Airborne Imaging Spectrometer (AIS) data were flown over the Recluse, Wyoming oil field on September 9, 1984. Processing software was developed at Earth Satellite Corporation (EarthSat) for interactive analysis of the AIS data. EarthSat's AIS processing capabilities include destriping, solar irradiance corrections, residual calculations, geometric resampling, equal energy normalization, interactive spectral classifications and a variety of compressive algorithms to reduce the data to 8-bit format with a minimum of information loss. The in-house photolab facilities of EarthSat can routinely produce high-quality color renditions of the enhanced AIS data. A total of 80 lithologic samples were collected under the AIS flight lines. Correlation (within the atmospheric windows) between the laboratory and the AIS spectra of sample sites was generally poor. Reasonable correlation was only possible in large, freshly plowed fields. Mixed pixels and contrast between the natural and sample's surfaces were believed responsible for the poor correlation. Finally, a drift of approximately three channels was observed in the diffraction grating position within the 1.8 to 2.1 micron quadrant

Dykstra, J. D.

Segal, D. B.

English

NASA Technical Reports Server

~86-11632 
ANALYSIS OF AIS DATA OF THE RECLUSE OIL FIELD, RECLUSE,WYOMING 
Jon D. Dykstra and Donald B. Segal, Earth Satellite Corporation, Chevy 
Chase, MD 26815; (301)951-0104 
ABSTRACT 
AIS data were flown over the Recluse,Wyoming oil field 
on September 9, 1984. Processing software has been developed 
at Earth Satellite Corporation (EarthSat) for interactive 
analysis of the AIS data. EarthSat's AIS processing 
capabilities include destriping, solar irradiance corrections, 
residual calculations, geometric resampling, equal energy 
normalization, interactive spectral classifications and a 
variety of compressive algot'ithms to redui!e the data to 8-bit 
format with a minimum of information loss. The in-house 
photo lab facilities of EarthSat can routinely produce high-
quality color renditions of the enhanced AIS data. EarthSat's 
AIS processing capabilities are available to fello'ii 
investigators through our Chevy Chase, Maryland office. 
A total of 80 lithologic samples were collected under the 
AIS flight lines. Correlation (within the atmospheric 
windows) between the laboratory and the AIS spectra of sample 
sites was generally poor. Reasonable correlation was only 
possible in large, freshly plowed fields. We believe mixed 
pixels and contrast between the natural and sample's surfaces 
are mainly responsible for the poor correlation. Finally, a 
drift of approximately three channels was observed in the 
diffraction grating position within the 1.8 - 2.1 micron 
quadrant. The drift appears to be sinusoidal in nature. 
AIS DATA 
Four flight lines of AIS data, and contemporaneous TMS data, were 
flown over the Recluse,Wyoming oil field. The Recluse oil field is 
located along the northeastern flank of the Powder River Basin. 
Figure 1 is a location map for the Recluse oil field and gives the 
approximate position of the four flight lines. For this flight, the 
AIS spectral range extended from 1.155 to 2.337 microns. 
AIS DATA PROCESSING 
A flow diagram of EarthSat AIS processing software is shown in 
Figure 2. On this figure, EarthSat's processing begins at the 
DESTRIPE position. 
Destripe 
The corrected data, as provided by JPL, still contains a residual 
banding (or striping) along the flight direction. The banding is 
apparently caused by imbalances in the dark current (DC bias) of the 
detectors across the pixel direction of the detector. If a . 
sufficiently large area of homogeneous, spectrally flat material is 
86 
https://ntrs.nasa.gov/search.jsp?R=19860002165 2020-03-23T06:30:45+00:00Z
present along the flight line it is possible to use the average 
radiance values, collected over several along-track pixels, to adjust 
the bias differences between the cross-track elements of the array. 
This is the approach commonly used by JPL, and one which produced the 
"flat field corrected" data for the Cuprite, Nevada scene described in 
the AIS User's Guide. 
Fig. 1 Location Map 
Fig. 2 Flow diagram of EarthSat's 
AIS processing 
Unfortunately, no such area was found on any of our four flight 
lines. Therefore, we used a different approach for the destriping. 
Our approach is based on histogram matching. The assumption is that, 
over the course of a complete flight line, each of the 32 cross-track 
detectors has covered, on the average, very similar surface materials. 
As long as the individual detectors are reasonably well behaved, this 
technique works extremely well in removing intra-band striping. By 
way of example, Figures 3 and 4 show several AIS channels before and 
after destriping. 
This method however can induce serious problems in terms of the 
inter-band radiometrics. Within a given band· (Le., one of the 128 
spectral channels) matching of the 32 AIS detectors is totally 
dependent upon the shape of each bands' unique reference histogram. 
If there are fundamental differences between any two bands' reference 
