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Functional regression in crop lodging assessment with digital images

Abstract

A method is proposed to predict a lodging score for a rice field based only on a digital overhead image of the field. This method converts the two-dimensional image data to a one-dimensional function by computing the average variance of transects across the image as a function of the transect angle. Then principles of functional data analysis are applied to estimate a regression function, and the predicted lodging score is an intercept term plus a measure of overall variability plus the inner product of the regression function and the periodogram of the average variance function.

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Correspondence to R. Todd Ogden.

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previously Associate Professor, Department of Statistics, University of South Carolina.

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Ogden, R.T., Miller, C.E., Takezawa, K. et al. Functional regression in crop lodging assessment with digital images. JABES 7, 389 (2002). https://doi.org/10.1198/108571102339

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  • DOI: https://doi.org/10.1198/108571102339

Key Words

  • Functional data analysis
  • Generalized cross-validation
  • Image transects
  • Remote sensing