| Summary: | Forests play an essential role in maintaining the Earth’s overall energy balance. The variability in forest canopy structure, topography, and underneath vegetation background conditions create uncertainty in modeling solar radiation at the Earth’s surface, particularly for boreal regions in high latitude. The purpose of this study is to analyze seasonal variation in visible, near-infrared, and shortwave infrared reflectance with respect to land cover classes, canopy structures, and topography in a boreal region of Alaska. We accomplished this investigation by fusing Landsat 8 images and LiDAR-derived canopy structural data and multivariate statistical analysis. Our study shows that canopy structure and topography interplay and influence reflectance spectra in a complex way, particularly during the snow season. We observed that deciduous trees, also tall with greater rugosity, are more dominant on the southern slope than on the northern slope. Taller trees are typically seen in higher elevations regardless of vegetation types. Surface reflectance in all studied wavelengths shows similar relationships with canopy cover, height, and rugosity, mainly due to close connections between these parameters. Visible and near-infrared reflectance decreases with canopy cover, tree height, and rugosity, especially for the evergreen forest. Deciduous forest shows more considerable variability of surface reflectance in all studied wavelengths, particularly in March, mainly due to the mixing effect of snow and vegetation. The multivariate statistical analysis demonstrates a significant tree shadow effect on surface reflectance for evergreen forests. However, the topographic shadow effect is prominent for deciduous forests during the winter season. These results provide great insight into understanding the role of vegetation structure and topography in surface radiation budget in the boreal region.
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