| ESA WorldCover 10 m 2021 v200 D Zanaga, R Van De Kerchove, D Daems, W De Keersmaecker, ... Zenodo, 2022 | 705 | 2022 |
| Copernicus global land cover layers—collection 2 M Buchhorn, M Lesiv, NE Tsendbazar, M Herold, L Bertels, B Smets Remote Sensing 12 (6), 1044, 2020 | 644 | 2020 |
| Copernicus global land service: land cover 100 m: collection 3: epoch 2019: Globe M Buchhorn, B Smets, L Bertels, B De Roo, M Lesiv, NE Tsendbazar, ... URL: https://zenodo. org/record/3939050 (дата обращения: 30.12. 2021), 2020 | 281 | 2020 |
| Areas of global importance for conserving terrestrial biodiversity, carbon and water M Jung, A Arnell, X De Lamo, S García-Rangel, M Lewis, J Mark, ... Nature Ecology & Evolution 5 (11), 1499-1509, 2021 | 273 | 2021 |
| Copernicus global land service: land cover 100m: collection 3 Epoch 2015, Globe M Buchhorn, B Smets, L Bertels, B De Roo, M Lesiv, NE Tsendbazar, ... Version V3. 0.1)[Data set], 2020 | 234 | 2020 |
| A global dataset of crowdsourced land cover and land use reference data S Fritz, L See, C Perger, I McCallum, C Schill, D Schepaschenko, ... Scientific data 4 (1), 1-8, 2017 | 160 | 2017 |
| Estimating the global distribution of field size using crowdsourcing M Lesiv, JC Laso Bayas, L See, M Duerauer, D Dahlia, N Durando, ... Global change biology 25 (1), 174-186, 2019 | 159 | 2019 |
| A global map of terrestrial habitat types M Jung, PR Dahal, SHM Butchart, PF Donald, X De Lamo, M Lesiv, ... Scientific data 7 (1), 256, 2020 | 147 | 2020 |
| Development of a global hybrid forest mask through the synergy of remote sensing, crowdsourcing and FAO statistics D Schepaschenko, L See, M Lesiv, I McCallum, S Fritz, C Salk, ... Remote Sensing of Environment 162, 208-220, 2015 | 146 | 2015 |
| Spatial distribution of arable and abandoned land across former Soviet Union countries M Lesiv, D Schepaschenko, E Moltchanova, R Bun, M Dürauer, ... Scientific data 5 (1), 1-12, 2018 | 136 | 2018 |
| Copernicus global land service: land cover 100m: epoch 2015: globe M Buchhorn, B Smets, L Bertels, M Lesiv, NE Tsendbazar, M Herold, ... Version V2. 0.2 10, 2019 | 120 | 2019 |
| Building a hybrid land cover map with crowdsourcing and geographically weighted regression L See, D Schepaschenko, M Lesiv, I McCallum, S Fritz, A Comber, ... ISPRS Journal of Photogrammetry and Remote Sensing 103, 48-56, 2015 | 118 | 2015 |
| Errors and uncertainties in a gridded carbon dioxide emissions inventory T Oda, R Bun, V Kinakh, P Topylko, M Halushchak, G Marland, T Lauvaux, ... Mitigation and Adaptation Strategies for Global Change 24, 1007-1050, 2019 | 101 | 2019 |
| Copernicus global land service: Land cover 100m: Version 3 Globe 2015-2019: Product user manual M Buchhorn, B Smets, L Bertels, B De Roo, M Lesiv, NE Tsendbazar, L Li, ... Zenodo, 2020 | 95 | 2020 |
| Russian forest sequesters substantially more carbon than previously reported D Schepaschenko, E Moltchanova, S Fedorov, V Karminov, P Ontikov, ... Scientific Reports 11 (1), 12825, 2021 | 94 | 2021 |
| Characterizing the spatial and temporal availability of very high resolution satellite imagery in google earth and microsoft bing maps as a source of reference data M Lesiv, L See, JC Laso Bayas, T Sturn, D Schepaschenko, M Karner, ... Land 7 (4), 118, 2018 | 84 | 2018 |
| ESA WorldCover 10 m 2020 v100. 2021 D Zanaga, R Van De Kerchove, W De Keersmaecker, N Souverijns, ... | 83 | 2021 |
| Towards operational validation of annual global land cover maps N Tsendbazar, M Herold, L Li, A Tarko, S De Bruin, D Masiliunas, M Lesiv, ... Remote Sensing of Environment 266, 112686, 2021 | 80 | 2021 |
| Developing and applying a multi-purpose land cover validation dataset for Africa NE Tsendbazar, M Herold, S De Bruin, M Lesiv, S Fritz, ... Remote Sensing of Environment 219, 298-309, 2018 | 69 | 2018 |
| Global forest management data for 2015 at a 100 m resolution M Lesiv, D Schepaschenko, M Buchhorn, L See, M Dürauer, I Georgieva, ... Scientific Data 9 (1), 199, 2022 | 67 | 2022 |
Steffen FritzIIASAEmail verificata su iiasa.ac.at