Seeing the snow through the trees : towards a validated canopy adjustment for satellite fractional snow-covered area Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/g158bm69j

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  • Forest canopy cover presents a major challenge for remote sensing of fractional snow-covered area (ƒSCA). Snow cover is systematically underestimated where satellites sensors cannot penetrate the forest canopy. Current canopy adjustments scale observable ƒSCA with the vegetation fraction, assuming that snow cover distributions are similar between sub-canopy and open locations. This assumption may be invalid because snow accumulation and ablation processes depend on forest characteristics. This study addresses how individual trees and the forest canopy affect snow cover distributions with the goal of determining metrics that can characterize spatial patterns of sub-canopy snow cover. In situ snow cover and forest canopy measurements were made at several snow study sites in the Oregon Cascades. These were compared to canopy-adjusted satellite estimates of ƒSCA. Differences between in situ and satellite ƒSCA were assessed based on forest canopy structure derived from manual surveys along transects, and 3-D terrestrial laser scanning (TLS). For larger spatial context, a simple geometric-optical model (SGM) was used to estimate forest canopy parameters from aerial photographs and multi-angular satellite data. The canopy adjustment resulted in improvements over unadjusted ƒSCA. However, a single canopy adjustment function is not able to adequately adjust for snow under trees in all cases. At the lower elevation sites, snow was present in the low-density forest sites for at least 14 days after it had completely disappeared from the high-density forested sites. At the higher elevation sites, snow remained in the high-density forested sites for at least 7 days after it had completely disappeared from the low-density sites. In assessing the vegetation survey results we found that TLS effectively depicted tree heights and crown radii, but the SGM estimates of canopy structure from aerial photographs and satellite multi-angular reflectance data require further refinement in dense forests before being applied for operational canopy adjustments.
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