histograms ,. these differences will be expressed in the output 
(destriped) data. 
In our first attempt to describe the AIS data we chose a single 
detector within each band from which to collect the reference 
histogram. The criteria fOr selecting the reference detector were 
87 
" 
ORIGI Al ~ IS 
POOR QUALITY 
that it show a low variance and appear, in other ways, to be well 
behaved. However, a problem arose because of the presence of an 
inaccurate "dark current correction" applied during data collection. 
The net effect of the erroneous dark current correction was to add 
r andom DC bias values to the individual detectors. Thus, during our 
original Jestriping process, a false bias was applied to each band; 
the magnitude of the bias was proportional to the level of the random 
noise at the detector for which we collected the reference histogra'lH. 
The final result was 128 well-destriped bands; however,in many cases 
each of these bands had bia ses which were equal to or greater than the 
absorption features comprising the desired spectral information. 
Figur 5 is a strongly stretched version of the normalized destriped 
data showing the obvious DC bias diff erences between the spectral 
channels. To prevent the undesirable effects induced by the r andom DC 
biases, we have modified the destrip i ng program t o col lect an average 
r eference his t ogram as an average of all dete ctors, ra ther than for a 
s ingle detector. The r esults (Figure 6) pr oduce much mor e uniform 
i nt er-band radiometrics. 
Fig. 3 Data as received from JPl 
Fig. 5 Erroneous bias effects when 
destriping based on singl. 
detector 
88 
Fig. 4 Data after EarthSat's 
destriping 
Fig. 6 Results of destriping based 
on all available detectors 
Clean 
This procedure was written to interactively remOve bad data 
lines. Bad lines appear as cross-track lines of fully sa~urated. (DN 
4095) or anomalousl} low DN values. Single lines are replaced by the 
average of the two adjacen.t lines on a pixel-by-pixel basis. Multiple 
line corrections are performed by a weighted average of the next 
adjacent good data lines. If these bad data lines are not removed 
they can adversely affect the later compression of the AIS data from 
16 to 8 bits. 
The AIS sensor is fixed orthogonal to the longitudinal axis of 
the aircraft fuselage. Therefore, when the aircraft must crab (point 
into the wind in order to maintain its heading) the resulting yaw 
induces a skew in the geometry of the AIS data. The degree of skew is 
proportional to. the yaw angle. .. 
W~ have made a first order skew correction for those flight lines 
with yaw angles greater than 10 degrees. The correction is based on a 
nearest neighbor resampling along the flight path direction. The 
correction can be likened to looking edgewise·· at a deck of cards and 
sloping the top edge to the left or right to the appropriate number of 
degrees depending upon the sign and magnitude of the yaw angle. 
Solar Normalize 
The incident energy at the top of the atmosphere drops off 
rapidly within the spectral range of the AIS sensor (approximately 1.2 
to 2.4 microns). Using the LOWTRAN program for atmospheric 
calculations, the incident solar radiation ,,'as found to range between 
approxUnately 530 watts/square metre at 1.2 microns down to 
approximately 62 watts/square metre at 2.4 microns. Therefore, with 
increasing wavelength, each consecutive AIS spectral channel is 
receiving a decreasing intensity of incident light. In order to 
compensate for this Unbalance, the pixels of each spectral channel are 
multiplied by a factor proportional to the inverse of the solar 
radiance for the channel. This effectively normalizes the 128 
spectral channels to a common incident solar baseline. 
Equal Ener2V Normalize (Full-Range) 
The purpose of the Equal Energy Normalize (EEN) calculation was 
to remove the effects of differing overall brightness and,thereby, 
accentuate the spectral, band-to-band, information. The algorithm 
used was identical to that described in the AIS User's Guide. 
Equal Energy Normalize (By Quad) 
Within the spectral range of the AIS sensor there are two major 
atmospheric absorption regions, one around 1.4 microns and the other 
around 1.9 microns. The major portions of these features fall almost 
entirely within grating positions 1 and 3, respectively. When 
. calculating the EEN data using all 128 channels, these major features 
tend to dominate the calculations; greatly decreasing the ability to 
detect smaller scale features in the other grating positions. 
Therefore, a procedure was developed which calculates the EEN 
separately for each of the four grating positions. 
89 
·'. 
I 
~~------------------________ ~D~ 
The algorithm used i~ the same as the EEN for the full-range. 
However, instead of basing the calculation on all 12~ spectral 
channels, the calculations are preformed four times, once for each of 
the 32 channel grating positions. Clearly, this procedure produces 
strong discontinuities at the grating boundaries. However, the 
presence of the discontinuities are well worth the greatly enhanced 
