Busca avançada
Ano de início
Entree

Characterizing and predicting biomass production in sugarcane and eucalyptus plantations in Brazil

Resumo

For major emerging countries with significant land resources such as Brazil, the Agriculture, Forestry and Land Use (AFOLU) sector is one of the major sources of greenhouse gas (GHG) emissions. At the same time, this sector offers a large potential for climate change mitigation through best management practices. São Paulo state is the main producer of both eucalyptus and sugarcane in Brazil, and there is potential for expansion in the area managed under both crops. These land uses can have a large impact on the regional carbon balance, both though carbon fixation in the vegetation and soils and though offsetting fossil fuel emissions by the production and consumption of biofuels. Process-based models, calibrated and validated previously, and applied spatially could help quantifying the fluxes and stocks of carbon at the field level, with different time scales (from years to decades) and spatial scales (from stands to regions). The main objective of this project is to take advantage of satellite and field data collected in the past decade; state-of-the-art process-based models; and computational tools that allow processing large amounts of data to assess the carbon dynamics of eucalyptus and sugarcane in São Paulo state. A bottom-up approach will be used, by parameterizing and testing process models based on field measurements, and then upscaling to São Paulo State. Images from Landsat will CBERS, Terra and Aqua satellites will be registered, radiometrically corrected and organized into a data set covering the 2000-2015 period in São Paulo State, with the associated metadata. Soils data will be compiled from published soil surveys, and meteorological variables will be collected from weather stations and global models. Different vegetation indices time-series will be produced, like the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). A time-series classification method will be used, in which the algorithm will use the seasonal and/or pluriannual vegetation indices profiles to classify the vegetation through time series pattern analysis. Estimation of vegetation structural parameters and in particular Leaf Area Index (LAI) and/or the fraction of absorbed photosynthetically active radiation (FAPAR) will also be derived from remote sensing data. Data collected over the last decade by EMBRAPA, CIRAD and CTBE on Eucalyptus plantations and sugarcane fields will be used to calibrate and validate models such as the G'Day process-based model. Both the remote sensing correction and processing, the classification procedure (calibration and application), process-based modelling at the site scale and the upscaling procedures will require a large amount of calculations and data processing. Therefore, novel computer science tools and techniques will be used in this project, including cloud-based computing, machine learning and visualization interfaces for spatial data. The expected outcome of accurate predictions of carbon fluxes and dynamics with satellite-data constrained crop models is in high demand from the scientific community, policy makers, and the forestry and agricultural sectors. Additionally, the science developed in this project will be useful as input to applications in other crops and regions. (AU)

