A
Andrii Shelestov
Researcher at National Technical University
Publications - 43
Citations - 2453
Andrii Shelestov is an academic researcher from National Technical University. The author has contributed to research in topics: Computer science & Land cover. The author has an hindex of 12, co-authored 27 publications receiving 1594 citations. Previous affiliations of Andrii Shelestov include National Academy of Sciences of Ukraine & National University of Life and Environmental Sciences of Ukraine.
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Journal ArticleDOI
Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data
TL;DR: A multilevel DL architecture that targets land cover and crop type classification from multitemporal multisource satellite imagery outperforms the one with MLPs allowing us to better discriminate certain summer crop types.
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Exploring Google Earth Engine platform for big data processing: classification of multi-temporal satellite imagery for crop mapping
Andrii Shelestov,Mykola Lavreniuk,Nataliia Kussul,Alexei Novikov,Sergii Skakun,Sergii Skakun +5 more
TL;DR: Efficiency of using the Google Earth Engine (GEE) platform when classifying multi-temporal satellite imagery with potential to apply the platform for a larger scale and in terms of classification accuracy, the neural network based approach outperformed support vector machine, decision tree and random forest classifiers available in GEE.
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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
Pierre Defourny,Sophie Bontemps,Nicolas Bellemans,Cosmin Cara,Gérard Dedieu,Eric Guzzonato,Olivier Hagolle,Jordi Inglada,Laurentiu Nicola,Thierry Rabaute,Mickael Savinaud,Cosmin Udroiu,Silvia Valero,Agnès Bégué,Jean-François Dejoux,Abderrazak El Harti,Jamal Ezzahar,Nataliia Kussul,Kamal Labbassi,Valentine Lebourgeois,Zhang Miao,Terrence Newby,Adolph Nyamugama,Norakhan Salh,Andrii Shelestov,Vincent Simonneaux,Pierre C. Sibiry Traoré,Souleymane Sidi Traore,Benjamin Koetz +28 more
TL;DR: These full-scale demonstration results clearly highlight the operational agriculture monitoring capacity of the Sen2-Agri system to exploit in near real-time the observation acquired by the Sentinel-2 mission over very large areas.
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Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models
Felix Kogan,Nataliia Kussul,Tatiana Adamenko,Sergii Skakun,Oleksii Kravchenko,Oleksii Kryvobok,Andrii Shelestov,Andrii Shelestov,Andrii Kolotii,Olga Kussul,Alla N. Lavrenyuk +10 more
TL;DR: It is concluded that performance of empirical NDVI-based regression model was similar to meteorological and CGMS models when producing winter wheat yield forecasts at oblast level in Ukraine 2–3 months prior to harvest, while providing minimum requirements to input datasets.
Journal ArticleDOI
Parcel-Based Crop Classification in Ukraine Using Landsat-8 Data and Sentinel-1A Data
Nataliia Kussul,Guido Lemoine,Francisco Javier Gallego,Sergii Skakun,Mykola Lavreniuk,Andrii Shelestov +5 more
TL;DR: Comparing pixel-based and parcel-based approaches to crop classification from multitemporal optical (Landsat-8) and synthetic-aperture radar (SAR) Sentinel-1 imagery finds that pixel- based overall classification accuracy can be increased from 85.32% to 89.40% when using parcel boundaries.