| 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 | 156 | 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 | 148 | 2013 |
| 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 | 82 | 2017 |
| 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 | 79 | 2007 |
| 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 | 65 | 2019 |
| 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 | 64 | 2013 |
| 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 | 46 | 2019 |
| Possibilities of discriminating tropical secondary succession in Amazônia using hyperspectral and multiangular CHRIS/PROBA data LS Galvão, FJ Ponzoni, V Liesenberg, JR dos Santos International Journal of Applied Earth Observation and Geoinformation 11 (1 …, 2009 | 46 | 2009 |
| 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 | 45 | 2016 |
| 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 Cue La Rosa, ... Sensors 20 (2), 563, 2020 | 38 | 2020 |
| Análise da dinâmica sazonal e separabilidade espectral de algumas fitofisionomias do Cerrado com índices de vegetação dos sensores MODIS/TERRA e AQUA V Liesenberg, FJ Ponzoni, LS Galvão Revista Árvore 31, 295-305, 2007 | 38 | 2007 |
| Object-oriented and pixel-based classification approaches to classify tropical successional stages using airborne high–spatial resolution images GA Piazza, AC Vibrans, V Liesenberg, JC Refosco GIScience & Remote Sensing 53 (2), 206-226, 2016 | 35 | 2016 |
| 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 | 32 | 2019 |
| Retrieval of forest attributes in complex successional forests of Central Indonesia: Modeling and estimation of bitemporal data A Wijaya, V Liesenberg, R Gloaguen Forest Ecology and Management 259 (12), 2315-2326, 2010 | 32 | 2010 |
| Multi-temporal airborne LiDAR-survey and field measurements of tropical peat swamp forest to monitor changes HDV Boehm, V Liesenberg, SH Limin IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2013 | 28 | 2013 |
| 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 | 27 | 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), 1-11, 2018 | 25 | 2018 |
| 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 | 24 | 2020 |
| 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 | 17 | 2019 |
| Análise comparativa de classificadores digitais em imagens do Landsat-8 aplicados ao mapeamento temático DFT Garofalo, CG Messias, V Liesenberg, ÉL Bolfe, MC Ferreira Pesquisa Agropecuária Brasileira 50, 593-604, 2015 | 17 | 2015 |
Marcos Benedito SchimalskiProfessor das disciplinas de Topografia, Geodésia, Sensoriamento e GIS na Universidade do Estado de Santa Catarina - CAV/UDESCE-mail confirmado em udesc.br