Matéria(s) publicada(s) na Agência FAPESP sobre o auxílio:
Matéria(s) publicada(s) em Outras Mídias (0 total):
Mais itensMenos itens
VEICULO: TITULO (DATA)
VEICULO: TITULO (DATA)

Publicações científicas (53)
(Referências obtidas automaticamente do Web of Science e do SciELO, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores)
DOS SANTOS LUCIANO, ANA CLAUDIA; ARAUJO PICOLI, MICHELLE CRISTINA; ROCHA, JANSLE VIEIRA; DUFT, DANIEL GARBELLINI; CAMARGO LAMPARELLI, RUBENS AUGUSTO; LIMA VERDE LEAL, MANOEL REGIS; LE MAIRE, GUERRIC. A generalized space-time OBIA classification scheme to map sugarcane areas at regional scale, using Landsat images time-series and the random forest algorithm. International Journal of Applied Earth Observation and Geoinformation, v. 80, p. 127-136, . (14/50715-9)
DIAS, DANIELLE; PINTO, ALLAN; DIAS, ULISSES; LAMPARELLI, RUBENS; LE MAIRE, GUERRIC; TORRES, RICARDO DA S.. A Multirepresentational Fusion of Time Series for Pixelwise Classification. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, v. 13, p. 4399-4409, . (19/16253-1, 16/50250-1, 14/50715-9, 17/20945-0, 14/12236-1, 13/50155-0, 15/24494-8)
DOS SANTOS LUCIANO, ANA CLAUDIA; ARAUJO PICOLI, MICHELLE CRISTINA; DUFT, DANIEL GARBELLINI; ROCHA, JANSLE VIEIRA; LIMA VERDE LEAL, MANOEL REGIS; LE MAIRE, GUERRIC. Empirical model for forecasting sugarcane yield on a local scale in Brazil using Landsat imagery and random forest algorithm. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 184, . (14/50715-9)
GOMES, LUIZ; TORRES, RICARDO DA SILVA; CORTES, MARIO LUCIO. BERT- and TF-IDF-based feature extraction for long-lived bug prediction in FLOSS: A comparative study. INFORMATION AND SOFTWARE TECHNOLOGY, v. 160, p. 12-pg., . (13/50155-0, 14/12236-1, 16/50250-1, 15/24494-8, 14/50715-9, 17/20945-0)
SILVA, EWERTON; TORRES, RICARDO S.; ALBERTON, BRUNA; MORELLATO, LEONOR PATRICIA C.; SILVA, THIAGO S. F.. A Change-Driven Image Foveation Approach for Tracking Plant Phenology. REMOTE SENSING, v. 12, n. 9, . (14/50715-9, 14/00215-0, 16/50250-1, 17/20945-0, 14/12236-1, 13/50155-0, 15/24494-8, 16/01413-5)
SILVA, EWERTON; TORRES, RICARDO DA S.; PINTO, ALLAN; LI, LIN TZY; VIANNA, JOSE EDUARDO S.; AZEVEDO, RODOLFO; GOLDENSTEIN, SIOME. Application-Oriented Retinal Image Models for Computer Vision. SENSORS, v. 20, n. 13, . (14/12236-1, 13/50155-0, 16/50250-1, 14/50715-9, 17/20945-0)
TAVARES, EDUARDO A.; TORRES, RICARDO DA S.; DOS SANTOS, JEFERSSON A.; IEEE. EVALUATING DEEP CONTEXTUAL DESCRIPTION OF SUPERPIXELS FOR DETECTION IN AERIAL IMAGES. 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), v. N/A, p. 4-pg., . (13/50155-0, 14/12236-1, 16/50250-1, 15/24494-8, 14/50715-9, 17/20945-0)
HERNANDEZ ALBARRACIN, JUAN F.; FERREIRA, EDEMIR, JR.; DOS SANTOS, JEFERSSON A.; TORRES, RICARDO DA S.; IEEE. FUSION OF GENETIC-PROGRAMMING-BASED INDICES IN HYPERSPECTRAL IMAGE CLASSIFICATION TASKS. 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), v. N/A, p. 4-pg., . (13/50169-1, 13/50155-0, 14/12236-1, 14/50715-9)
