Relations between growth analysis, yield and remote sensing of sugarcane / Relação entre indicadores de crescimento e de produção da cana-de-açucar e dados espectrais terrestres e orbitais

AUTOR(ES)
DATA DE PUBLICAÇÃO

2007

RESUMO

The knowledge about the relations between agronomic variables and spectral data is a challenging issue when adopting remote sensing technique for crop yield forecast. This study analyses the relationship between sugarcane agronomic variables and spectral data derived from field spectroscopy and orbital data. One commercial field of sugarcane with the variety SP80-1842, planted in 1996, located in Araras municipality, São Paulo State, was monitored by biophysical data, field spectroscopy and satellite images in nine different dates during the crop seasons of 2000 and 2001. Leaf area index (LAI), number of stalks per meter (NPM), yield (TCH), total biomass (BMT) and spectral data were studied by temporal analysis, by linear and multiple regressions (Stepwise), and correlation analysis. Field spectroscopy data were obtained with Cimel 313a and orbital data were gathered from Landsat-5 and Landsat-7 images. All the three sensors have the same spectral resolution. The spectral data studied were red band, near infrared band and the spectral vegetation indices SR, RVI, NDVI and SAVI. The temporal behaviour of the agronomic variables were explained by sigmoidal and exponential models and the spectral data were explained by quadratic, cubic and exponential cubic models. No significant differences were found between the two levels of spectral data: field spectroscopy and orbital images. The best correlations between spectral vegetation indices and agronomic variables were with NDVI, SR and RVI. Multiple regression used to estimate yield and biomass obtained r2 values greater than 0,90 for field spectroscopy and greater than 0,80 for satellite images. These results showed the feasibily of using regression analysis to estimate yield and biomass of sugarcane based on spectral data. Key words: Sugarcane; growth analysis; field spectroscopy; orbital spectral data

ASSUNTO(S)

cana-de-açucar imagens multiespectrais sugarcane remote sensing sensoriamento remoto multispectral images

ACESSO AO ARTIGO

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