Topographic Effects on Optical Remote Sensing: Simulations by PLC Model

Optical remote sensing offers a convenient method to monitor changes in mountain vegetation at regional and global scales, thanks to its synoptic coverage and frequent temporal sampling capabilities provided by satellite observations. However, local topography substantially affects remotely sensed observations and subsequently impacts the accuracy of biophysical parameter retrieval [e.g., leaf area index (LAI)], hindering the application of remote sensing over mountainous areas. However, the quantification of topographic effects based on remote sensing imagery is limited by the variability of conditions in a study area. Additionally, it is also not conducive to investigate the topographic effects on hyperspectral observations. Therefore, this article employed computer simulation model, i.e., path length correction model, to controllably simulate the topographic effects on hyperspectral reflectance, and 12 vegetation indices (VIs) and LAI retrieval. The results showed that topographic effects varied with the spectral band and were modulated by various factors, such as slope, aspect, and sun position. The topographic effects on VIs exhibited divergence, in which the topographic effects on normalized difference vegetation index and difference vegetation index were smallest and largest, respectively. The topography effects on LAI retrieval were related to terrain configuration and canopy density under specific solar zenith angle. The relative error of LAI retrieval could exceed 100% under extreme conditions. This article will facilitate understanding of topographic effects on hyperspectral remote sensing over mountainous regions.