DOS SANTOS LUCIANO, ANA CLAUDIA; ARAUJO PICOLI, MICHELLE CRISTINA; ROCHA, JANSLE VIEIRA; JUNQUEIRA FRANCO, HENRIQUE COUTINHO; SANCHES, GUILHERME MARTINELI; LIMA VERDE LEAL, MANOEL REGIS; LE MAIRE, GUERRIC. Generalized space-time classifiers for monitoring sugarcane areas in Brazil. REMOTE SENSING OF ENVIRONMENT, v. 215, p. 438-451, . (14/50715-9)
NOGUEIRA, KEILLER; FADEL, SAMUEL G.; DOURADO, ICARO C.; WERNECK, RAFAEL DE O.; MUNOZ, V, JAVIER A.; PENATTI, OTAVIO A. B.; CALUMBY, RODRIGO T.; LI, LIN TZY; DOS SANTOS, JEFERSSON A.; TORRES, RICARDO DA S.. Exploiting ConvNet Diversity for Flooding Identification. IEEE Geoscience and Remote Sensing Letters, v. 15, n. 9, p. 1446-1450, . (14/50715-9, 16/18429-1, 13/50155-0, 15/24494-8, 14/12236-1, 13/50169-1)
MARIANO, GREICE C.; STAGGEMEIER, VANESSA G.; CERDEIRA MORELLATO, LEONOR PATRICIA; TORRES, RICARDO DA S.. Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis. ECOLOGICAL INFORMATICS, v. 46, p. 19-35, . (14/50715-9, 10/51307-0, 17/20945-0, 16/50250-1, 13/50155-0, 07/59779-6, 15/24494-8, 14/12236-1, 09/18438-7, 13/50169-1)
ATTIA, AHMED; NOUVELLON, YANN; CUADRA, SANTIAGO; CABRAL, OSVALDO; LACLAU, JEAN-PAUL; GUILLEMOT, JOANNES; CAMPOE, OTAVIO; STAPE, JOSE-LUIZ; GALDOS, MARCELO; LAMPARELLI, RUBENS; et al. Modelling carbon and water balance of Eucalyptus plantations at regional scale: Effect of climate, soil and genotypes. FOREST ECOLOGY AND MANAGEMENT, v. 449, . (14/50715-9, 17/00886-0, 12/06933-6)
VEZY, REMI; CHRISTINA, MATHIAS; ROUPSARD, OLIVIER; NOUVELLON, YANN; DUURSMA, REMKO; MEDLYN, BELINDA; SOMA, MAXIME; CHARBONNIER, FABIEN; BLITZ-FRAYRET, CELINE; STAPE, JOSE-LUIZ; et al. Measuring and modelling energy partitioning in canopies of varying complexity using MAESPA model. Agricultural and Forest Meteorology, v. 253, p. 203-217, . (14/50715-9)
UCHOA MAIA RODRIGUES, DANIELE C.; MOURA, FELIPE A.; CUNHA, SERGIO AUGUSTO; TORRES, RICARDO DA S.. Graph visual rhythms in temporal network analyses. GRAPHICAL MODELS, v. 103, . (14/50715-9, 16/50250-1, 13/50169-1, 14/12236-1, 18/19007-9, 17/20945-0, 13/50155-0, 15/24494-8)
GUEVARA, JUDY C.; TORRES, RICARDO DA S.; DA FONSECA, NELSON L. S.. On the classification of fog computing applications: A machine learning perspective. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, v. 159, . (14/50715-9, 16/50250-1, 17/20945-0, 14/12236-1, 13/50169-1, 13/50155-0, 15/24494-8)
MUNOZ, JAVIER VARGAS; GONCALVES, MARCOS A.; DIAS, ZANONI; TORRES, RICARDO DA S.. Hierarchical Clustering-Based Graphs for Large Scale Approximate Nearest Neighbor Search. PATTERN RECOGNITION, v. 96, . (14/50715-9, 16/50250-1, 17/16246-0, 17/20945-0, 14/12236-1, 13/50169-1, 15/11937-9, 17/12646-3, 13/50155-0, 15/24494-8)
WERNECK, RAFAEL DE OLIVEIRA; RAVEAUX, ROMAIN; TABBONE, SALVATORE; TORRES, RICARDO DA SILVA. Learning cost function for graph classification with open-set methods. PATTERN RECOGNITION LETTERS, v. 128, p. 8-15, . (14/50715-9, 16/18429-1, 17/20945-0, 13/50155-0, 17/16453-5, 15/24494-8, 14/12236-1, 13/50169-1)
