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Proceedings Paper

Dynamics modeling for sugar cane sucrose estimation using time series satellite imagery
Author(s): Yu Zhao; Diego Della Justina; Yoriko Kazama; Jansle Vieira Rocha; Paulo Sergio Graziano; Rubens Augusto Camargo Lamparelli
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Paper Abstract

Sugarcane, as one of the most mainstay crop in Brazil, plays an essential role in ethanol production. To monitor sugarcane crop growth and predict sugarcane sucrose content, remote sensing technology plays an essential role while accurate and timely crop growth information is significant, in particularly for large scale farming. We focused on the issues of sugarcane sucrose content estimation using time-series satellite image. Firstly, we calculated the spectral features and vegetation indices to make them be correspondence to the sucrose accumulation biological mechanism. Secondly, we improved the statistical regression model considering more other factors. The evaluation was performed and we got precision of 90% which is about 20% higher than the conventional method. The validation results showed that prediction accuracy using our sugarcane growth modeling and improved mix model is satisfied.

Paper Details

Date Published: 25 October 2016
PDF: 11 pages
Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99980J (25 October 2016); doi: 10.1117/12.2242490
Show Author Affiliations
Yu Zhao, Hitachi, Ltd. (Japan)
Diego Della Justina, Univ. Estadual de Campinas (Brazil)
Yoriko Kazama, Hitachi, Ltd. (Japan)
Jansle Vieira Rocha, Univ. Estadual de Campinas (Brazil)
Paulo Sergio Graziano, Univ. Estadual de Campinas (Brazil)
Rubens Augusto Camargo Lamparelli, Univ. Estadual de Campinas (Brazil)


Published in SPIE Proceedings Vol. 9998:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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