Modeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction

Sloping terrain induces distortion of canopy reflectance (CR), and the retrieval of biophysical variables from remote sensing data needs to account for topographic effects. We developed a 1-D model (the path length correction (PLC)-based model) for simulating CR over sloping terrain. The effects of sloping terrain on single-order and diffuse scatterings are accounted for by PLC and modification of the fraction of incoming diffuse irradiance, respectively. The PLC model was validated via both Monte Carlo and remote sensing image simulations. The comparison with the Monte Carlo simulation revealed that the PLC model can capture the pattern of slope-induced reflectance distortion with high accuracy (red band: <inline-formula> <tex-math notation="LaTeX">$R^{2} = 0.88$ </tex-math></inline-formula>; root-mean-square error (RMSE) = 0.0045; relative RMSE (RRMSE) = 15%; near infrared response (NIR) band: <inline-formula> <tex-math notation="LaTeX">$R^{2} = 0.79$ </tex-math></inline-formula>; RMSE = 0.041; RRMSE = 16%). The comparison of the PLC-simulated results with remote sensing observations acquired by the Landsat8-OLI sensor revealed an accuracy similar to that with the Monte Carlo simulation (red band: <inline-formula> <tex-math notation="LaTeX">$R^{2} = 0.83$ </tex-math></inline-formula>; RMSE = 0.0053; RRMSE = 13%; NIR band: <inline-formula> <tex-math notation="LaTeX">$R^{2} = 0.77$ </tex-math></inline-formula>; RMSE = 0.023; RRMSE = 8%). To further validate the PLC model, we used it to implement topographic normalization; the results showed a large reduction in topographic effects after normalization, which implied that the PLC model captures reflectance variations caused by terrain. The PLC model provides a promising tool to improve the simulation of CR and the retrieval of biophysical variables over mountainous regions.