Knowledge discovery and unsupervised detection of within-field yield defective observations

Suspicious observations, or the so-called outliers, are always present, to a greater or lesser extent, in agronomical and environmental datasets. Within field yield datasets are no exception. While most filtering approaches use expert thresholds and dedicated filters to remove these defective observations, more general and unsupervised methods will be required to process a growing number of yield maps. However, by using these last approaches,...