Visible-near infrared (VIS-NIR) spectral data are widely used for remotely estimating a number of crop health metrics. In general, these indices and models do not explicitly account for leaf surface characteristics, which themselves can be indicators of plant status or environmental responses. To explicitly include leaf surface characteristics, data are required linking optical properties to surface characteristics. We present the design and experimental validation of a goniospectropolarimeter (GoSPo) that combines the capabilities of a spectrometer, goniometer, and polarimeter. GoSPo was designed with the objective of studying the relationships between leaf surface characteristics and the resulting light reflectance, transmission, and polarization as functions of both direction and VIS-NIR spectra. Using six motors, a pneumatic system, two spectrometers, and a combination of lenses, polarizers, and mirrors, GoSPo can examine a leaf from a particular angle, approximate hemispherical transmittance and reflectance (with root-mean-square error values of 0.0189 and 0.0216 for reflectance and transmittance, respectively, compared to a spectrophotometer and integrating sphere), and obtain spectral polarization measurements without disrupting the sample between measurements. The data collected with GoSPo will aid in model development for remote sensing applications.