Sensoriamento remoto aplicado ao modelo SAFER na estimativa de parâmetros biofísicos de cultivos
Carregando...
Data
2022-02-18
Autores
Almeida, Samira Luns Hatum de
Título da Revista
ISSN da Revista
Título de Volume
Editor
Universidade Estadual Paulista (Unesp)
Resumo
O sensoriamento remoto (SR) é um importante ferramente na estimativa de parâmetros biofísicos das culturas, e tem possibilitado a criação de metodologias precisas, menos morosas e capazes de considerar a variabilidade dos campos de produção. Aliar o SR a variáveis climatológicas, pode melhor a precisão de modelos de estimativa de variáveis biofísicas das culturas e ainda considerar as individualidades e adversidades de cada região. Nesse contexto, o Simple Algorithm for Evapotranspiration Retrieving (SAFER) combina o comportamento espectral da cultura e dados meteorológicos com o objetivo de estimar a evapotranspiração real das culturas, processo relacionado ao seu desenvolvimento. Dito isso, objetivou-se com esta pesquisa avaliar o potencial do sensoriamento remoto aplicado ao modelo SAFER na estimativa: (i) de massa de forragem em sistemas de produção animal; (ii) na estimativa de maturação do amendoim. O experimento com pastagem foi desenvolvido no estado de São Paulo, Brasil, nos sistemas de produção animal a pleno sol e silvipastoril, por quatro ciclos completos da forragem, com a utilização do sensor proximal CropCircle. Já os experimentos com a cultura do amendoim foram desenvolvidos no estado da Georgia, EUA em três campos comerciais. A reflectância ao longo do ciclo foi obtida a partir de imagens do satélite PlanetScope. Os resultados demonstraram que o SAFER é um modelo promissor, tendo maior acurácia e precisão para estimar a massa da forragem composta por folhas e caule no sistema silvipastoril. Para o amendoim, a evapotranspiração estimada pelo SAFER apresentou correlação significativa com o índice de maturação.
Remote sensing is an important tool for estimation of crop biophysical parameters, and has enabled the creation of precise methodologies, less time-consuming and capable of considering the spatial variability of production compounds. Combining this tool with climatological variables can allow better accuracy of estimation models and also consider the individualities and adversities of each region. In this context, the Simple Algorithm for Evapotranspiration Retrieving (SAFER) combines the crop spectral behavior and meteorological data, with the objective of estimating the crop real evapotranspiration, a process related to crop development. The objective of this work was to evaluate the potential of remote sensing applied to the SAFER model in estimating: (i) forage mass in animal production systems. (ii) in the estimation of peanut maturity. The pasture experiment was carried out in the state of São Paulo, Brazil, in full sun and silvopastoral animal production systems during four complete forage cycles, using an active crop canopy sensor HOlland Scientific model ACS 430. The experiments with the peanut crop were carried out in the state of Georgia, USA in three commercial fields. The reflectance over the cycle was obtained from PlanetScope satellite images. The results showed that SAFER is a promising model in the estimation of forage mass, having greater accuracy and precision to estimate the mass of forage composed of leaves and stem in the silvopastoral system. For peanuts, the evapotranspiration estimated by SAFER showed a significant correlation with the maturity index and made it possible to generate a robust model for estimating this variable.
Remote sensing is an important tool for estimation of crop biophysical parameters, and has enabled the creation of precise methodologies, less time-consuming and capable of considering the spatial variability of production compounds. Combining this tool with climatological variables can allow better accuracy of estimation models and also consider the individualities and adversities of each region. In this context, the Simple Algorithm for Evapotranspiration Retrieving (SAFER) combines the crop spectral behavior and meteorological data, with the objective of estimating the crop real evapotranspiration, a process related to crop development. The objective of this work was to evaluate the potential of remote sensing applied to the SAFER model in estimating: (i) forage mass in animal production systems. (ii) in the estimation of peanut maturity. The pasture experiment was carried out in the state of São Paulo, Brazil, in full sun and silvopastoral animal production systems during four complete forage cycles, using an active crop canopy sensor HOlland Scientific model ACS 430. The experiments with the peanut crop were carried out in the state of Georgia, USA in three commercial fields. The reflectance over the cycle was obtained from PlanetScope satellite images. The results showed that SAFER is a promising model in the estimation of forage mass, having greater accuracy and precision to estimate the mass of forage composed of leaves and stem in the silvopastoral system. For peanuts, the evapotranspiration estimated by SAFER showed a significant correlation with the maturity index and made it possible to generate a robust model for estimating this variable.
Descrição
Palavras-chave
Agricultura digital, Massa de forragem, Maturação do amendoim, Sensor proximal, Sensor orbital, Amendoim, Maturação, Agricultura