International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
0.26
0.24
0.22} ;
$ 02 |
0.18 PRY DW
016% i 2
; Wavelength/um ‘
b. Vegetation
ur ——- QUAC
— g— FLAASH
3
=
e
Wavelengtl/um
c. Water body
0.205 1
0.2
wo LE 105 [oe
ä
$ 019
=
0.185 :
05 1 1.5 2
Wavelengthfum
d. Asphalt road
Figure 3. Contrast of reflectance spectrum curve
As the fourth band of SPOT-5 is beyond the band scope of wild
radiometer, in order to ensure the integrity and aesthetics of the
comparison chart, during the resampling process of measured
spectral reflectance curves, the reflectance of the part (the
fourth band) beyond the band scope shall be given man-made
based on past experience and trends of the curve, thus
comparative analysis mainly focuses on comparing the
differences of the first three bands. We can conclude from the
figure that the measured reflectance curve of the first three
bands is more similar to the curve after the Model FLAASH
atmospheric correction.
Soil reflectance is related to soil types, water content and
surface roughness and other factors, and there are no obvious
peaks and valleys of reflectance of soil surface under the
natural state. The farmlands in the study region have just been
harvested with straws covering the soil surface, so there is a
valley at the 0.65 um of the three curves, similar to vegetation.
However, it is not so different from the near-infrared
reflectance. As shown in Figure 3(b), the vegetation spectral
begin to decrease from the green band (0.55 um), a small valley
at the red band (0.65 um), which is due to the strong absorption
10
effect of chlorophyll to red light and strong reflect action of
chlorophyll to green light; then there is a peak of reflection at
the rear-infrared (0.84 um), which is subject to the effect of the
structure of vegetation leaf cells, the unique characteristic of
vegetation. Under the case that the reflectance of both models
are slightly smaller than the measured reflectance, accuracy of
FLAASH is higher than that of QUAC. The water body in the
study area includes sediment, chlorophyll and other substances,
and the is relatively shallow, also influenced by the bottom
materials and the spectral transmittance of the water, so at the
visible-near infrared, reflectance rises with the increase of
wavelength instead of reducing. Reflectance curve of asphalt
road surrounding the farmland rises slowly at the visible-near
infrared band, and then becomes gentle after that. From Figure
3(d)we can see that the value of the measured reflectance curve
is larger, and the reflectance after FLAASH atmospheric
correction is more similar to the characteristics of the measured
spectral.
3.3.3 RVI comparative analysis: The vegetation index (VI) is
the index mainly reflecting the differences of vegetation among
visible light, near infrared reflectance and soil background. In
the field of remote sensing application, the index of various
vegetations in certain conditions can be used for illustrating the
growth situation of vegetation quantitatively. In order to
evaluate the influences of the types of atmospheric corrective
models on calculation of vegetation index, here the RVI is
taken as the example; the three types of RVI value including
the original DN value, the value of FLAASH and QUAC after
atmospheric correction have been compared with each other.
vegetation
Figure 4. Contrast of the value of RVI
water asphalt soil
As shown in figure 4, for various ground features, the value of
RVI after atmospheric correction is a little bit higher (excluding
waters) than the calculation of original value of DN. Therein,
the value of RVI after atmospheric correction increases
obviously in the filed of vegetation, and the value of RVI after
atmospheric correction based on the model of FLAASH nearly
reaches 2.5. Thus it can be seen that the atmospheric correction
could conspicuously increase the differences of RVI between
the vegetation-covered area and non-vegetation covered area,
which makes the vegetation information gets more prominent.
4. CONCLUSIONS
This paper makes a summary and comparison between Model
FLAASH atmospheric correction and Model QUAC
atmospheric correction, and on this basis the contrastive
analysis of visual effect, reflectance spectral curve effect and
RVI effect. The results of the trail show that: the images after
the two model atmospheric corrections appear to be brighter
visually and contrast is enhanced; while the reflection spectral
characteristics of the surface features are largely restored and
emphasis the vegetation information, indicating that the two
models can be applied to the SPOT-5 images in southern hilly