DEVELOPING SUGAR CANE YIELD PREDICTION ALGORITHMS FROM SATELLITE IMAGERY By

@inproceedings{Robson2012DEVELOPINGSC,
  title={DEVELOPING SUGAR CANE YIELD PREDICTION ALGORITHMS FROM SATELLITE IMAGERY By},
  author={Andrew Robson and Chris Abbott and D. Lamb and R. G. V. Bramley},
  year={2012}
}
THE RESEARCH PRESENTED in this paper discusses the accuracies of remote sensing and GIS as yield prediction tools at both a regional and crop scale over three Australian cane growing regions; Bundaberg, Burdekin and the Herbert. For the Burdekin region, the prediction of total tonnes of cane per hectare (TCH) produced from 4999 crops during the 2011 season was 99% using an algorithm derived from 2010 imagery (green normalised difference vegetation index) and average yield (TCH) data extracted… CONTINUE READING
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