8
3.2. PAR
PAR is derived from radiation data. The relationship between PAR and radiation is
explained by June 2002 as: PAR = 0.5 x global radiation 5
Units of PAR and global radiation are Mega Joule per m
2
MJ m
-2
. Since radiation data from Geophysics and
Meteorology Agency BMG are sunshine
duration and not in MJ m
-2
, the data were converted first. Equation 5 is used to do the
conversion.
N n
b a
Q Q
A s
+ =
6 where Q
s
= radiation reaching the surface MJ Q
A
= radiation reach on the top of the atmosphere MJ
n = actual sunshine duration N = maximum sunshine duration
a = 0.29 cos θ
b = 0.52 a
and b are constants depend on position of the area.
3.3. fAPAR
fAPAR calculation in NetPro uses some equations based on previous researches and uses
NDVI value as the input. fAPAR equations used are shown in the next table.
Table 2. fAPAR equations used by Net Pro v. 1.0
fAPAR equation Source
in June, 2004
1.075 NDVI - 0.08
7
Ochi and Shibasaki 1999
1.25 NDVI - 0.025
8
Ruimy et al. 1994 1.62 NDVI - 0.04
9
Lind and Fensholt 1999
1.67 NDVI - 0.08
10
Prince and Goward 1995
3.4. LAI LAI calculation in NetPro also uses NDVI as
the input. The equation is based on Ibrahim 2001.
LAI = 12.74 NDVI + 1.34 11
3.5. NPP
PAR and fAPAR result from NetPro are used as input for NPP calculations see Equation
1. NPP estimation using dynamic e requires
minimum and maximum daily temperature. This data is included in Serang daily meteorological
data file from Geophysics and Meteorology Agency
BMG see Appendix 3. There are CO
2
concentration, temperature increase and nitrogen condition choices in this
process. This simulation used present CO
2
concentration, 350 ppm; no temperature increase; and lowest choice of leaf nitrogen concentration,
115 mmol m
-2
. Before the model gives the result, daily and hourly respiration simulation is needed.
The model writes the simulation in two csv files which were prepared before the simulation.
IV RESULT AND DISCUSSION 4.1 NDVI
NDVI classification was the first step used for further analysis.
In satellite image processing for this research, missing data, zero or negative NDVI
were classified as “Class 1” where zero NDVI was not analyzed further. They represents non-
vegetated area. Bare soil and rocks generally have positive but lower NDVI values close to 0
meanwhile water and clouds have negative NDVIs.
Cloudiness in both 2002 and 2004 could affect the estimation of NDVI. Cloud was
classified to Class 1 NDVI or zero NDVI. The real NDVI under the cloud could not be
estimated. Area not covered by cloud seemed had NDVI change, so it was not possible and
improper to guess one image’s NDVI under the cloud based on the other image’s NDVI i.e.
guess the 2002 image’s NDVI under the cloud based on 2004 image’s NDVI for the same
place. The solution for this problem was to make union of both image’s cloud. Therefore, 2002
image had both the cloud of 2002 and 2004, and also 2004 image had both the cloud of 2002 and
2004. Before this step was taken, cloudiness in 2004 was higher than in 2002.
The number of NDVI classes per year was the same as the number of NPP classes per year.
There were seven NDVI classes in 2002 and eight NDVI classes in 2004 see Figure 6 and 7.
9
Table 3. Class of NDVI of the Cidanau watershed, 2002 and 2004
2002 2004
Class NDVI
Classification NDVI
Area ha
NDVI Area
ha
1 0 0 8115 0 8115
2 0-0.1 0.052 2234
0.051 2278 3 0.1-0.2
0.151 2758 0.155 3316
4 0.2-0.3 0.254 4303
0.249 5866 5 0.3-0.4
0.339 3746 0.326 1798
6 0.4-0.5 0.427 289
0.437 48 7 0.5-0.6
0.506 1 0.543
15 8 0.6-0.7
0.650 10 Average
0.141 0.126 The highest NDVI class in 2004 was 0.650,
which resulted in the highest NPP class. The NDVI classification can be seen at the
Table 3. NDVI was classified according to the range values. Average of an NDVI class was
obtained to give an input for NetPro model. The average of NDVI for overall watershed were only
0.141 2002 and 0.126 2004 or only in Class 3 range.
In 2002, the site was dominated by Class 4 and Class 5. Meanwhile, in 2004 it was
dominated by Class 3 and Class 4. The obvious difference was the area of Class 5 was high in
2002 but then dropped in 2004. This fact would affect the result of NPP estimation explained
later.
The position of lower and higher NDVI can be analyzed visually by comparing its
distribution with the land use of Cidanau. Because the main interest in Cidanau is about the
maintenance of private garden, the NDVI of private garden is important. This NDVI value is
used to estimate NPP of the research site.
The position of lower NDVI, the Class 1 and Class 2, in 2002 and in 2004 was mainly in
paddy field and forest in higher land figure 8- 12. The lower NDVI classes occurred in forested
area were caused by cloudiness in the satellite image see figure 4 and 5. Higher NDVI in both
research years occurred in forest and Rawa Danau preserve as well as in private garden land.
Higher NDVI classes are Class 4 and higher. The LAI of higher NDVI classes were in forest LAI
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