1.6.3 VI Biophysical Definition
Despite the success of vegetation indices, there are increasing demands to better
define what VI values represent and measure about a canopy. VIs, as measures of
canopy greenness, depict integrative spatial and temporal variations in canopy
biophysics (fractional cover and LAI), leaf physiology (pigments, age, nitrogen),
and structure (leaf thickness, leaf angles and shading). A temporal sequence of VI
values will most likely include simultaneous changes in many of these variables,
and the retrieval of specific variables will either require multiple indices or inverse
radiative transfer models with required implicit assumptions and generalizations
about land cover type, leaf phenology, and biochemistry.
To a large extent VIs are used opportunistically with the aim of finding the best
correlation between a local site experimental data set and a selection of VIs. A VI
correlation made with seasonal LAI will incorporate, and confuse, simultaneous
changes in leaf chemistry and traits that accompany the measured changes in LAI.
There is a tendency to search for the ‘‘best VI’’, although such studies rarely offer
insight into the mechanisms of the VI relationships to specific variables. There are
far less multi-site studies and spatial and temporal extension analyses of VIbiophysical relationships. This contributes to the overall lack of consensus as to
what VIs measure about a canopy and how to further interpret VI values. EVI may
provide a more direct relationship with photosynthesis (GPP) in high biomass
canopies by relying on the more sensitive NIR reflectances that are able to sense to
a greater canopy depth compared with the chlorophyll-sensitive Red band that only
senses the uppermost leaf layer. However, Vickers et al. (2012) noted that VIs can
only be used to determine the upper limits of canopy exchange processes (photosynthesis and transpiration) as environmental drivers, such as water vapor deficits and soil drought, will influence these processes without affecting canopy
spectral properties.
However, it may not always be necessary to deconstruct canopy spectral signals
into their biophysical components (LAI, chlorophyll, etc.). The convergence of
relationships between VIs and tower fluxes across different ecosystems (Figs. 1.10,
1.13) is surprising since, in theory CO 2 and water exchanges can vary considerably
over short time periods; and are related not just to foliage density but environmental variables (PAR, air temperature, vapor pressure deficit, etc.), which can
vary considerably over short time periods. VIs provide both a measure of the
capacity to absorb photosynthetically active radiation, as well as reflect recent
environmental forcings acting on the canopy. Ecological processes tend to adjust
plant characteristics over time periods of weeks or months to match the capacity of
the environment to support photosynthesis and maximize growth. This is known as
the resource balance or resource optimization theory (Field et al. 1995), which
treats photosynthesis or primary production as integrators of resource availability.
32
A. Huete et al.
Despite the success of vegetation indices, there are increasing demands to better
define what VI values represent and measure about a canopy. VIs, as measures of
canopy greenness, depict integrative spatial and temporal variations in canopy
biophysics (fractional cover and LAI), leaf physiology (pigments, age, nitrogen),
and structure (leaf thickness, leaf angles and shading). A temporal sequence of VI
values will most likely include simultaneous changes in many of these variables,
and the retrieval of specific variables will either require multiple indices or inverse
radiative transfer models with required implicit assumptions and generalizations
about land cover type, leaf phenology, and biochemistry.
To a large extent VIs are used opportunistically with the aim of finding the best
correlation between a local site experimental data set and a selection of VIs. A VI
correlation made with seasonal LAI will incorporate, and confuse, simultaneous
changes in leaf chemistry and traits that accompany the measured changes in LAI.
There is a tendency to search for the ‘‘best VI’’, although such studies rarely offer
insight into the mechanisms of the VI relationships to specific variables. There are
far less multi-site studies and spatial and temporal extension analyses of VIbiophysical relationships. This contributes to the overall lack of consensus as to
what VIs measure about a canopy and how to further interpret VI values. EVI may
provide a more direct relationship with photosynthesis (GPP) in high biomass
canopies by relying on the more sensitive NIR reflectances that are able to sense to
a greater canopy depth compared with the chlorophyll-sensitive Red band that only
senses the uppermost leaf layer. However, Vickers et al. (2012) noted that VIs can
only be used to determine the upper limits of canopy exchange processes (photosynthesis and transpiration) as environmental drivers, such as water vapor deficits and soil drought, will influence these processes without affecting canopy
spectral properties.
However, it may not always be necessary to deconstruct canopy spectral signals
into their biophysical components (LAI, chlorophyll, etc.). The convergence of
relationships between VIs and tower fluxes across different ecosystems (Figs. 1.10,
1.13) is surprising since, in theory CO 2 and water exchanges can vary considerably
over short time periods; and are related not just to foliage density but environmental variables (PAR, air temperature, vapor pressure deficit, etc.), which can
vary considerably over short time periods. VIs provide both a measure of the
capacity to absorb photosynthetically active radiation, as well as reflect recent
environmental forcings acting on the canopy. Ecological processes tend to adjust
plant characteristics over time periods of weeks or months to match the capacity of
the environment to support photosynthesis and maximize growth. This is known as
the resource balance or resource optimization theory (Field et al. 1995), which
treats photosynthesis or primary production as integrators of resource availability.
32
A. Huete et al.