Remote Sensing of Terrestrial Photosynthesis
513
for calculating photosynthesis from remote sensing products can be as simple
as a description of a linear relationship between absorbed solar radiation
and net primary production (e.g., Monteith 1977) or can include more or
less detailed treatments of plant physiology (e.g., Sellers et al. 1992a)
and radiation (e.g., Gerstl and Borel 1992) and turbulent transfer (e.g.,
Dickenson et al. 1986).
The central role of models highlights the three major challenges in the
remote sensing of photosynthesis. First, ecological and physiological models
of photosynthesis were not generally developed to utilize remote sensing
data, resulting in a mismatch between the inputs required by some of the
existing models and the outputs available from satellite observations. The
process of reformulating physiological and ecological models in terms of
parameters easier to relate to radiances needs to be balanced with the
development of new sensors and algorithms for deriving relevant parameters
(Ustin et al. 1993). Second, the quality of the remote sensing data must be
uniformly high. Effects of calibration changes, atmospheric transmission,
solar elevation, and canopy architecture still present major challenges. Third,
many remote sensing techniques, especially satellite techniques, provide
data on spatial scales where even the smallest spatial unit can be very
heterogeneous, consisting of many plants or even contrasting ecosystems.
24.3 Remote Sensing of Photosynthetic Capacity
Ecosystem photosynthetic capacity, potential photosynthetic CO 2 fixation
under optimal conditions, is controlled by LAI, the photosynthetic capacity
of individual leaves, and the spatial organization of leaves. Each of these is
potentially accessible through remote sensing. In addition, a number of
physical principles and ecological regularities often appear to simplify the
situation, such that a single index may capture the combined effects of all
three variables. The mechanistic basis for these simplifications appears to
involve a combination of physical, biochemical, and ecological factors, discussed below. To understand these simplifications and some of their implications, it is useful to first consider the way the measurements are made.
24.3.1 Absorbed Radiation
Leaf area index is one of a number of parameters that can be derived from a
comparative assessment of reflectance in the red, where green leaves are
strong absorbers, and the near infrared, where green leaves are highly
reflective (Fig. 24.1). In addition to LAI, methods based on the red-near
infrared contrast can yield estimates of crop yield (Fig. 24.2; Monteith
1977), green biomass (Fig. 24.2), annual net primary production in natural
513
for calculating photosynthesis from remote sensing products can be as simple
as a description of a linear relationship between absorbed solar radiation
and net primary production (e.g., Monteith 1977) or can include more or
less detailed treatments of plant physiology (e.g., Sellers et al. 1992a)
and radiation (e.g., Gerstl and Borel 1992) and turbulent transfer (e.g.,
Dickenson et al. 1986).
The central role of models highlights the three major challenges in the
remote sensing of photosynthesis. First, ecological and physiological models
of photosynthesis were not generally developed to utilize remote sensing
data, resulting in a mismatch between the inputs required by some of the
existing models and the outputs available from satellite observations. The
process of reformulating physiological and ecological models in terms of
parameters easier to relate to radiances needs to be balanced with the
development of new sensors and algorithms for deriving relevant parameters
(Ustin et al. 1993). Second, the quality of the remote sensing data must be
uniformly high. Effects of calibration changes, atmospheric transmission,
solar elevation, and canopy architecture still present major challenges. Third,
many remote sensing techniques, especially satellite techniques, provide
data on spatial scales where even the smallest spatial unit can be very
heterogeneous, consisting of many plants or even contrasting ecosystems.
24.3 Remote Sensing of Photosynthetic Capacity
Ecosystem photosynthetic capacity, potential photosynthetic CO 2 fixation
under optimal conditions, is controlled by LAI, the photosynthetic capacity
of individual leaves, and the spatial organization of leaves. Each of these is
potentially accessible through remote sensing. In addition, a number of
physical principles and ecological regularities often appear to simplify the
situation, such that a single index may capture the combined effects of all
three variables. The mechanistic basis for these simplifications appears to
involve a combination of physical, biochemical, and ecological factors, discussed below. To understand these simplifications and some of their implications, it is useful to first consider the way the measurements are made.
24.3.1 Absorbed Radiation
Leaf area index is one of a number of parameters that can be derived from a
comparative assessment of reflectance in the red, where green leaves are
strong absorbers, and the near infrared, where green leaves are highly
reflective (Fig. 24.1). In addition to LAI, methods based on the red-near
infrared contrast can yield estimates of crop yield (Fig. 24.2; Monteith
1977), green biomass (Fig. 24.2), annual net primary production in natural