Original paper
A general method to filter out defective spatial observations from yield mapping datasets
Abstract
Yield maps are recognized as a valuable tool with regard to managing upcoming crop production but can contain a large amount of defective data that might result in misleading decisions. These anomalies must be removed before further processing to ensure the quality of future decisions. This paper proposes a new holistic methodology to filter out defective observations likely to be present in yield datasets. The notion of spatial neighbourhood...
Paper Details
Title
A general method to filter out defective spatial observations from yield mapping datasets
Published Date
Jan 18, 2018
Journal
Volume
19
Issue
5
Pages
789 - 808
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Notes
History