Yield maps reflect systematic and random sources of yield variation as well as numerous errors caused by the harvest and mapping procedures used. A general framework for processing of multi-year yield map data was developed. Steps included (1) raw data screening, (2) standardization, (3) interpolation, (4) classification of multi-year yield maps, (5) post-classification spatial filtering to create spatially contiguous yield classes, and (6) statistical evaluation of classification results. The techniques developed allow more objective mapping of yield zones, which are an important data layer in algorithms for prescribing variable rates of production inputs.
Precision Agriculture – Springer Journals
Published: Jan 20, 2005
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