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Poster Session
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Forest vegetation information of multispectral image
from space and it's false color display tradeoff
The eigenvector tp from the basis of a space in which the covariance matrix is diagonal therefore the principal components are uncorrelated.
The means and various of six Tm bands (expect the thermal infrared band 6) of Dawopu image window Pinquan county are shown in table 2.
The table 2 shows that larger variance appear in three reflectance infrared bands of TM than is visible bands and the most abundant information is given in TM5 band.
Table 2: means and variances of TM digital image (expect band 6)
Dawopu image window Pingquan county
| Channel |
Wavelength (um) |
Mean |
Variance |
| 1 |
0.42-0.52 |
60.252 |
41.226 |
| 2 |
0.52-0.60 |
26.578 |
26.436 |
| 3 |
0.63-0.69 |
24.592 |
74.716 |
| 4 |
0.76-0.90 |
78.801 |
283.478 |
| 5 |
1.55-1.75 |
71.921 |
416.664 |
| 6 |
2.08-2.35 |
25.107 |
114.679 |
The eigenvalues the percentage variances and the cumulative percentage
age variances are calculated and shown in table 3.
Table 3. eignvalues and cumulative percent variance.
| Parameter |
Principal Component |
| 1 |
2 |
3 |
4 |
5 |
7 |
| Eigenvalues |
691.098 |
234.514 |
18.187 |
7.658 |
2.872 |
1.904 |
| Percent variance |
0.772 |
0.245 |
0.019 |
0.0008 |
0.003 |
0.002 |
| Cumulative percent variance |
0.772 |
0.967 |
0.986 |
0.994 |
0.997 |
0.99 |
The first principal component image contains 77.2 percent of the original data variances the first three principal component images contain 98.6 of K-L transform and contain obvious physical shown in color plate 3 there is very abundant vegetation information in color plate 3 that almost is a fine vegetation distribution map.
The interpretation results on vegetation from color plate 3 are shown in table 4.
Table 4. interpretation list for false display of components
PCI ( red ) PC2 (green) PC3 (Blue).
| Tone |
Land use / land Cover |
| Purple |
bare land or spared withered grass land |
| yellow |
shrub (down edge of forest ) or farmer land with irrigation condition |
| Red |
farmer land with nature crops |
| Black |
Chinese pine forest |
| Blue black |
larch forest |
| Dark blue |
mixed forest of birch and Chinese pine |
| Light blue |
birch forest (young growth ) |
| Azure |
meadow |
| Grass green |
birch forest. |
- Trade-off in false-color composite of the rationing images.
Pingquan county is located in high mountain region with heavy shadows that hinder the interpretation of vegetation We need to develop a technique to remove the shadows and extract the vegetation information.
According to the concept of the optimum index factor (OIF),
Eq.
Where si standard deviation of rationing image for order i, | R | is the absolute value of correlation coefficient for color order j. By random test we get the rationing image subset [TM/TM3,TM3/TM2,TM2/TM1] whose OIF value is the maximized and make false-color display for this rationing image subset (appropriate color red , green, blue )in which the mountain shadows were removed and the land cover information was extracted successfully in order to compare the effects between the false color composition of rationing image (TM4/TM3,red,TM3/TM2) green TM2/TM1blue and original image we also given the false color composition of original images ( TM5,red, TM3, Green, TM2 , blue) which are shown in color plate 4.
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