| UAV for mapping shrubland vegetation: Does fusion of spectral and vertical information derived from a single sensor increase the classification accuracy? J Prošek, P Šímová International Journal of Applied Earth Observation and Geoinformation 75 …, 2019 | 87 | 2019 |
| The potential of Unmanned Aerial Systems: A tool towards precision classification of hard-to-distinguish vegetation types? J Komárek, T Klouček, J Prošek International journal of applied earth observation and geoinformation 71, 9-19, 2018 | 83 | 2018 |
| Vegetation structure derived from airborne laser scanning to assess species distribution and habitat suitability: The way forward V Moudrý, AF Cord, L Gábor, GV Laurin, V Barták, K Gdulová, M Malavasi, ... Diversity and Distributions 29 (1), 39-50, 2023 | 52 | 2023 |
| Effects of urbanization on taxonomic, functional and phylogenetic avian diversity in Europe F Morelli, Y Benedetti, JD Ibáñez-Álamo, P Tryjanowski, J Jokimäki, ... Science of the Total Environment 795, 148874, 2021 | 47 | 2021 |
| Comparison of a commercial and home-assembled fixed-wing UAV for terrain mapping of a post-mining site under leaf-off conditions V Moudrý, R Urban, M Štroner, J Komárek, J Brouček, J Prošek International journal of remote sensing 40 (2), 555-572, 2019 | 43 | 2019 |
| Applicability of Data Acquisition Characteristics to the Identification of Local Artefacts in Global Digital Elevation Models: Comparison of the Copernicus and TanDEM-X DEMs J Marešová, K Gdulová, P Pracná, D Moravec, L Gábor, J Prošek, ... Remote Sensing 13 (19), 3931, 2021 | 35 | 2021 |
| Temperature buffering in temperate forests: Comparing microclimate models based on ground measurements with active and passive remote sensing V Kašpar, L Hederová, M Macek, J Müllerová, J Prošek, P Surový, J Wild, ... Remote Sensing of Environment 263, 112522, 2021 | 34 | 2021 |
| Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems AM Cunliffe, K Anderson, F Boschetti, RE Brazier, HA Graham, ... Remote Sensing in Ecology and Conservation 8 (1), 57-71, 2022 | 29 | 2022 |
| Integration of hyperspectral and LiDAR data for mapping small water bodies J Prošek, K Gdulová, V Barták, J Vojar, M Solský, D Rocchini, V Moudrý International Journal of Applied Earth Observation and Geoinformation 92, 102181, 2020 | 27 | 2020 |
| Effects of environmental conditions on ICESat-2 terrain and canopy heights retrievals in Central European mountains V Moudrý, K Gdulová, L Gábor, E Šárovcová, V Barták, F Leroy, ... Remote Sensing of Environment 279, 113112, 2022 | 26 | 2022 |
| Scale mismatches between predictor and response variables in species distribution modelling: A review of practices for appropriate grain selection V Moudrý, P Keil, L Gábor, V Lecours, A Zarzo-Arias, V Barták, ... Progress in Physical Geography: Earth and Environment 47 (3), 467-482, 2023 | 21 | 2023 |
| Digital elevation models as predictors of yield: comparison of an UAV and other elevation data sources D Moravec, J Komárek, J Kumhálová, M Kroulík, J Prošek, P Klápště Agron Res 15 (1), 249-55, 2017 | 16 | 2017 |
| Effects of light and noise pollution on avian communities of European cities are correlated with the species’ diet F Morelli, P Tryjanowski, JD Ibáñez-Álamo, M Díaz, J Suhonen, ... Scientific Reports 13 (1), 4361, 2023 | 8 | 2023 |
| Drone-derived canopy height predicts biomass across non-forest ecosystems globally AM Cunliffe, K Anderson, F Boschetti, RE Brazier, HA Graham, ... bioRxiv, 2020.07. 16.206011, 2020 | 4 | 2020 |
| Optimising Species Distribution Models: Sample size, positional error, and sampling bias matter V Moudrý, M Bazzichetto, R Remelgado, R Devillers, J Lenoir, RG Mateo, ... EcoEvoRxiv, 2023 | 3 | 2023 |
| Optimising occurrence data in species distribution models: sample size, positional uncertainty, and sampling bias matter V Moudrý, M Bazzichetto, R Remelgado, R Devillers, J Lenoir, RG Mateo, ... Ecography, e07294, 2024 | | 2024 |
