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1000
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Abstract/Summary
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Agricultural intensification decreased land cover complexity by converting small complex arable field geometries into large and simple structures which then were managed uniformly. These changes have led to a variety of negative environmental effects and influence ecosystem services. We present a novel small-scale and site-specific cropping system which splits a large field into small homogeneous sub-fields called ‘patches’ grouped in different yield potentials. A detailed workflow is presented to generate new spatially arranged patches with special focus on preprocessing and filtering of multi-year yield data, the variation in patch sizes and the adaptation of maximum working width to use available conventional farm equipment and permanent traffic lanes. The reduction of variance by the used cluster algorithm depends on the within-field heterogeneity. The patch size, the number of growing seasons (GS) used for clustering and the parallel shift of the patch structure along the permanent traffic lane resulted in a change in relative variance. Independent cross validation showed an increased performance of the classification algorithm with increasing number of GS used for clustering. The applied cluster analysis resulted in robust field segregation according to different yield potential zones and provides an innovative method for a novel cropping system.
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