WALDNER, FRANCOIS; BELLEMANS, NICOLAS; HOCHMAN, ZVI; NEWBY, TERENCE; DE ABELLEYRA, DIEGO; VERON, SANTIAGO R.; BARTALEV, SERGEY; LAVRENIUK, MYKOLA; KUSSUL, NATALIIA; LE MAIRE, GUERRIC; et al. Roadside collection of training data for cropland mapping is viable when environmental and management gradients are surveyed. International Journal of Applied Earth Observation and Geoinformation, v. 80, p. 82-93, . (14/50715-9)
PISANI, FLAVIA; PASCOTTI VALEM, LUCAS; GUIMARAES PEDRONETTE, DANIEL CARLOS; DA S. TORRES, RICARDO; BORIN, EDSON; BRETERNITZ, MAURICIO. A unified model for accelerating unsupervised iterative re-ranking algorithms. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, v. 32, n. 14, . (14/50715-9, 13/50169-1, 14/12236-1, 13/08645-0, 13/50155-0, 15/24494-8)
ESMAEL, AGNALDO APARECIDO; DOS SANTOS, JEFERSSON ALEX; TORRES, RICARDO DA SILVA. On the ensemble of multiscale object-based classifiers for aerial images: a comparative study. MULTIMEDIA TOOLS AND APPLICATIONS, v. 77, n. 19, p. 24565-24592, . (14/50715-9, 16/50250-1, 13/50169-1, 14/12236-1, 17/20945-0, 13/50155-0, 15/24494-8)
JOLIVOT, AUDREY; LEBOURGEOIS, VALENTINE; LEROUX, LOUISE; AMELINE, MAEL; ANDRIAMANGA, VALERIE; BELLON, BEATRIZ; CASTETS, MATHIEU; CRESPIN-BOUCAUD, ARTHUR; DEFOURNY, PIERRE; DIAZ, SANTIANA; et al. Harmonized in situ datasets for agricultural land use mapping and monitoring in tropical countries. EARTH SYSTEM SCIENCE DATA, v. 13, n. 12, p. 5951-5967, . (14/50715-9)
VARGAS MUNOZ, JAVIER A.; DIAS, ZANONI; TORRES, RICARDO DA SILVA. A genetic programming approach for searching on nearest neighbors graphs. MULTIMEDIA TOOLS AND APPLICATIONS, v. 81, n. 16, p. 24-pg., . (14/12236-1, 17/20945-0, 13/50155-0, 13/50169-1, 17/12646-3, 15/11937-9, 16/50250-1, 15/24494-8, 17/16246-0, 14/50715-9)
GUIMARAES PEDRONETTE, DANIEL CARLOS; VALEM, LUCAS PASCOTTI; ALMEIDA, JURANDY; TONES, RICARDO DA S.. Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking. IEEE Transactions on Image Processing, v. 28, n. 12, p. 5824-5838, . (14/50715-9, 16/50250-1, 17/25908-6, 17/20945-0, 14/12236-1, 16/06441-7, 18/15597-6, 13/50155-0, 17/02091-4, 15/24494-8)
LE MAIRE, GUERRIC; GUILLEMOT, JOANNES; CAMPOE, OTAVIO C.; STAPE, JOSE-LUIZ; LACLAU, JEAN-PAUL; NOUVELLON, YANN. Light absorption, light use efficiency and productivity of 16 contrasted genotypes of several Eucalyptus species along a 6-year rotation in Brazil. FOREST ECOLOGY AND MANAGEMENT, v. 449, . (14/50715-9)
FERREIRA GOMES, LUIZ ALBERTO; TORRES, RICARDO DA SILVA; CORTES, MARIO LTICIO. Bug report severity level prediction in open source software: A survey and research opportunities. INFORMATION AND SOFTWARE TECHNOLOGY, v. 115, p. 58-78, . (14/50715-9, 16/50250-1, 13/50169-1, 14/12236-1, 17/20945-0, 13/50155-0, 15/24494-8)
GUIMARAES PEDRONETTE, DANIEL CARLOS; VALEM, LUCAS PASCOTTI; TORRES, RICARDO DA S.. A BFS-Tree of ranking references for unsupervised manifold learning. PATTERN RECOGNITION, v. 111, . (16/50250-1, 15/24494-8, 13/50155-0, 18/15597-6, 13/50169-1, 17/20945-0, 14/12236-1, 17/25908-6, 14/50715-9)
