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Mapping productivity and essential biophysical parameters of cultivated tropical grasslands from sentinel-2 imagery. Abstract: Nitrogen (N) is the main nutrient element that maintains productivity in forages; it is inextricably linked to dry matter increase and plant support capacity. In recent years, high spectral... ... Repository: BDPA Publication year: 2020
Mapping agricultural intensification in the Brazilian savanna: a machine learning approach using harmonized data from Landsat Sentinel-2. Author(s): BOLFE, E. L.; SANO, E. E.; BETTIOL, G. M.; VICTORIA, D. de C.; VICENTE, L. E. Agricultural intensification practices have been adopted in the Brazilian savanna (Cerrado), mainly in the transition between Cerrado and the Amazon Forest, to increase productivity while reducing pre... ... Repository: BDPA Publication year: 2023
Multitemporal segmentation of Sentinel-2 images in an agricultural intensification region in Brazil. Author(s): ANTUNES, J. F. G.; COUTINHO, A. C.; ESQUERDO, J. C. D. M. ABSTRACT: With the recent evolution in the sensor's spatial resolution, such as the MultiSpectral Imager (MSI) of the Sentinel-2 mission, the need to use segmentation techniques in satellite images ha... ... Repository: BDPA Publication year: 2022
Imputation of missing parts in UAV orthomosaics using PlanetScope and Sentinel-2 data: a case study in a grass-dominated área. Author(s): OLIVEIRA, S. R. de M.; ANTUNES, J. F. G. In this study, we propose a methodological framework to impute missing parts of UAV orthomosaics using PlanetScope (PS) and Sentinel-2 (S2) data and the random forest (RF) algorithm of an integrated c... ... Repository: BDPA Publication year: 2023
Mapping integrated crop–livestock systems using fused Sentinel-2 and PlanetScope time series and deep learning. Author(s): ANTUNES, J. F. G.; COUTINHO, A. C.; ESQUERDO, J. C. D. M. 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
Optimum combination of spectral variables for crop mapping in heterogeneous landscapes based on Sentinel-2 time series and machine learning. Author(s): ESQUERDO, J. C. D. M. This article aimed to determine a workflow for more efficient large-scale crop mapping using a time series of images from the Sentinel-2 Satellite, statistical methods of attribute selection, and mach... ... Repository: BDPA Publication year: 2024
Evaluation of early season mapping of integrated crop livestock systems using Sentinel-2 data. Author(s): ESQUERDO, J. C. D. M.; ANTUNES, J. F. G.; COUTINHO, A. C. ABSTRACT. Various approaches were developed considering the need to increase agricultural productivity in cultivated areas without more deforestation, such as the Integrated Crop livestock systems (IC... ... Repository: BDPA Publication year: 2022
Improved modeling of gross primary production and transpiration of sugarcane plantations with time-series Landsat and Sentinel-2 images. Author(s): CABRAL, O. M. R. Abstract: Sugarcane croplands account for ~70% of global sugar production and ~60% of global ethanol production. Monitoring and predicting gross primary production (GPP) and transpiration (T) in these... ... Repository: BDPA Publication year: 2023
New vegetation index for monitoring coffee rust using sentinel-2 multispectral imagery. Author(s): FERREIRA, W. P. M. Coffee Rust (Hemileia vastatrix) is considered the primary coffee disease in the world. The pathogenic fungus can find favorable environmental conditions in different countries, constantly threatening... ... Repository: BDPA Publication year: 2023
New spectral index and machine learning models for detecting coffee leaf miner infestation using sentinel-2 multispectral imagery. Author(s): FERREIRA, W. P. M. The coffee leaf miner (Leucoptera coffeella) is a key coffee pest in Brazil that can cause severe defoliation and a negative impact on the productivity. Thus, it is essential to identify initial pest... ... Repository: BDPA Publication year: 2023

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