Modeling the View Angle Dependence of Gap Fractions in Forest Canopies: Implications for Mapping Fractional Snow Cover Using Optical Remote Sensing

Jicheng Liu Department of Geography and Environment, Boston University, Boston, Massachusetts

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Curtis E. Woodcock Department of Geography and Environment, Boston University, Boston, Massachusetts

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Rae A. Melloh Engineer Research and Development Center, Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire

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Robert E. Davis Engineer Research and Development Center, Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire

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Ceretha McKenzie Engineer Research and Development Center, Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire

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Thomas H. Painter Department of Geography, University of Utah, Salt Lake City, Utah

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Abstract

Forest canopies influence the proportion of the land surface that is visible from above, or the viewable gap fraction (VGF). The VGF limits the amount of information available in satellite data about the land surface, such as snow cover in forests. Efforts to recover fractional snow cover from the spectral mixture analysis model Moderate Resolution Imaging Spectroradiometer (MODIS) snow-covered area and grain size (MODSCAG) indicate the importance of view angle effects in forested landscapes. The VGF can be estimated using both hemispherical photos and forest canopy models. For a set of stands in the Cold Land Field Processes Experiment (CLPX) sites in the Fraser Experimental Forest in Colorado, the convergence of both measurements and models of the VGF as a function of view angle supports the idea that VGF can be characterized as a function of forest properties. A simple geometric optical (GO) model that includes only between-crown gaps can capture the basic shape of the VGF as a function of view zenith angle. However, the GO model tends to underestimate the VGF compared with estimates derived from hemispherical photos, particularly at high view angles. The use of a more complicated geometric optical–radiative transfer (GORT) model generally improves estimates of the VGF by taking into account within-crown gaps. Small footprint airborne lidar data are useful for mapping forest cover and height, which makes the parameterization of the GORT model possible over a landscape. Better knowledge of the angular distribution of gaps in forest canopies holds promise for improving remote sensing of snow cover fraction.

Corresponding author address: Jicheng Liu, Department of Geography and Environment, Boston University, 675 Commonwealth Ave., Boston, MA 02215. Email: jcliu@bu.edu

This article included in the The Cold Land Processes Experiment (CLPX) special collection.

Abstract

Forest canopies influence the proportion of the land surface that is visible from above, or the viewable gap fraction (VGF). The VGF limits the amount of information available in satellite data about the land surface, such as snow cover in forests. Efforts to recover fractional snow cover from the spectral mixture analysis model Moderate Resolution Imaging Spectroradiometer (MODIS) snow-covered area and grain size (MODSCAG) indicate the importance of view angle effects in forested landscapes. The VGF can be estimated using both hemispherical photos and forest canopy models. For a set of stands in the Cold Land Field Processes Experiment (CLPX) sites in the Fraser Experimental Forest in Colorado, the convergence of both measurements and models of the VGF as a function of view angle supports the idea that VGF can be characterized as a function of forest properties. A simple geometric optical (GO) model that includes only between-crown gaps can capture the basic shape of the VGF as a function of view zenith angle. However, the GO model tends to underestimate the VGF compared with estimates derived from hemispherical photos, particularly at high view angles. The use of a more complicated geometric optical–radiative transfer (GORT) model generally improves estimates of the VGF by taking into account within-crown gaps. Small footprint airborne lidar data are useful for mapping forest cover and height, which makes the parameterization of the GORT model possible over a landscape. Better knowledge of the angular distribution of gaps in forest canopies holds promise for improving remote sensing of snow cover fraction.

Corresponding author address: Jicheng Liu, Department of Geography and Environment, Boston University, 675 Commonwealth Ave., Boston, MA 02215. Email: jcliu@bu.edu

This article included in the The Cold Land Processes Experiment (CLPX) special collection.

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