Olha Danylo

Olha Danylo joined IIASA's Ecosystems Services and Management Program (ESM)in 2014, with an Ernst Mach Scholarship and continued working as a research assistant with the Environmental Resources and Development (ERD) and the Earth Observation Systems (EOS) groups. Her current scientific interests include the usage of GIS and machine learning tools to analyze spatial and remote sensing data, aiming to improve land cover mapping and contribute to urban climatology science.

Dr. Danylo graduated from the department of Applied Mathematics at Lviv Polytechnic National University (Ukraine) in 2012, where she obtained her MSc degree in Mathematical and Computer Modeling. Dr. Danylo obtained her PhD degree in Engineering Science at the Lviv Polytechnic National University (Ukraine) in 2015. During her PhD studies she was a visiting researcher in Systems Research Institute of the Polish Academy of Sciences (SRI, Poland) and at IIASA. She also participated in the Young Scientists Summer Program (YSSP) in 2012.


Last update: 26-APR-2016

Jonas M ORCID: https://orcid.org/0000-0003-1269-4145, Bun R, Nahorski Z, Marland G, Gusti M, & Danylo O (2019). Quantifying greenhouse gas emissions. Mitigation and Adaptation Strategies for Global Change DOI:10.1007/s11027-019-09867-4. (In Press)

Lesiv M, Laso Bayas JC, See L, Dürauer M, Dahlia D, Durando N, Hazarika R, Sahariah PK, et al. (2019). Estimating the Global Distribution of Field Size using Crowdsourcing. Global Change Biology 25 (1): 174-186. DOI:10.1111/gcb.14492.

Danylo O, Bun R, See L, & Charkovska N (2019). High-resolution spatial distribution of greenhouse gas emissions in the residential sector. Mitigation and Adaptation Strategies for Global Change DOI:10.1007/s11027-019-9846-z. (In Press)

Laso Bayas JC, Moorthy I, Sturn T, Karner M, Perger C, Fraisl D, Domian D, Gardeazabal A, et al. (2018). Citizen Scientists Monitoring the Environment: The Latest Apps from IIASA. In: Citizen Observatories for natual hazards and Water Management, 27-30 November 2018, Venice, Italy.

Lesiv M, Bayas JCL, See L, Duerauer M, Dahlia D, Durando N, Hazarika R, Sahariah PK, et al. (2018). Estimating the Global Distribution of Field Size using Crowdsourcing.

Danylo O, Moorthy I, Sturn T, See L, Laso Bayas J-C, Domian D, Fraisl D, Giovando C, et al. (2018). The Picture Pile Tool for Rapid Image Assessment: A Demonstration using Hurricane Matthew. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4: 27-32. DOI:10.5194/isprs-annals-IV-4-27-2018.

See L, Fritz S, Moorthy I, Danylo O, van Dijk M, & Ryan B (2018). Using Remote Sensing and Geospatial Information for Sustainable Development. In: From Summits to Solutions: Innovations in Implementing the Sustainable Development Goals. Eds. Desai, R.M., Kato, H., Kharas, H. & McArthur, J.W., pp. 172-198 Brookings Institution Press. ISBN 9780815736639

Lesiv M, Fritz S, Laso Bayas JC, Dürauer M, Domian D, See L, McCallum I, Danylo O, et al. (2018). Global Field Sizes Dataset for Ecosystems Modeling. In: European Geosciences Union General Assembly 2018, 9-13 April 2018, Vienna, Austria.

Bun R, Nahorski Z, Horabik-Pyzel J, Danylo O, See L, Charkovska N, Topylko P, Halushchak M, et al. (2018). Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources. Mitigation and Adaptation Strategies for Global Change: 1-28. DOI:10.1007/s11027-018-9791-2.

Charkovska N, Horabik-Pyzel J, Bun R, Danylo O, Nahorski Z, Jonas M, & Xiangyang X (2018). High resolution spatial distribution and associated uncertainties of greenhouse gas emissions from the agricultural sector. Mitigation and Adaptation Strategies for Global Change 23: 1-25. DOI:10.1007/s11027-017-9779-3.

Kinakh V, Bun R, & Danylo O (2018). Geoinformation Technology for Analysis and Visualisation of High Spatial Resolution Greenhouse Gas Emissions Data Using a Cloud Platform. In: Advances in Intelligent Systems and Computing II. Eds. Shakhovska, N. & Stepashko, V., pp. 217-229 Cham, Switzerland: Springer International. ISBN 978-3-319-70581-110.1007/978-3-319-70581-1_15.

Kinakh V, Bun R, & Danylo O (2017). Geoinformation technology of analysis and vizualization of spatial data on greenhouse gas emissions using Google Earth Engine. In: 2017 12th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT). pp. 212-215 Liev, Ukraine: IEEE. ISBN 978-153861638-310.1109/STC-CSIT.2017.8098771.

Laso Bayas JC, Lesiv M, Waldner F, Schucknecht A, Duerauer M, See L, Fritz S, Fraisl D, et al. (2017). A global reference database of crowdsourced cropland data collected using the Geo-Wiki platform. Scientific Data 4: e170136. DOI:10.1038/sdata.2017.136.

Moorthy I, See L, Fritz S, McCallum I, Perger C, Dürauer M, Dresel C, Sturn T, et al. (2017). Crowd-driven tools for the calibration and validation of Earth Observation products. In: Earth Observation Open Science 2017 Conference, 25-28 September 2017, Frascati, Italy.