CABRAL, OSVALDO M. R.; FREITAS, HELBER CUSTODIO; CUADRA, SANTIAGO VIANA; DE ANDRADE, CRISTIANO ALBERTO; RAMOS, NILZA PATRICIA; GRUTZMACHER, PRISCILA; GALDOS, MARCELO; CONTADOR PACKER, ANA PAULA; DA ROCHA, HUMBERTO RIBEIRO; ROSSI, PAULO. The sustainability of a sugarcane plantation in Brazil assessed by the eddy covariance fluxes of greenhouse gases. Agricultural and Forest Meteorology, v. 282, . (14/24452-0, 14/50715-9)
WALDNER, FRANCOIS; BELLEMANS, NICOLAS; HOCHMAN, ZVI; NEWBY, TERENCE; DE ABELLEYRA, DIEGO; VERON, SANTIAGO R.; BARTALEV, SERGEY; LAVRENIUK, MYKOLA; KUSSUL, NATALIIA; LE MAIRE, GUERRIC; et al. Roadside collection of training data for cropland mapping is viable when environmental and management gradients are surveyed. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, v. 80, p. 12-pg., . (14/50715-9)
DOURADO, ICARO CAVALCANTE; TABBONE, SALVATORE; TORRES, RICARDO DA SILVA; CONTE, D; RAMEL, JY; FOGGIA, P. Event Prediction Based on Unsupervised Graph-Based Rank-Fusion Models. GRAPH-BASED REPRESENTATIONS IN PATTERN RECOGNITION, GBRPR 2019, v. 11510, p. 11-pg., . (17/20945-0, 14/50715-9, 14/12236-1, 16/50250-1, 13/50155-0, 15/24494-8)
OLIVEIRA, ALBERTO; OAKLEY, ERIC; TORRES, RICARDO DA SILVA; ROCHA, ANDERSON. Relevance prediction in similarity-search systems using extreme value theory. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, v. 60, p. 236-249, . (14/50715-9, 16/50250-1, 17/20945-0, 14/12236-1, 17/12646-3, 13/50155-0, 15/24494-8)
MELO DE OLIVEIRA SANTOS, CECILIA LIRA; CAMARGO LAMPARELLI, RUBENS AUGUSTO; DANTAS ARAUJO FIGUEIREDO, GLEYCE KELLY; DUPUY, STEPHANE; BOURY, JULIE; DOS SANTOS LUCIANO, ANA CLAUDIA; TORRES, RICARDO DA SILVA; LE MAIRE, GUERRIC. Classification of Crops, Pastures, and Tree Plantations along the Season with Multi-Sensor Image Time Series in a Subtropical Agricultural Region. REMOTE SENSING, v. 11, n. 3, . (15/24494-8, 14/50715-9, 14/12236-1, 13/50155-0)
CORDOVA NEIRA, MANUEL ALBERTO; MENDES JUNIOR, PEDRO RIBEIRO; ROCHA, ANDERSON; TORRES, RICARDO DA SILVA. Data-Fusion Techniques for Open-Set Recognition Problems. IEEE ACCESS, v. 6, p. 21242-U24, . (14/50715-9, 17/20945-0, 16/50250-1, 13/50155-0, 15/24494-8, 14/12236-1, 17/12646-3, 13/50169-1)
ALMEIDA, ALEXANDRE E.; TORRES, RICARDO DA S.. Remote Sensing Image Classification Using Genetic-Programming-Based Time Series Similarity Functions. IEEE Geoscience and Remote Sensing Letters, v. 14, n. 9, p. 1499-1503, . (14/50715-9, 13/50155-0, 14/12236-1, 15/02105-0, 13/50169-1)
MENINI, NATHALIA; ALMEIDA, ALEXANDRE E.; LAMPARELLI, RUBENS; LE MAIRE, GUERRIC; DOS SANTOS, JEFERSSON A.; PEDRINI, HELIO; HIROTA, MARINA; TORRES, RICARDO DA S.. A Soft Computing Framework for Image Classification Based on Recurrence Plots. IEEE Geoscience and Remote Sensing Letters, v. 16, n. 2, p. 320-324, . (14/50715-9, 16/26170-8, 18/06918-3, 13/50155-0, 14/12236-1, 15/02105-0, 17/12646-3, 13/50169-1)
FERREIRA GOMES, LUIZ ALBERTO; TORRES, RICARDO DA SILVA; CORTES, MARIO LUCIO. On the prediction of long-lived bugs: An analysis and comparative study using FLOSS projects. INFORMATION AND SOFTWARE TECHNOLOGY, v. 132, . (14/50715-9, 16/50250-1, 14/12236-1, 15/24494-8, 17/20945-0, 13/50155-0)
