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 a Geographic 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. The relationship 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 the potential of remote sensing for spatial variability studies.

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Published in Transactions of the ASAE, v. 41, issue 2, p. 489-495.

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Salaries and research support provided by State and Federal Funds appropriated to the Ohio Agricultural Research and Development Center, The Ohio State University.