Airborne hyperspectral imaging for estimating acorn yield based on the PLS B-matrix calibration technique

Alternate bearing of acorn is a well-marked yield variability phenomenon in forest production. In Japan, this phenomenon is also related to wildlife management (e.g. of animals such as wild pigs, that rely on acorn as their major feed source). Effective management of animals dependent on acorn will require accurate estimation of acorn yield at an early stage. In this paper, we proposed a way to estimate acorn yield from the canopy reflectance values of individual trees. Using an Airborne Imaging Spectrometer for Application (AISA) Eagle System, hyperspectral images in 72 visible and near-infrared wavelengths (407–898 nm) were acquired over an acorn forest in Japan 10 times over three consecutive years (2003–2005) during the early acorn growing season. The canopy spectral reflectance values for individual trees at each wavelength were extracted from the images, and important wavelengths were determined as estimating factors by the B-matrix technique based on partial least squares (PLS) analysis. Yield-estimating models were then developed by multiple linear regression (MLR). Three models obtained from images acquired on June 27 in 2003, July 13 in 2004 and June 21 in 2005 estimated acorn yield well in comparison with ground truth, indicating that the procedure has considerable potential. The study also demonstrated the B-matrix technique based on PLS analysis to be reliable and efficient in identifying important wavelengths for determining suitable estimating factors that best contribute to the estimation model.