3.B. Remote sensing and atmospheric acquisitions
We will acquire pixel-based reflectances and indices from MODIS and Hyperion,
derived from in-situ atmosphere measurements and corrections from nearby AERNOET
sunphotometer sites. We will use available validation datasets from the AERONET-based
Surface Reflectance Validation Network (ASRVN, Wang et al., 2009) to obtain independent
atmosphere corrected assessments of seasonal greening. The Belterra site is close to the
Tapajos tower site.
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- we will compare the seasonal profiles of standard MODIS vegetation products, which are
operationally corrected at coarse scales, with higher quality MODIS product versions that are
independently corrected for aerosols with in-situ atmosphere measurements from sun
photometers located at AERONET sites. The AERONET-based Surface Reflectance
Validation Network (ASRVN, Wang et al., 2009) provides a more exact correction of satellite
data, enables better fine-scale cloud filtering of satellite data, and provides hourly
measurements of direct and diffuse solar radiation.
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we will use a seasonal data set of Hyperion images.
Scaling of leaf optical measurements: hemispherical leaf optical measurements will be
made with a full-range (350 – 2500nm) ASD spectroradiometer and Licor integrating sphere
that provides direct measures of reflectance, transmittance and absorption spectra. These
spectra will made for samples from harvested branches + leaves (kept moist and measured
the same day). A portable ASD Field-Spec radiometer with spectral range in the visible and
near-infrared (350-1100 nm) and with a leaf clip apparatus will also be used for
measurements of in-situ leaf spectra. These measurements will be conducted to ensure the
integrity of measurements made from the harvested samples.
The narrowband spectral measurements will be used to derive hyperspectral indices
sensitive to leaf chlorophyll, including the first derivative of the red edge slope at 700-740nm
and the narrow-band versions of vegetation indices, such as EVI. MODIS vegetation
products are derived from broadbands which are unable to capture fine chlorophyll spectral
features and their variation with leaf phenology (see comparison leaf age spectra figure, in
which the more intense red absorption feature of younger leaves and their stronger red-NIR
contrast (from 675nm to 750nm) are masked by the broader red bands common to MODIS
and other satellite sensors). This shows that hyperspectral measures would best depict the
stronger vigor (and metabolism) of younger leaves and the phenological dynamics of
broadband ‘greenness’ measures (from young to old leaves) may behave differently than the
hyperspectral ‘greenness’ measures.
In this study, we aim to relate hyperspectral measures of leaf phenology with concurrent leaf
physiology to best determine how to couple leaf optics with leaf function. Although spectral
absorption in the red is normally correlated with chlorophyll, other factors will need to be
considered including seasonal variations in the presence and extent of epiphyll coatings on the
leaf (epiphyll activity is most pronounced in the humid rainy season and their presence increases
‘red’ absorption, independent of chlorophyll amounts and/or photosynthesis activity (Toomey et
al., 2009).
At the canopy scale, remotely-sensed phenologic dynamics will additionally be influenced by
multiple leaf scattering and multiple species (with some degree of asynchronous behavior). The
high LAI levels common in tropical rainforests cause saturation in the photosynthetically active
spectral region, including the chlorophyll-sensitive spectral regions. Studies have shown that in
such high LAI environments, the best correlations with chlorophyll occur with narrowband spectra
away from the intense absorption regions, either at ~710nm or in the longer wavelengths of the
green peak area (Carter and Knapp 2001). Thus sensitivity to chlorophyll at the canopy scale
would require narrowband spectral measurements.
Although, not a direct measure of chlorophyll, the NIR spectral region exhibits very high multiple
leaf scattering and becomes very sensitive to leaf dynamics in a forest canopy (up to an optical
depth of LAI=8). Thus, broadband NIR measurements have been shown very useful in depicting
seasonal ‘greenness’ variations in the Amazon and other tropical regions, and forms the basis of
the EVI satellite product. As the EVI does not saturate, it provides (for the first time) satellitebased measurements of spatial and temporal variations in vegetation greenness in high biomass
tropical biomes. In this study we aim to further make use of the EVI signal and uncouple the
mechanisms of EVI responses, since the EVI responds to (1) LAI, (2) leaf phenology, including
epiphylls, and (3) canopy roughness (i.e., sunlit/shaded canopy fractions). These combined
factors are not unlike those that eddy covariance flux measures are sensitive to.
Satellite data show a pronounced NIR reflectance increase and a small red reflectance increase
through the dry season in the Amazon. While the NIR region is relatively unaffected by
atmosphere contamination, the red band is very sensitive and the dry season increase could be a
result of a build-up in aerosols from biomass burning or it could be a result of new leaf emergence
from leaf flushing (see figure X that shows younger leaves with higher red broadband reflectance.
- Assuming the overall roughness of the canopy is largely seasonally invariant, we will test
the relative roles of LAI and leaf phenology in explaining observed seasonal optical
dynamics, primarily in the NIR. A net increase in LAI would cause higher NIR
reflectances; as would a constant LAI but with replacement of older epiphyll-covered
leaves by younger leaves; as would a constant LAI but with the phenologic-optical
development of the young leaves {if leaf flushing occurred all near the beginning of the
dry season – in July-August- this would be plausible. I didn’t explain and we need to
verify this, but as leaves get older and thicker, their NIR inceases, causing higher Vis, yet
lower fluxes?}; and would some combination of all of the above.
- The red increase due to aerosol or due to leaf phenology test.
How to scale leaf hyperspectral and canopy hyperspectral to broadband canopy forest?