CAMPANA, JOSE L. FLORES; PINTO, ALLAN; CORDOVA NEIRA, MANUEL ALBERTO; LORGUS DECKER, LUIS GUSTAVO; SANTOS, ANDREZA; CONCEICAO, JHONATAS S.; TORRES, RICARDO DA SILVA. On the Fusion of Text Detection Results: A Genetic Programming Approach. IEEE ACCESS, v. 8, p. 81257-81270, . (19/16253-1, 16/50250-1, 14/50715-9, 17/20945-0, 14/12236-1, 13/50155-0, 15/24494-8)
DIAS, DANIELLE; DIAS, ULISSES; MENINI, NATHALIA; LAMPARELLI, RUBENS; LE MAIRE, GUERRIC; TORRES, RICARDO DA S.. Image-Based Time Series Representations for Pixelwise Eucalyptus Region Classification: A Comparative Study. IEEE Geoscience and Remote Sensing Letters, v. 17, n. 8, p. 1450-1454, . (14/50715-9, 17/20945-0, 16/50250-1, 13/50155-0, 15/24494-8, 14/12236-1)
FADEL, SAMUEL G.; TORRES, RICARDO DA S.. Neural relational inference for disaster multimedia retrieval. MULTIMEDIA TOOLS AND APPLICATIONS, v. 79, n. 35-36, . (14/50715-9, 16/50250-1, 17/24005-2, 17/20945-0, 14/12236-1, 13/50169-1, 13/50155-0, 15/24494-8)
ALBARRACIN, JUAN F. H.; OLIVEIRA, RAFAEL S.; HIROTA, MARINA; DOS SANTOS, JEFERSSON A.; TORRES, RICARDO DA S.. A Soft Computing Approach for Selecting and Combining Spectral Bands. REMOTE SENSING, v. 12, n. 14, . (15/02105-0, 14/50715-9, 13/50169-1, 16/08085-3, 14/12236-1, 17/12646-3, 16/26170-8, 13/50155-0, 18/06918-3)
COLMANETTI, MICHEL ANDERSON ALMEIDA; CUADRA, SANTIAGO VIANNA; LAMPARELLI, RUBENS AUGUSTO CAMARGO; JUNIOR, JAIR BORTOLUCCI; CABRAL, OSVALDO MACHADO RODRIGUES; CAMPOE, OTAVIO CAMARGO; VICTORIA, DANIEL DE CASTRO; BARIONI, LUIS GUSTAVO; GALDOS, MARCELO VALADARES; FIGUEIREDO, GLEYCE KELLY DANTAS ARAUJO; et al. Implementation and calibration of short-rotation eucalypt plantation module within the ECOSMOS land surface model. Agricultural and Forest Meteorology, v. 323, p. 15-pg., . (18/21103-6, 14/50715-9)
CIRNE, MARCOS; ANDALO, FERNANDA; DIAS, RAFAEL; RESEK, THIAGO; BERTOCCO, GABRIEL; TORRES, RICARDO DA S.; ROCHA, ANDERSON; IEEE. DEEP FACE VERIFICATION FOR SPHERICAL IMAGES. 2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), v. N/A, p. 5-pg., . (13/50155-0, 14/12236-1, 17/12646-3, 16/50250-1, 15/24494-8, 14/50715-9, 17/20945-0)
WERNECK, RAFAEL DE O.; RAVEAUX, ROMAIN; TABBONE, SALVATORE; TORRES, RICARDO DA S.; BAI, X; HANCOCK, ER; HO, TK; WILSON, RC; BIGGIO, B; ROBLESKELLY, A. Learning Cost Functions for Graph Matching. STRUCTURAL, SYNTACTIC, AND STATISTICAL PATTERN RECOGNITION, S+SSPR 2018, v. 11004, p. 10-pg., . (14/50715-9, 17/20945-0, 14/12236-1, 16/18429-1, 16/50250-1, 13/50169-1, 13/50155-0, 15/24494-8)
DOS SANTOS LUCIANO, ANA CLAUDIA; GAMA CAMPAGNUCI, BRUNA CRISTINA; LE MAIRE, GUERRIC. Mapping 33 years of sugarcane evolution in Sa similar to o Paulo state, Brazil, using landsat imagery and generalized space-time classifiers. REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, v. 26, p. 12-pg., . (14/50715-9)
DIAS, DANIELLE; DIAS, ULISSES; MENINI, NATHALIA; LAMPARELLI, RUBENS; LE MAIRE, GUERRIC; TORRES, RICARDO; IEEE. PIXELWISE REMOTE SENSING IMAGE CLASSIFICATION BASED ON RECURRENCE PLOT DEEP FEATURES. 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), v. N/A, p. 4-pg., . (13/50155-0, 14/12236-1, 16/50250-1, 15/24494-8, 14/50715-9, 17/20945-0)
