Agriculture Reference
In-Depth Information
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Figure 5.2
A scanning electron
micrograph of transverse view of a
mature broad-bean leaf magnified
420
. The upper half of the leaf
in
terior is more disorganized, and
extensive intercellular air spaces
expose the surfaces of mesophyll
cells directly to air contact (from
Troughton and Donaldson, 1972).
×
[61],
Line
——
-2.1
——
Norm
PgEn
of green leaf density (figure 5.4). Thus, the determinants of the spectral
reflectance of plant canopies include physiological condition of leaves,
their structural arrangement and density within the plant canopy, and
the underlying substrate, when the plant canopy is open (Tucker, 1980a).
Sensitivity of satellite data to these characteristics of leaves becomes the
basis for monitoring drought conditions using satellite data.
[61],
Ve
getation Indices
The spectral properties of vegetation canopies, mentioned above, make it
possible to monitor vegetation dynamics and their spatial and temporal
variability using various remote-sensing platforms. Satellite data-based de-
tection of vegetation health and stress depends on the strong relationship
between simple transforms of reflected red and near-infrared energy and
the intercepted or absorbed photosynthetically active radiation (APAR) of
the plant canopy. Several such transforms, referred to as vegetation indices
(VIs), are based on the unique spectral signature of green vegetation in the
red and NIR portions of the spectrum and form the basis for quantitative
assessment of vegetation condition using satellite data. According to Jack-
son and Huete (1991), VIs can be divided into two groups: slope-based and
distance-based VIs.
Sl
ope-Based Vegetation Indices
The slope-based VIs are simple arithmetic combinations that exploit the
contrast between the spectral response patterns of vegetation in the red and
NIR portions of the electromagnetic spectrum. Some of these vegetation
indices include the ratio vegetation index (RVI), normalized difference
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