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| REIS, A. A. dos; WERNER, J. P. S.; SILVA, B. C. da; ANTUNES, J. F. G.; ESQUERDO, J. C. D. M.; FIGUEIREDO, G. K. D. A.; COUTINHO, A. C.; LAMPARELLI, R. A. C.; MAGALHÃES, P. S. G.. |
| ABSTRACT. Canopy height (CH) is one of the key parameters used to evaluate forage biomass production and support grazing management decisions in intensively managed fields. In this study, we demonstrate the potential of using textural information derived from PlanetScope (PS) imagery to estimate CH of intensively managed mixed pastures in an Integrated Crop-Livestock Systems (ICLS) in the western region of São Paulo State, Brazil. PS images and field data of CH were acquired during the forage growing season of 2019 (from May to November) to calibrate and validate the CH prediction models using the Random Forest (RF) regression algorithm. We used as predictor variables eight second-order texture measures derived from the green, red, near-infrared spectral... |
| Tipo: Anais e Proceedings de eventos |
Palavras-chave: Sistemas integrados; Nanossatélites; Medidas de textura; Integração lavoura pecuária; Canopy height; Integrated systems; Nano-satellites; Texture measures; Integrated crop-livestock systems; Pastagem. |
| Ano: 2021 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1136079 |
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| REIS, A. A. dos; WERNER, J. P. S.; SILVA, B. C.; FIGUEIREDO, G. K. D. A.; ANTUNES, J. F. G.; ESQUERDO, J. C. D. M.; COUTINHO, A. C.; LAMPARELLI, R. A. C.; ROCHA, J. V.; MAGALHÃES, P. S. G.. |
| Abstract: Fast and accurate quantification of the available pasture biomass is essential to support grazing management decisions in intensively managed fields. The increasing temporal and spatial resolutions oered by the new generation of orbital platforms, such as Planet CubeSat satellites, have improved the capability of monitoring pasture biomass using remotely sensed data. Here, we assessed the feasibility of using spectral and textural information derived from PlanetScope imagery for estimating pasture aboveground biomass (AGB) and canopy height (CH) in intensively managed fields and the potential for enhanced accuracy by applying the extreme gradient boosting (XGBoost) algorithm. Our results demonstrated that the texture measures enhanced AGB and CH... |
| Tipo: Artigo de periódico |
Palavras-chave: Pasto; Pastagem tropical; Floresta aleatória; Random forest; Mixed pastures; Integrated systems; Texture measures; Extreme gradient boosting; Biomassa; Pastagem Mista; Sensoriamento Remoto; Pastures; Tropical pastures; Biomass; Aboveground biomass; Remote sensing. |
| Ano: 2020 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1125026 |
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