signal-to-noise ratio of the data, particularly within the 2.1 to 2.3 
micron grating position. 
Compress 12=>8-bits 
This was the final step in the digital data enhancement. The 
objective was to compress the 12-bit A1S data (contained in a 16-bit 
1*2 format) into an 8-bit word which is then compatible with standard 
image display and printing devices. The compression algorithm was 
carefully designed to minimize the amount of information lost during 
the data compression. 
Several data compression dpproaches have been used during this 
project. The most common was to calculate the mean and standard 
deviation for each of the spectral bands of a given flight line. 
Using the average of the means and thr.ee times the standard deviation 
of the channel with the largest calculated standard deviation, a 
minimum and maximum input value are calculated: minimum equals the 
average mean minus three times the largest standard deviation, the 
maximum equals the average plus three times the standard deviation. A 
linear lookup table is defined into whic.h these minimum and maximum 
values are mapped to 0 and 255, respectively. This lookup table is 
then applied to all the pixels within each of the 128 spectral 
channels. 
RESULTS 
Correlation Between AIS and Lab Spectra 
During the course of this study 80 lithologic samples were 
collected under the AIS flight lines. The samples were analyzed using 
X-ray diffraction, elemental analysis and laboratory spectral 
reflectance measurements. In open homogeneous areas, such as freshly 
plowed fields, it was possible to achieve reasonable correlations 
(within the atmospheric windows) between the A1S spectra and those 
measured in the laboratory. However, for the less disturbed areas it 
has been difficult to achieve much correlation between the lab and A1S 
spectra. We believe that this is largely due to the two phenomena: 
1) The mixture of surface materials within a given pixel,and 2) 
natural vs. sample (laboratory) reflectance surfaces •. The mixture 
problem is location dependent. Recluse is particularly bad in this 
regard. The problem of providing the laboratory spectrometer with a 
"natural" weathered surface is a more universal problem. 
In a heterogeneous region, such as the Recluse study area, it is 
impossible to sample all the surface materials that fall within any 
• given AIS pi"xel. Therefore, the only possible approach is to collect 
a hand sample at a given site which is characteristic of the 
general area. The approximately lOO-square-metre A1S pixel will 
almost always contain many more different types of surface materials 
than are able to be represented in a hand sample. The only sites· 
where this was not the case were in large, homogeneous, freshly plowed 
90 
", 
ORIGI AL PA·~ I 
OF POOR QUALITY 
fields. No t surprisingly, it was within these areas that we have the 
best correlations between the laboratory and AIS spectra. 
The second, and equally difficult problem to control, is the 
unavoidable fact that the AIS data is measuring sunlight reflected 
from the upper few microns of naturally weathered surfaces. When 
unconsolidated samples reach the laboratory, these weathering surfaces 
have been lost. The degree to which the natural chemical and physical 
weathering environments have modified the mineralogy and reflective 
properties of the surface types will adversely affect the correlation 
between AIS and laboratory spectra. 
Gra t ing Drift 
An important observation that came from our interpretation of 
specially processed imagery of the AIS data is an apparent sinusoidal 
drift in the wavelength position of the diffraction grating. Figure 7 
is a photograph of the last sixty or so juxtaposed AIS spectral 
channels. The flight direc~ ion is from the top to the bottom of the 
picture. Note the wavy zone (arrow on Figure 7), approximately 3 
Fig. 7 Approximately 60 AIS channels 
between 1.8 and 2.4 microns. 
Arrow locates 2.0 absorption of 
carbon dioxide. Note wavy 
pattern along flight line. 
channels wide, which moves down the flight line in a sinusoidal nature 
with an amplitude of approximately three channels. This is marking 
the location of the 2.0-micron absorption band due to atmospheric 
carbon dioxide. Clearly, the channel number of this absorption ought 
to be constant. Its wavy appearance on the AIS imagery suggests that 
the electronics controlling the precise wavelength position of the 
diffraction grating are possibly being affected by a signal of the 
observed period and amplitude. There is not, to date, enough 
informat ion to say whether or not this same phenomenon is affecting 
each of the other three grating positions; however, a similar effect , 
although less apparent, is observable in the second grating position 
(1.5 - 1.8 microns). Before more de tailed analyses of absorption band 
placements can be performed, these apparent band shifts need to be 
further understood. 
91 


Analysis of AIS Data of the Recluse Oil Field, Recluse, Wyoming

Abstract

Similar works

Full text

Available Versions

NASA Technical Reports Server