Fritz S, See L, Perger C, McCallum I, Schill C, Schepaschenko D, Duerauer M, Karner M, et al. (2017). A global dataset of crowdsourced land cover and land use reference data. Scientific Data 4: p. 170075. DOI:10.1038/sdata.2017.75.

Danylo O, Sturn T, Giovando C, Moorthy I, Fritz S, See L, Kapur R, Girardot B, et al. (2017). Picture Pile: A citizen-powered tool for rapid post-disaster damage assessments. In: European Geosciences Union (EGU) General Assembly 2017, 23–28 April 2017, Vienna, Austria.

Crespo Cuaresma J, Danylo O, Fritz S, McCallum I, Obersteiner M ORCID: https://orcid.org/0000-0001-6981-2769, See L, & Walsh B ORCID: https://orcid.org/0000-0003-1689-2309 (2017). Economic Development and Forest Cover: Evidence from Satellite Data. Scientific Reports 7: art.no.40678. DOI:10.1038/srep40678.

Danylo O, See L, Gomez Sanabria A, Schnabel G, & Fritz S (2017). Using the LCZ framework for change detection and urban growth monitoring. Geophysical Research Abstracts 19: p. 18043.

Crespo Cuaresma J, Danylo O, Fritz S, McCallum I, Obersteiner M, & See L (2016). Economic development and forest cover: evidence from satellite data. Working Paper No. 25, Department of Economics, Vienna University of Economics and Business

Charkovska N, Danylo O, Topylko P, Halushchak M, Nahorski Z, & Horabik-Pyzal J (2016). Spatial modeling of greenhouse gas emissions from stationary sources. Ukraine: PP Soroka T.B.. ISBN 978-966-2598-74-2

Danylo O, See L, Bechtel B, Schepaschenko D, & Fritz S (2016). Contributing to WUDAPT: A Local Climate Zone Classification of Two Cities in Ukraine. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS) 9 (5): 1841-1853. DOI:10.1109/JSTARS.2016.2539977.

Charkovska NR, Bun R, Danylo O, Horabik-Pyzel J, & Jonas M (2015). Spatial GHG inventory in the agriculture sector and uncertainty analysis: A case study for Poland. In: Proceedings, 4th International Workshop on Uncertainty in Atmospheric Emissions, 7-9 October 2015, Krakow, Poland. pp. 16-24 Warsaw, Poland: Systems Research Institute, Polish Academy of Sciences. ISBN 83-894-7557-X

Danylo O, Bun R, See L, Topylko P, Xu X, Charkovska N, & Tymków P (2015). Accounting uncertainty for spatial modeling of greenhouse gas emissions in the residential sector: fuel combustion and heat production. In: Proceedings, 4th International Workshop on Uncertainty in Atmospheric Emissions, 7-9 October 2015, Krakow, Poland. pp. 193-200 Warsaw, Poland: Systems Research Institute, Polish Academy of Sciences. ISBN 83-894-7557-X

Horabik-Pyzel J, Charkovska N, Danylo O, Nahorski Z, & Bun R (2015). Conditionally autoregressive model for spatial disaggregation of activity data in GHG inventory: Application for agriculture sector in Poland. In: Proceedings, 4th International Workshop on Uncertainty in Atmospheric Emissions, 7-9 October 2015, Krakow, Poland. pp. 25-31 Warsaw, Poland: Systems Research Institute, Polish Academy of Sciences. ISBN 83-894-7557-X

Oda T, Ott L, Topylko P, Halushchak M, Bun R, Lesiv M, Danylo O, & Horabik-Pyzel J (2015). Uncertainty associated with fossil fuel carbon dioxide (CO2) gridded emission datasets. In: Proceedings, 4th International Workshop on Uncertainty in Atmospheric Emissions, 7-9 October 2015, Krakow, Poland. pp. 124-129 Warsaw, Poland: Systems Research Institute, Polish Academy of Sciences. ISBN 83-894-7557-X

Topylka P, Halushchak M, Bun R, Oda T, Lesiv M, & Danylo O (2015). Spatial Greenhouse Gas (GHG) inventory and uncertainty analysis: A case study for electricity generation in Poland and Ukraine. In: Proceedings, 4th International Workshop on Uncertainty in Atmospheric Emissions, 7-9 October 2015, Krakow, Poland. pp. 49-56 Warsaw, Poland: Systems Research Institute, Polish Academy of Sciences. ISBN 83-894-7557-X

Bun R, Nahorski Z, Horabik-Pyzel J, Danylo O, Charkovska N, Topylko P, Halushchak M, Lesiv M, et al. (2015). High resolution spatial inventory of GHG emissions emissions from stationary and mobile sources in Poland: summarized results and uncertainty analysis. In: Proceedings, 4th International Workshop on Uncertainty in Atmospheric Emissions, 7-9 October 2015, Krakow, Poland. pp. 41-48 Warsaw, Poland: Systems Research Institute, Polish Academy of Sciences. ISBN 83-894-7557-X

Danylo O (2012). Spatial inventory of greenhouse gas emissions in the residential sector: a case-study for Poland and Ukraine. In: Worlds Within Reach: From Science To Policy - IIASA 40th Anniversary Conference, 24-26 October 2012, Hofburg Congress Center, Vienna and IIASA, Laxenburg, Austria.