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Creating Spatially Contiguous Yield Classes for Site-Specific Management

Dep. of Agron. and Hortic., Univ. of Nebraska, P.O. Box 830915, Lincoln, NE 68583-0915

View larger version (40K): [in a new window]   Fig. 1. General flowchart of yield data processing. PCI, prior-classification interpolation; PCF, postclassification filtering.

View larger version (101K): [in a new window]   Fig. 2. Maps of yield classes at Sites A (Clay Center, left) and B (Cairo, right) as affected by aggregation method (PCI: prior-classification interpolation; PCF: postclassification filtering) and cell size used for interpolation in PCI or windows size used for PCF (4–64 m). All maps shown are for hierarchical cluster analysis using Ward's method. Light colors show high-yielding areas; dark colors show low-yielding areas with high yield variability among years. At Site A, the circle indicates the center-pivot–irrigated area.

View larger version (31K): [in a new window]   Fig. 3. Effect of different spatial aggregation techniques on the average yield variance (RVc, %/100) accounted for by the classification at Sites A (a and b, Clay Center) and B (c and d, Cairo). Left (a, c): Mean relative yield was first interpolated to maps of different grid cell size and then classified using hierarchical cluster analysis (WAR) or fuzzy-k-means clustering (FUZ). Right (b, d): Mean relative yield was interpolated to 4- by 4-m grid cell size and classified using WAR or FUZ, and the resulting yield classes were then spatially filtered using different window sizes ranging from 8 to 64 m.

View larger version (43K): [in a new window]   Fig. 4. Effect of increasing grid cell size used in prior-classification interpolation (PCI, left) or window size used in postclassification filtering (PCF, right) on selected landscape pattern metrics describing the categorical maps of yield classes at Sites A and B. Landscape metrics shown are patch density (PD), the total core area per field (TCA), the mean core area per patch (MCA), the contagion index (CONTAG), and the splitting index (SPLIT). All values refer to hierarchical cluster analysis using the Ward method.