| 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 | 189 | 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 | 169 | 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 | 114 | 2017 |
| 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 | 113 | 2019 |
| 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 | 87 | 2007 |
| 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 | 83 | 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 | 69 | 2013 |
| 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 | 65 | 2020 |
| 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 | 64 | 2020 |
| 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 | 62 | 2019 |
| 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 | 57 | 2016 |
| 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 | 53 | 2020 |
| 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 | 50 | 2009 |
| 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 | 45 | 2018 |
| 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 | 41 | 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 | 40 | 2020 |
| 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 | 39 | 2016 |
| 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 | 37 | 2021 |
| 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 | 33 | 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 | 32 | 2013 |
Marcos Benedito SchimalskiProfessor das disciplinas de Topografia, Geodésia, Sensoriamento e GIS na Universidade do Estado de Santa Catarina - CAV/UDESCVerified email at udesc.br
