SHANNON-WIENER'S DIVERSITY INDEX FOR LINKING YIELD MONITOR AND REMOTELY SENSED DATA FOR CORN
Yield is the ultimate measure for quantifying the effect of agricultural inputs. Measurement of yield variability is 
needed for developing and evaluating site-specific crop management strategies. However, there are many sources of error 
in measuring the actual yield variability. To assess the contribution of harvest practices to yield variability, yield monitor and 
aerial image data were collected in the 2000 growing season. Aerial images were collected by a DuncanTech MS3100 multispectral 
digital camera on two dates. The boundary effect on variability of yield monitor data was studied by successive clipping 
of yield monitor data for determining the effect of the harvester operations at the end of the field on the yield monitor 
errors. Results indicated that the correlations between grain yield and the normalized difference vegetation index (NDVI) 
at the V16 growth stage were improved as the field perimeter was clipped to 30.5 m inside of the field boundary; the coefficient 
of determination (r2) improved from 0.67 to 0.76. The Shannon-Wiener diversity index (SWDI), an index used in ecological 
studies to determine how diverse a population is, showed that diversity at the perimeter was decreased as additional clipping 
of data occurred inside the field perimeter. The yield variability was considerably higher in the clipped areas than in other 
areas due to the speed of the harvester, headland harvest, and time for yield monitor fill-up and emptying. Areas of the highly 
diverse yield monitor were about twice that of remotely sensed data, as indicated by the SWDI. Results indicated that the outer 
6.1 m was responsible for about 34% of the high yield diversity at the perimeter of the field. The headland harvesting effect 
was included fully in that 34% high yield diversity.