| Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data GV Laurin, N Puletti, W Hawthorne, V Liesenberg, P Corona, D Papale, ... Remote Sensing of Environment 176, 163-176, 2016 | 237 | 2016 |
| Optical and SAR sensor synergies for forest and land cover mapping in a tropical site in West Africa GV Laurin, V Liesenberg, Q Chen, L Guerriero, F Del Frate, A Bartolini, ... International Journal of Applied Earth Observation and Geoinformation 21, 7-16, 2013 | 194 | 2013 |
| Assessment of CNN-based methods for individual tree detection on images captured by RGB cameras attached to UAVs AA Santos, J Marcato Junior, MS Araújo, DR Di Martini, EC Tetila, ... Sensors 19 (16), 3595, 2019 | 178 | 2019 |
| Evaluating Sentinel-2 and Landsat-8 data to map sucessional forest stages in a subtropical forest in Southern Brazil C Sothe, CM Almeida, V Liesenberg, MB Schimalski Remote Sensing 9 (8), 838, 2017 | 164 | 2017 |
| Comparative performance of convolutional neural network, weighted and conventional support vector machine and random forest for classifying tree species using hyperspectral and … C Sothe, CM De Almeida, MB Schimalski, LEC La Rosa, JDB Castro, ... GIScience & Remote Sensing 57 (3), 369-394, 2020 | 149 | 2020 |
| Tree species classification in a highly diverse subtropical forest integrating UAV-based photogrammetric point cloud and hyperspectral data C Sothe, M Dalponte, CM Almeida, MB Schimalski, CL Lima, ... Remote Sensing 11 (11), 1338, 2019 | 136 | 2019 |
| Predicting canopy nitrogen content in citrus-trees using random forest algorithm associated to spectral vegetation indices from UAV-imagery L Prado Osco, AP Marques Ramos, D Roberto Pereira, ... Remote Sensing 11 (24), 2925, 2019 | 135 | 2019 |
| Applying fully convolutional architectures for semantic segmentation of a single tree species in urban environment on high resolution UAV optical imagery D Lobo Torres, R Queiroz Feitosa, P Nigri Happ, L Elena Cué La Rosa, ... Sensors 20 (2), 563, 2020 | 134 | 2020 |
| A CNN approach to simultaneously count plants and detect plantation-rows from UAV imagery LP Osco, MS de Arruda, DN Gonçalves, A Dias, J Batistoti, M de Souza, ... ISPRS Journal of Photogrammetry and Remote Sensing 174, 1-17, 2021 | 103 | 2021 |
| A machine learning framework to predict nutrient content in valencia-orange leaf hyperspectral measurements LP Osco, APM Ramos, MM Faita Pinheiro, ÉAS Moriya, NN Imai, ... Remote Sensing 12 (6), 906, 2020 | 96 | 2020 |
| Variations in reflectance with seasonality and viewing geometry: implications for classification of Brazilian savanna physiognomies with MISR/Terra data V Liesenberg, LS Galvão, FJ Ponzoni Remote Sensing of Environment 107 (1-2), 276-286, 2007 | 93 | 2007 |
| GIS-based modeling for selection of dam sites in the Kurdistan Region, Iraq AA Othman, AF Al-Maamar, DAMA Al-Manmi, V Liesenberg, SE Hasan, ... ISPRS International Journal of Geo-Information 9 (4), 244, 2020 | 76 | 2020 |
| Evaluating SAR polarization modes at L-band for forest classification purposes in Eastern Amazon, Brazil V Liesenberg, R Gloaguen International Journal of Applied Earth Observation and Geoinformation 21 …, 2013 | 76 | 2013 |
| A principal component approach for predicting the stem volume in Eucalyptus plantations in Brazil using airborne LiDAR data CA Silva, C Klauberg, AT Hudak, LA Vierling, V Liesenberg, ... Forestry: An International Journal of Forest Research 89 (4), 422-433, 2016 | 69 | 2016 |
| ATSS deep learning-based approach to detect apple fruits LJ Biffi, E Mitishita, V Liesenberg, AA Santos, DN Goncalves, NV Estrabis, ... Remote Sensing 13 (1), 54, 2020 | 64 | 2020 |
| Delineation of potential sites for rice cultivation through multi-criteria evaluation (MCE) using remote sensing and GIS SMH Raza, SA Mahmood, AA Khan, V Liesenberg International Journal of Plant Production 12, 1-11, 2018 | 62 | 2018 |
| Large scale multi-layer fuel load characterization in tropical savanna using GEDI spaceborne lidar data RV Leite, CA Silva, EN Broadbent, CH Do Amaral, V Liesenberg, ... Remote Sensing of Environment 268, 112764, 2022 | 54 | 2022 |
| Semantic segmentation of tree-canopy in urban environment with pixel-wise deep learning JAC Martins, K Nogueira, LP Osco, FDG Gomes, DEG Furuya, ... Remote Sensing 13 (16), 3054, 2021 | 54 | 2021 |
| Estimating pasture biomass and canopy height in Brazilian savanna using UAV photogrammetry J Batistoti, J Marcato Junior, L Ítavo, E Matsubara, E Gomes, B Oliveira, ... Remote Sensing 11 (20), 2447, 2019 | 53 | 2019 |
| Optical and SAR remote sensing synergism for mapping vegetation types in the endangered Cerrado/Amazon ecotone of Nova Mutum—Mato Grosso F de Souza Mendes, D Baron, G Gerold, V Liesenberg, S Erasmi Remote Sensing 11 (10), 1161, 2019 | 50 | 2019 |
Marcos Benedito SchimalskiProfessor das disciplinas de Topografia, Geodésia, Sensoriamento e GIS na Universidade do Estado de Santa Catarina - CAV/UDESC在 udesc.br 的电子邮件经过验证