SANTOS, ELISANGELA SILVA; ALBERTON, BRUNA; MORELLATO, LEONOR PATRICIA; TORRES, RICARDO DA SILVA; IEEE. PIXELWISE TIME SERIES RETRIEVAL IN PHENOLOGICAL STUDIES. 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), v. N/A, p. 4-pg., . (13/50169-1, 13/50155-0, 14/12236-1, 16/50250-1, 15/24494-8, 14/50715-9, 17/20945-0)
DOS SANTOS LUCIANO, ANA CLAUDIA; ARAUJO PICOLI, MICHELLE CRISTINA; ROCHA, JANSLE VIEIRA; DUFT, DANIEL GARBELLINI; CAMARGO LAMPARELLI, RUBENS AUGUSTO; LIMA VERDE LEAL, MANOEL REGIS; LE MAIRE, GUERRIC. A generalized space-time OBIA classification scheme to map sugarcane areas at regional scale, using Landsat images time-series and the random forest algorithm. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, v. 80, p. 10-pg., . (14/50715-9)
PEREIRA, ERICO M.; TORRES, RICARDO DA S.; DOS SANTOS, JEFERSSON A.. A genetic algorithm approach for image representation learning through color quantization. MULTIMEDIA TOOLS AND APPLICATIONS, v. 80, n. 10, p. 15315-15350, . (13/50169-1, 16/50250-1, 15/24494-8, 17/20945-0, 13/50155-0, 14/50715-9, 14/12236-1)
WERNECK, RAFAEL DE O.; DOURADO, ICARO C.; FADEL, SAMUEL G.; TABBONE, SALVATORE; TORRES, RICARDO DA S.; IEEE. GRAPH-BASED EARLY-FUSION FOR FLOOD DETECTION. 2018 25TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), v. N/A, p. 5-pg., . (13/50169-1, 13/50155-0, 14/12236-1, 16/18429-1, 14/50715-9, 17/16453-5, 17/24005-2)
SANTANA, TIAGO M. H. C.; TORRES, RICARDO DA S.; DOS SANTOS, JEFERSSON A.; IEEE. SUPERPIXEL CONTEXT DESCRIPTION BASED ON VISUAL WORDS CO-OCCURRENCE MATRIX. IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, v. N/A, p. 4-pg., . (13/50169-1, 13/50155-0, 14/12236-1, 16/50250-1, 15/24494-8, 14/50715-9, 17/20945-0)
ALMEIDA, ALEXANDRE E.; MENINI, NATHALIA; VERBESSELT, JAN; TORRES, RICARDO DA S.; IEEE. BFAST EXPLORER: AN EFFECTIVE TOOL FOR TIME SERIES ANALYSIS. IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, v. N/A, p. 4-pg., . (13/50169-1, 13/50155-0, 14/12236-1, 15/02105-0, 15/24494-8, 14/50715-9, 16/26170-8, 16/08085-3)
MENINI, NATHALIA; ALMEIDA, ALEXANDRE E.; LAMPARELLI, RUBENS; LE MAIRE, GUERRIC; OLIVEIRA, RAFAEL S.; VERBESSELT, JAN; HIROTA, MARINA; TORRES, RICARDO DA S.. Tucuma A toolbox for spatiotemporal remote sensing image analysis. IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, v. 7, n. 3, p. 13-pg., . (13/50169-1, 13/50155-0, 14/12236-1, 15/02105-0, 17/12646-3, 18/06918-3, 14/50715-9, 16/26170-8, 16/08085-3)
VARGAS MUNOZ, JAVIER A.; DIAS, ZANONI; TORRES, RICARDO S.; ASSOC COMP MACHINERY. A Genetic Programming Approach for Searching on Nearest Neighbors Graphs. ICMR'19: PROCEEDINGS OF THE 2019 ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA RETRIEVAL, v. N/A, p. 5-pg., . (13/50169-1, 13/50155-0, 14/12236-1, 16/50250-1, 15/24494-8, 14/50715-9, 17/20945-0)
NOGUEIRA, KEILLER; DOS SANTOS, JEFERSSON A.; CANCIAN, LEONARDO; BORGES, BRUNO D.; SILVA, THIAGO S. F.; MORELLATO, LEONOR PATRICIA; TORRES, RICARDO DA S.; IEEE. SEMANTIC SEGMENTATION OF VEGETATION IMAGES ACQUIRED BY UNMANNED AERIAL VEHICLES USING AN ENSEMBLE OF CONVNETS. 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), v. N/A, p. 4-pg., . (13/50169-1, 13/50155-0, 14/12236-1, 14/50715-9)

Por favor, reporte erros na lista de publicações científicas utilizando este formulário.