ukraine on agriculture was featured in the mass media:
- Maryland Today: "Unexploded Ordnance Is Scattered Across Ukraine’s Front Lines. UMD Researchers Are Mapping Hot Spots With AI.", https://today.umd.edu/unexploded-ordnance-is-scattered-across-ukraines-front-lines-umd-researchers-are-mapping-hot-spots-with-ai
- Bloomberg: “Russia Reaped $1 Billion of Wheat in Occupied Ukraine, NASA Says”, https://www.bloomberg.com/news/articles/2022-12-03/russia-reaped-1-billion-of-wheat-in-occupied-ukraine-nasa-says
- NASA Earth Observatory: “Larger Wheat Harvest in Ukraine Than Expected”, https://earthobservatory.nasa.gov/images/150590/larger-wheat-harvest-in-ukraine-than-expected
- New York Times: “Russia now occupies roughly 22 percent of Ukraine’s farmland, according to a NASA analysis”, https://www.nytimes.com/live/2022/07/07/world/russia-ukraine-war-news/russia-now-occupies-roughly-22-percent-of-ukraines-farmland-according-to-a-nasa-analysis?smid=url-share
- NASA Earth Observatory: “Measuring War’s Effect on a Global Breadbasket”, https://earthobservatory.nasa.gov/images/150025/measuring-wars-effect-on-a-global-breadbasket
- NASA Earth Observatory: “Tracking Night Lights in Ukraine”, https://earthobservatory.nasa.gov/images/150002/tracking-night-lights-in-ukraine
- Maryland Today: “Russian Attack on Ukraine Also Targeted Global Food Supply”, https://today.umd.edu/russian-attack-on-ukraine-also-targeted-global-food-supply
Areas of Interest
- Remote sensing
- Agricultural monitoring
- Machine learning in remote sensing
- Disaster monitoring and risk assessment
Degree TypePhDDegree DetailsComputer Science, Space Research Institute NASU-SSAU (Ukraine), 2005
Degree TypeMSDegree DetailsApplied Mathematics, National Technical University of Ukraine “Kyiv Polytechnic Institute”, 2004
Degree TypeBSDegree DetailsApplied Mathematics, National Technical University of Ukraine “Kyiv Polytechnic Institute”, 2002
Ongoing projects (PI or UMD PI):
|2023-2024||PI for the NASA Rapid Response project “Artillery Craters and Unexploded Ordnance Mapping in Ukraine using High Resolution Satellite Imagery”|
|2022 – 2025||PI for the NASA project “Agriculture Velocity of Winter Wheat” within Future Investigators in NASA Earth and Space Science and Technology (FINESST).
FI: Leonid Shumilo (graduate student)
|2022 – 2025||Co-PI for the NSF project “FAI: Advancing Deep Learning Towards Spatial Fairness” (NSF Program on Fairness in Artificial Intelligence in Collaboration with Amazon).
PI: X. Jia (University of Pittsburgh), Co-PI: Y. Xie (UMD)
|2021-2024||UMD PI for the NASA project “Maintenance and refinement of the Suomi NPP and NOAA-20 VIIRS Land Surface Reflectance product suite”.
PI: E. Vermote (NASA/GSFC)
|2021 – 2024||PI the NASA project “Climate induced agriculture change hotspots and its implication to global food security in the
former Soviet Union (Russia and Ukraine)” within Future Investigators in NASA Earth and Space Science
and Technology (FINESST)
FI: Abdul Qadir (graduate student)
2021 – 2023
PI for the NASA project “High-Impact Hot Spots of Land Cover Land Use Change: Ukraine and Neighboring Countries”
2019 – 2022
UMD PI for the NASA project “Integration of L-band, C-band, and optical observations for agricultural monitoring”
|2021 – 2022||UMD PI for the IARPA/NGA project “WATCH: Wide Area Terrestrial Change Hypercube”
PI: M. Leotta (Kitware)
ProfessionalAssociate Editor, journal Remote Sensing of Environment
ProfessionalEditorial Board Member, section “Remote Sensing Image Processing”, journal Remote Sensing
InternationalTask Coordinator of the Cloud Masking Inter-comparison eXercise (CMIX) within CEOS WGCV
CampusRemote Sensing Teaching Team Lead
Andres Eduardo Santamaria ArtigasPostDoc at UMD
José Luis VillaescusaEUMETSAT
Meredith BrownPostDoc at Sandia National Laboratories
- Christian Abys
- Katherine Melocik
- Abdul Qadir
- Leonid Shumilo
- Yiming Zhang