As the strength of wood is greatly affected by its three-dimensional (3D) grain angles (the dive angle and the surface angle), the wood industry today requires automatic, rapid, and robust measurement techniques for measuring them simultaneously. In the present study, a near infrared spatially and spectrally resolved imaging (NIR-SSRI) system was designed in a line scan model, mainly including an NIR hyperspectral imaging camera and a halogen spotlight source (Ø 1 mm). Spatially resolved diffuse reflectance images at three target wavelengths (1002 nm, 1217 nm, and 1413 nm) were obtained from Hinoki cypress [ Chamaecyparis obtusa (Siebold & Zucc.) Endl.] samples at various (0°, 3°, 6°, … 45°) dive angles and surface angles (0°, 3°, 6°, … 45°). The scattering patterns caused by the “tracheid effect” were almost elliptical. Subsequently, nonlinear least squares fitting was used to determine their eccentricities ( e ) and rotation angles ( θ ). The e values at each selected wavelength were highly correlated with the dive angle reference values; and the global identification model developed using Gaussian process regression (GPR) under five-fold cross-validation (CV) reached a determination coefficient ( r 2 ) of 0.98 with a root mean square error (RMSE) of 2.2°. On the other hand, local surface angle identification models developed using linear regression analysis achieved determination coefficients higher than 0.90 on r 2 and an RMSE of CV lower than 3.8° when the dive angle was lower than 30°.