Environmental Engineering Reference
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aggregation of heterogeneous vegetation. This aggregated information stands for the
overall development stage of various plants, species within a pixel. It is important for
investigating biogeochemical process, such as water, energy exchange, and carbon
fluxes between biosphere and atmosphere.
Validation is a significant challenge for the study of satellite-derived vegetation
phenology. First of all, the reflectance reached to satellite sensors can be
contaminated by soil background signal and atmospheric influences. The contami-
nation must be discussed or identified during validation. Secondly, scaling from
field observations to satellite image requires multiple simultaneously collected data
at intensive field observation sites. Finally, the key phenological metrics that are
often derived from satellite measurements refer to the onset of greenness and
dormancy and length of the growing season. Although the meaning of these metrics
in many ecosystems is clear, there are many environments in which the precise
interpretation is needed, such as mixed forests, evergreen forests, and dry lands.
17.2.1 Physical Principles for Deriving Phenology from
Satellite Measurements
Remote sensing techniques, which can capture canopy reflectance, allow vegetation
photosynthetic capacity to be assessed. Reflected red energy decreases with plant
development due to chlorophyll absorption within actively photosynthetic leaves.
Reflected near infrared (NIR), on the other hand, will increase with plant develop-
ment through scattering processes (reflection and transmission) in healthy, turgid
leaves (Huete et al. 1999 ). However, the red and NIR radiation reflected from a
plant canopy to a satellite sensor can be contaminated by the effects of atmospheric
particles through absorption and scattering and soil background. A simple measure
of reflected energy is not able to quantify plant biophysical parameters from
satellite measurements. Many spectral combinations or transformations, referred
as Vegetation Indices (VI), are utilized to circumvent the problems of solar irradi-
ance, atmospheric aerosols, and canopy background. These VIs are designed to
enhance spectral reflectance and emissive characteristics of vegetation that are
related to phenological development.
Most of the studies have used satellite-derived VIs to exploit the seasonal
changes in the spectral signature of vegetation photosynthetic activity. Normalized
Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Leaf
Area Index (LAI) are the most widely used indices in satellite monitoring of
vegetation phenology (Ahl et al. 2006 ; Peckham et al. 2008 ; Reed et al. 1994 ;
White et al. 1997 ; Zhang et al. 2004 ). The NDVI, computed from NIR reflectance
and red reflectance Eq. 17.1 , has been related to several biophysical parameters
including the fraction of photosynthetically active radiation (fPAR) (Huete et al.
1997 ), chlorophyll density (Tucker et al. 2001 ), percent canopy cover (Yoder and
Waring 1994 ), and productivity (Prince et al. 1995 ). The EVI Eq . 17.2 is developed
to optimize the vegetation signal with improved sensitivity in high biomass regions
(Huete et al. 2002 ) and to reduce the canopy background signal and atmosphere
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