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4. APPLICATION TO AVIRIS IMAGERY
Twenty eight AVIRIS scenes were selected using the quick look data at the Jet
Propulsion Laboratory. They were transformed to apparent reflectance by
dividing by the solar constant. The description of spectra in terms of
reflectance as opposed to radiance greatly equalizes the wavelength
dependence. However it increases the effect of noise.
Table 2 lists the
data sets used, and the scene type.
The selection largely
spans the natural
. variability
represented in the AVIRIS data sets, with the
exception of clouds.
The two
spruce forest scenes (920616B and 920615B) are
for overlapping areas,
as was
discovered only during
image processing.
Table 2. AVIRIS
Data
Scenes and Surface Types
Flight
Run
Scene
Catalog name
type of scene
920602A
9
8
Moffett Field
suburb, shallow water
920826B
3
2
Maricopa farm
agriculture
920828B
13
1
Los Alamos
geology, town
920827B
2
5
Rodgers Dry Lake
geology
921119B
9
8
Tampa Bay
city, water
920603B
2
3
Cuprite
geology
920826B
5
1
Camp Pendleton
water, military base
920615B
2
3
Harvard Forest
forest
920612B
2
5
Indian Pines
agriculture, forest
920531C
6
1
Death Valley
geology
920603B
14
3
Cima volcanic field
geology
920708B
1
2
Gainesville, FL
lake, vegetation
920819B
2
1
Denver
suburb, agriculture
920828B
2
5
San Juan Mtns
snow, geology
920602A
6
2
Jasper Ridge
suburb, vegetation
920826B
4
1
Fort Huachuca
a.f.base, geology
920616B
2
1
Spruce forest
forest, clear cuts
920820B
6
1
Pleasant Grove
agriculture
921117D
2
30
Jackson, TN
agriculture, forest
921119B
5
4
Tampa Bay
island, shallow water
920826B
6
2
San Joaquin
agriculture
920531C
2
1
Owens Valley
geology
920820B
7
1
Dunnigan, CA
agriculture
920819B
10
14
San Berdardino
agriculture
920708B
5
1
Gainesville, FL
town, vegetation
920621C
2
1
Blackhawk Island
ag, forest, water
920615B
8
1
Spruce forest
forest, clear cuts
920820B
8
3
Davis, Webster
agriculture, town
Since 28 AVIRIS images represent 4 gigabytes of data an efficient analysis
strategy was needed. First a scene showing considerable variability in
surface types (Moffet Field) was analyzed. It was found that 9 variables
(spectral intervals) described E to within 0.1%. Then a 1% sample of the 28
scenes (every 100th pixel) was analyzed. Finally, the basis function
expansion to level 20 was subtracted out from each scene to select "bad"
pixels, with the worst 1% in terms of residuals being saved from each. Then
these were added to the original 1% sample, so that the significance of poorly
described spectra was multiplied by a factor of 50. Even this requires only
approximately 20 basis functions to describe the AVIRIS signal very well, as
illustrated in table 3.