58
considerations with the use of leaf and imaging spectroscopy for scaling plant functional traits. In addition, the underlying drivers of vegetation optical properties are
complex and numerous (Ustin et al. 2004; Ollinger 2011). For example, in the visible range (~0.4–0.75 microns) of the electromagnetic (EM) spectrum, the strong
absorption of solar energy by photosynthetic pigments in healthy, green foliage
dominates the optical properties of leaves (Ustin et al. 2009; Figs. 3.2. and 3.3).
Importantly, knowledge of leaf pigment pools and fluxes provides key insight into
plant photosynthesis, environmental stress, and overall vigor. As such a significant
amount of research has focused on the retrieval of foliar primary and accessory pigments using spectroscopic and other RS measurements (e.g., Jacquemoud et al.
1996; Richardson et al. 2002; Sims and Gamon 2002; Ustin et al. 2009; Féret et al.
2017). Blackburn (2007) and Ustin et al. (2009) provide more detailed reviews on
the use of spectroscopy to remotely sense pigments in higher plants.
Within the near-infrared (NIR, ~0.8–1.2 microns) portion of the EM spectrum,
optical signals are generally dominated by scattering from internal leaf structures,
structural properties, water, and leaf epidermal layer (Figs. 3.2 and 3.3). In addition,
strong leaf water absorption features in the NIR, centered on ~0.97 and 1.1 microns,
are often used to remotely sense vegetation water content (e.g., Hunt and Rock
1989; Gao and Goetz 1995; Sims and Gamon 2003; Stimson et al. 2005; Colombo
et al. 2008). Much of the early research into the use of spectroscopic RS focused on
leaf and canopy water content retrieval given its importance in plant function and as
an important indicator of moisture (Fig. 3.5.) and other stress. In attached, fresh leaf
material, water also dominates the spectral absorption features of the SWIR (1.3–2.5
micron) portion of the EM (Hunt and Rock 1989; Sims and Gamon 2003); as a
result, spectral optical properties are strongly regulated by leaf and canopy water
content in this region (Fig. 3.5). Along with water absorption, a number of other
biochemical and structural trait absorption features exist in the SWIR wavelength
region (Fig. 3.3), including cellulose, lignin, structural carbon, and nutrients and
proteins (Curran 1989; Elvidge 1990; Kokaly et al. 2009; Ollinger 2011; Ely et al.,
2019). Removal of water from leaf materials can sometimes enhance the detection
of these absorption features (e.g., see Serbin et al. 2014 and references within;
Fig. 3.5). However, at the canopy scale, a number of studies have demonstrated the
capacity to retrieve these foliar biochemical properties in the SWIR region (e.g.,
Wessman et al. 1988; Martin and Aber 1997; Townsend et al. 2003; Kokaly et al.
2009; Asner et al. 2015; Singh et al. 2015), perhaps because of the increased signal
due to multiple scattering within canopies (Baret et al. 1994).
In addition to the underlying leaf biochemical and structural characteristics, leaf
orientation, display, and distribution in a canopy are also strong drivers of plant
optical properties (Ollinger, 2011; Fig. 3.4). Decreasing the leaf area of a canopy
generally results in a higher reflectance signal from elements deeper within the
canopy, including twigs, branches, stems, and soil/litter layer (Asner 1998; Asner
et al. 2000; Ollinger 2011). Canopies with flat, horizontal leaves tend to have higher
NIR reflectance than those with more erect, vertical leaves, depending on the sunsensor geometry. Leaf anatomy and average leaf angle vary widely across species
S. P. Serbin and P. A. Townsend
considerations with the use of leaf and imaging spectroscopy for scaling plant functional traits. In addition, the underlying drivers of vegetation optical properties are
complex and numerous (Ustin et al. 2004; Ollinger 2011). For example, in the visible range (~0.4–0.75 microns) of the electromagnetic (EM) spectrum, the strong
absorption of solar energy by photosynthetic pigments in healthy, green foliage
dominates the optical properties of leaves (Ustin et al. 2009; Figs. 3.2. and 3.3).
Importantly, knowledge of leaf pigment pools and fluxes provides key insight into
plant photosynthesis, environmental stress, and overall vigor. As such a significant
amount of research has focused on the retrieval of foliar primary and accessory pigments using spectroscopic and other RS measurements (e.g., Jacquemoud et al.
1996; Richardson et al. 2002; Sims and Gamon 2002; Ustin et al. 2009; Féret et al.
2017). Blackburn (2007) and Ustin et al. (2009) provide more detailed reviews on
the use of spectroscopy to remotely sense pigments in higher plants.
Within the near-infrared (NIR, ~0.8–1.2 microns) portion of the EM spectrum,
optical signals are generally dominated by scattering from internal leaf structures,
structural properties, water, and leaf epidermal layer (Figs. 3.2 and 3.3). In addition,
strong leaf water absorption features in the NIR, centered on ~0.97 and 1.1 microns,
are often used to remotely sense vegetation water content (e.g., Hunt and Rock
1989; Gao and Goetz 1995; Sims and Gamon 2003; Stimson et al. 2005; Colombo
et al. 2008). Much of the early research into the use of spectroscopic RS focused on
leaf and canopy water content retrieval given its importance in plant function and as
an important indicator of moisture (Fig. 3.5.) and other stress. In attached, fresh leaf
material, water also dominates the spectral absorption features of the SWIR (1.3–2.5
micron) portion of the EM (Hunt and Rock 1989; Sims and Gamon 2003); as a
result, spectral optical properties are strongly regulated by leaf and canopy water
content in this region (Fig. 3.5). Along with water absorption, a number of other
biochemical and structural trait absorption features exist in the SWIR wavelength
region (Fig. 3.3), including cellulose, lignin, structural carbon, and nutrients and
proteins (Curran 1989; Elvidge 1990; Kokaly et al. 2009; Ollinger 2011; Ely et al.,
2019). Removal of water from leaf materials can sometimes enhance the detection
of these absorption features (e.g., see Serbin et al. 2014 and references within;
Fig. 3.5). However, at the canopy scale, a number of studies have demonstrated the
capacity to retrieve these foliar biochemical properties in the SWIR region (e.g.,
Wessman et al. 1988; Martin and Aber 1997; Townsend et al. 2003; Kokaly et al.
2009; Asner et al. 2015; Singh et al. 2015), perhaps because of the increased signal
due to multiple scattering within canopies (Baret et al. 1994).
In addition to the underlying leaf biochemical and structural characteristics, leaf
orientation, display, and distribution in a canopy are also strong drivers of plant
optical properties (Ollinger, 2011; Fig. 3.4). Decreasing the leaf area of a canopy
generally results in a higher reflectance signal from elements deeper within the
canopy, including twigs, branches, stems, and soil/litter layer (Asner 1998; Asner
et al. 2000; Ollinger 2011). Canopies with flat, horizontal leaves tend to have higher
NIR reflectance than those with more erect, vertical leaves, depending on the sunsensor geometry. Leaf anatomy and average leaf angle vary widely across species
S. P. Serbin and P. A. Townsend