5
Remote sensing of vegetation can use aeroplane or satellite to carry the sensor and other
instruments. This research used Landsat 7 ETM images and ER Mapper 6.4 software to do
satellite image processing. ER Mapper has a ready
to use equation to calculate NDVI data. Arc View 3.2 software is used to manage and
display the data as NetPro model required. Normalized Difference Vegetation Index
NDVI is derived from band 3 red and band 4 near infra-red values of Landsat 7 ETM data
see Table 1.
2.4.2. Normalized Difference Vegetation Index NDVI
Normalized Difference Vegetation Index NDVI is one of several remote sensing
vegetation indices that use red and near-infrared reflectance. The ER Mapper software provides
NDVI equation that is ready to run for Landsat image processing. The equations developed by
Rouse et al. 1974 in Jensen, 2000.
red NIR
red NIR
NDVI +
− =
3 Table 1. Landsat 7 ETM characteristics
Spectral Resolution μm
Spatial Resolution m at nadir
1 blue 0.450-0.515
30 x 30 2 green
0.525-0.605 30 x 30
3 red 0.630-0.690
30 x 30 4 near IR
0.750-0.900 30 x 30
5 mid-IR 1.55-1.75
30 x 30 6 thermal IR
10.40-12.50 60 x 60
7 mid IR 2.08-2.35
30 x 30 Band
8 pan 0.52-0.90
15 x 15 Sensor Technology
Scanning mirror spectrometer
Swath Width 185 km
Date Rate 250 images per day
31450 km
2
Revisit 16 days
Orbit and Inclination 705 km
sun-synchronous Inclination=98.2
o
. Equatorial crossing 10.00
a.m ±15 min. Launch
April 15, 1999 Jensen, 2000
6
Chlorophyll a absorbs wavelengths of 0.43
μm and 0.66 μm, and chlorophyll b absorbs wavelengths of 0.45
μm and 0.65 μm or mostly in the blue and red portion of electromagnetic
spectrums Jensen, 2000 causing leaves to look green. This kind of interaction and properties
between leaves and electromagnetic spectrums are the basis of vegetation indices observation
through remote sensing. NDVI is correlated with fraction of PAR absorbed fPAR Coops et al.,
1997, and therefore, it is used as an input of NPP estimation.
NDVI describes difference of leaf’s reactions
to red and infrared energy. A healthy leaf absorbs red energy for photosynthesis, transmits, and
reflects infrared energy. The combination between red and near-infrared reflectance
measurement is more highly correlated with biomass than either only red or near-infrared
measurement Jensen, 2000. The greater the red absorption is, and the least the infrared reflection
is, indicating greener leaf. Generally, NDVI is known as “greenness index” of a leaf.
Figure 2. Sketch of hypothetical additive reflectance from a two-leaf layer canopy Jensen,
2000.
Interaction between near-infrared energy and the leaf is controlled by the spongy mesophyll
cells. Heating effect of near-infrared energy can cause irreversible denaturation of its protein.
Near-infrared energy is transmitted by the upper leaf layer, and then transmitted again and
reflected by the lower layer back to the upper layer. Therefore, the greater the number of leaf
layers is, the greater the near-infrared reflectance, and its spectral properties may provide
information on plant senescence and stress Jensen, 2000 See Figure 2. Leaf’s treatment to
infrared radiation is explained in the following paragraph.
For example, the leaf’s transmittance is 50 and its reflectance is 50 of incident radiant flux
Φ
1
. Leaf 1 reflects 50 of Φ
i
back R
1
and transmits it onto Leaf 2 T
1
. Leaf 2 then transmits 50 of T
1
T
2
and reflects it back to Leaf 1 R
2
. Leaf 1 once again transmits 50 of R
2
T
3
and reflects 50 of R
2
R
3
back to Leaf 2. Fifty percents are of R
3
reflected back to Leaf 1 R
4
and another 50 is transmitted through Leaf 2 T
4
. Fifty percents of R
4
are then transmitted by Leaf 1 T
5
and another 50 is then reflected back R
5
. R
1
= ½ Φ
i
T
1
= ½ Φ
i
T
2
= ½ R
1
= ¼ Φ
i
R
2
= ½ R
1
= ¼ Φ
i
T
3
= ½ R
2
=
8 1
Φ
i
R
3
= ½ R
2
=
8 1
Φ
i
T
4
= ½ R
3
=
16 1
Φ
i
R
4
= ½ R
3
=
16 1
Φ
i
T
4
= ½ R
4
=
32 1
Φ
i
R
5
= ½ R
4
=
32 1
Φ
i
Additive reflectance from Leaf 1 and Leaf 2 is R
1
and T
3
is ½ Φ
i
+
8 1
Φ
i
=
8 5
Φ
i
= 62.5 Φ
i
based on Jensen, 2000.
2.5. LAI
