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Land use/cover classification in the Brazilian Amazon using satellite images. Author(s): LU, D.; BATISTELLA, M.; LI, G.; MORAN, E.; HETRICK, S.; FREITAS, C. DA C.; SANT'ANNA, S. J. Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical... ... Repository: BDPA Publication year: 2012
Biometric characteristics and canopy reflectance association for early-stage sugarcane. Author(s): ROCHA, M. G. da; BARROS, F. M. M. de; OLIVEIRA, S. R. de M.; AMARAL, L. R. do ABSTRACT: Knowing the spatial variability of sugarcane biomass in the early stages of development may help growers in their management decision-making. Proximal canopy sensing is a promising technolog... ... Repository: BDPA Publication year: 2019
Information and precision technologies used for improving the milking routine performance. Author(s): PAIVA, C. A. V.; MACHADO, F. S.; CAMPOS, M. M.; SOUZA, G. N. de; VELASCO, F. O.; POSSAS, F. P.; LIMA, J. A. M.; FERREIRA, A. L.; PEREIRA, L. G. R. Repository: BDPA Publication year: 2016
Análise de dados de dispositivos IoT instalados em estábulo do tipo "Compost Barn". Author(s): AMORIM FILHO, M. de M.; CARNEIRO, J. da C.; ARBEX, W. A.; BERNARDO, W. F.; ARCURI, P. B. A convergência entre a Internet das Coisas (IoT) e o agronegócio, notadamente na pecuária, promove uma gestão ambiental mais precisa e uma produção mais eficiente. A IoT, interligando dispositivos por... ... Repository: BDPA Publication year: 2024
Data fusion in agriculture: resolving ambiguities and closing data gaps. Author(s): BARBEDO, J. G. A. Abstract. Acquiring useful data from agricultural areas has always been somewhat of a challenge, as these are often expansive, remote, and vulnerable to weather events. Despite these challenges, as te... ... Repository: BDPA Publication year: 2022
Model for multiple imputation to estimate daily rainfall data and filling of faults. Author(s): CARVALHO, J. R. P. de; MONTEIRO, J. E. B. de A.; NAKAI, A. M.; ASSAD, E. D. Modeling by multiple enchained imputation is an area of growing importance. However, its models and methods are frequently developed for specific applications. In this study the model for multiple imp... ... Repository: BDPA Publication year: 2017
Forage mass estimation in silvopastoral and full sun systems: evaluation through proximal remote sensing applied to the SAFER model. Author(s): ALMEIDA, S. L. H. DE; SOUSA, J. B. C.; NOGUEIRA, S. F.; PEZZOPANE, J. R. M.; TEIXEIRA, A. H. DE C.; BOSI, C.; ADAMI, M.; ZERBATO, C.; BERNARDI, A. C. de C.; SILVA, G. B. S. da; SILVA, R. P. DA Abstract: The operational slowness in the execution of direct methods for estimating forage mass, an important variable for defining the animal stocking rate, gave rise to the need for methods with fa... ... Repository: BDPA Publication year: 2023
Mapping integrated crop–livestock systems using fused Sentinel-2 and PlanetScope time series and deep learning. Author(s): WERNER, J. P. S.; BELGIU, M.; BUENO, I. T.; REIS, A. A. dos; TORO, A. P. S. G. D.; ANTUNES, J. F. G.; STEIN, A.; LAMPARELLI, R. A. C.; MAGALHÃES, P. S. G.; COUTINHO, A. C.; ESQUERDO, J. C. D. M.; FIGUEIREDO, G. K. D. A. The main objective of this research was to develop a method for mapping ICLS using deep learning algorithms applied on Satellite Image Time Series (SITS) data cubes, which consist of Sentinel-2 (S2) a... ... Repository: BDPA Publication year: 2024
Gamaespectrômetro como ferramenta ao cientista do solo: identificando o limite entre um Argissolo Vermelho e um Planossolo Háplico. Author(s): RODRIGUES, H. M.; NASCIMENTO, C. W. R. do; CEDDIA, M. B.; VASQUES, G. de M.; FEIJÓ, R. G. Este trabalho teve como objetivo mapear o limite entre um PLANOSSOLO HÁPLICO e um ARGISSOLO VERMELHO utilizando um gamaespectrômetro. O estudo foi realizado na Fazendinha Agroecológica Km 47 em Seropé... ... Repository: BDPA Publication year: 2019
A machine learning framework to predict nutrient content in valencia-orange leaf hyperspectral measurements. Author(s): OSCO, L. P.; RAMOS, A. P. M.; PINHEIRO, M. M. F.; MORIYA, E. A. S.; IMAI, N. N.; ESTRABIS, N.; IANCZYK, F.; ARAÚJO, F. F.; LIESENBERG, V.; JORGE, L. A. de C.; LI, J.; MA, L.; GONÇALVES, W. N.; MARCATO JUNIOR, J.; CRESTE, J. E. This paper presents a framework based on machine learning algorithms to predict nutrient content in leaf hyperspectral measurements. This is the first approach to evaluate macro- and micronutrient con... ... Repository: BDPA Publication year: 2020

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