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TitleA multi-scale approach to mapping effective leaf area index in Boreal Picea mariana stands using high spatial resolution CASI imagery
AuthorFernandes, R; Miller, J R; Hu, B; Rubinstein, I G
SourceInternational Journal of Remote Sensing vol. 23, no. 18, 2002 p. 3547-3568,
Alt SeriesNatural Resources Canada, Contribution Series 20181579
PublisherInforma UK Limited
Mediapaper; on-line; digital
File formatpdf
Subjectsgeophysics; remote sensing
ProgramClimate Change Geoscience
Released2010 11 25
AbstractThis study evaluates the performance of a simple geometric-optics reflectance model, used in combination with multi-spectral clustering, to map spatial patterns of effective Leaf Area Index (Le) within Boreal Picea mariana stands. Two metre resolution Compact Airborne Spectrographic Imager (CASI) images, acquired during the winter to minimize variability in understory reflectance, are used to map Le over BOREAS northern and southern Old Black Spruce tower flux sites. A combined multi-spectral clustering and ray-tracing approach is used to map open areas in each site at 2 m scale. A modified version of the Forest Light Interaction Model (FLIM) is then applied over canopy areas using 30 m scale red and near-infrared reflectance values derived from CASI images. Comparison of the combined FLIM and clustering approach (FLIMCLUS) with surface Le measurements in areas with overstory cover indicate a R2 of 0.67 for the SSA-OBS site and 0.16 for the NSA-OBS site. The poor NSA-OBS performance may be due to the low observed range of Le along the transect selected since additional measurements in a sparse canopy area closely match FLIM estimates. The relative standard error at both sites is under 10% and is close to the 5% precision error in surface Le estimates. Comparison of FLIMCLUS with FLIM and the simple ratio indicate substantial differences over open areas where the latter methods map-zero Le values. Further validation over other study sites, including surface data mapping edges between canopy and open areas, is proposed. The FLIM-CLUS Le maps may be useful for testing scale dependent assumptions within remote sensing algorithms and ecosystem flux models applied to the study sites and similar Picea mariana stands.