Three spatial data sets consisting of high spatial resolution (1 m) remote sensing images acquired in 12 spectral bands, an on-the-go yield map, and a Digital Elevation Model were co-registered and evaluated for spatial variability studies in aGeographic Information Systems environment. Separate on-the-go yield maps were developed for 3, 5, and 12 statistically significant mean yield classes. For each yield class, the corresponding mean spectral and elevation data were extracted. Therelationship between mean spectral and yield data was strongly linear (r = 0.99). Also, a strong linear relationship between mean yield and elevation data (r = 0.92) was found. The relationship between the spectral and on-the-go yield data indicated thepotential of remote sensing for spatial variability studies.
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