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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
approach here the end of the detector where the quantum
efficiency is very low; the model is very constrained here and
adding additional spectral lines would mean only to generate a
very high error in the center wavelength of this band.
Table 1: Requirements and Results for APEX Median Radiance
requirements.
|nm|
|nm]
SSIr
|nm|
SSI r
|nni|
GSDr
[m]
GSDc
[ml
380
387.73
15
16.30
3.65
3.65
400
400.55
15
8.80
3.65
3.65
470
469.85
10
8.97
3.65
3.65
500
500.53
10
9.92
3.65
3.65
515
515.59
9
9.59
3.65
3.65
580
581.77
5
4.06
3.65
3.65
650
650.89
5
2.86
3.65
3.65
700
698.83
5
3.51
3.65
3.65
750
749.61
5
4.27
3.65
3.65
780
781.45
5
4.76
3.65
3.65
850
850.98
10
5.89
3.65
3.65
900
901.81
10
6.73
3.65
3.65
940
937.16
10
7.30
3.65
3.65
980
983.54
10
8.04
3.65
3.65
1000
1000
10
8.29
3.65
3.65
Xr
|nmj
SNRr
SNRc
NeAL R
NeALc
F
380
314
716.35
2.23e-4
0.98e-4
-
400
681
692.27
1.32e-4
1.30e-4
-
470
484
924.07
2.41e-4
1.27e-4
-
500
737
897.31
1.44e-4
1.18e-4
-
515
901
879.91
1.14e-4
1.17 e-4
-
580
554
557.14
1.69e-4
1.68 e-4
.
650
436
444.64
1.87e-4
1.83 e-4
-
700
313
450.99
2.19e-4
1.52 e-4
-
750
197
604.96
4.98e-4
1.63 e-4
-
780
186
623.29
6.44e-4
1.5 4 e-4
0.80
850
134
629.56
1.21 e-3
1.5 7e-4
0.61
900
138
590.81
8.56e-4
1.99 e-4
-
940
118
239.08
3.12e-4
1.54 e-4
-
980
156
176.11
5.38e-4
4.75 e-4
-
1000
121
78.89
6.53e-4
1.01 e-3
-
FHtsr «tosorptövity
Figure 4: Customized filter for APEX Median Radiance
Requirements.
implies that the instrument has the potentiality of performing
much better than what requested. This is clearly a great
advantage especially in terms of SNR and noise-equivalent-
delta-radiance because it will allow (a) to detect a signal much
higher than its corresponding noise and (b) to distinguish
between radiance levels that might differ only for a few percent
of chemical contents.
Table 2: Binning pattern for the APEX Median Radiance
requirements.
1
2
3
4
5
6
7
8
1
35
132
160
172
214
243
258
34
50
140
167
178
215
243
258
9
10
11
12
13
14
15
271
278
291
299
304
310
312
271
278
291
299
304
310
312
Error Budget
Figure 5: Error Budget For APEX Median Radiance
Requirements.
3.2 Dedicated science application: Chlorophyll/Red-Edge
The optimization algorithm can be applied to specific science
application and this case study illustrates how this is possible.
Let’s assume that it is necessary to identify the chlorophyll
content within leaves with an accuracy of 2%, in the visible-
near-inffared spectral region. A few reflectance canopy profiles
of leaves with a content of chlorophyll between 10% and 80%
are shown in Figure 6. (The PROSPECT 9 model has been used
in order to generate reflectance curves in step of 2% chlorophyll
content). When a leave has more than 60% in chlorophyll
content is very hard to distinguish the variations in reflectance
because of the high absorption; therefore only curves up to 60%
of chlorophyll have been considered.
Nevertheless 80% of the requirements have been met before
applying any filtering solution. The Figure 5 reports the error
budget for every requirements; a very positive error means that
the requirement has been satisfied and, on the other side,
Figure 6: Canopy Reflectances with variable Leaf Chlorophyll
Content. The content is indicated in microgramm/cnT.