Twelve subscenes were selected from LANDSAT 5, scene 50129-17075 over White Sands, NM. Data set WHITE covers the entire White Sands desert area. Black and white films and hard copy prints of each band in this area were produced. A new command file was written for the interactive digital image manipulation system (IDIMS) to generate pseudocolor pixel prints of LANDSAT Thematic Mapper bands for data from B and A tapes. The program PCMAIN.FOR of principal component analysis and a supplemental program HEDIT.FOR for generating sampled data sets were developed. The procedures for performing component analysis on a subscene by using these programs are described. Modifications to various subroutines are listed. Bright target saturation internal calibration lamp state dependence was examined using calibration data of night scene 50052-02182, WRS 111/112 over Harrisburg, PA

Lee, Y.

English

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Task Assignment 110"^
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September 1984	 N^'	 VD 'L^^' 	 c
er'., n SlopLANDSAT INSTRUMENTS CHARACTERIZATION
GSFC ATR - Dr. J. Barker
SAR Task Leader - Dr. Y. Lee	 o
Task Objective: 	 '%VJ3LVW
The objective of this task is to provide analytical and programming support for both
Landsat-4 and -5 Thematic Mapper (TM) and Multispectral Scanner (MSS) instrument
characterization, with emplias.s on the radiometric performance.
Work Performed:
The following work was performed in the areas indicated.
140 Special Sub-Scer_e Selection
Twelve subscenes were selected from Landsat-5, scene 50129-17075 over White
Sands, NM. Data set WHITE covers the entire White Sands desert area. Black-and-
white films and hard copy prints of each band in this area were produced by LAS.
Color films and prints are in processing. The 256 by 214 pixel eight-cycle
pseudocolor pixel prints were generated on IDIMS for the mid-left subarea that
covers some bright desert area, a small water body, and a part of an airport. Data
sets WS1 through WS6 cover subareas of the White Sands desert. They were created
for further detail scene feature s°udies. Data set WS7 covers a homogeneous water
body. Data set WS8 through WS11 cover some homogeneous ground features.
Particularly, data set WS9 includes a well-defined bright circular area and some
stand-out road features. All subscenes created start at the first line of a forward
scan. The forward and reverse scans misregistration had been corrected by shifting
all forward scans 47 pixels toward the east.
A new command file was written for the Interactive Digital Image Manipulation
System (IDIMS) to generate pseudocolor pixel prints of Landsat Theri,atic Mapper
bands for data from B and A tapes. The file consists of 232 lines of IDIMS image
processing, graphics, and arithmetic commands.
These commands apply pseudocolors to ranges of radiance ,jumbers for each band
and add approMiet- annotation to the image. The current command file can handle
multiple image sizes of 64, 128, or 256 lines and can make 1 to 8 cycles through an
established pseudocolor look-up table fo• a range of 256 radiance values.
In making prints on the Optronics film recorder, a hardware timeout pr-blem was
encountered in the recording of the last 10 lines of each image data set. Systems
personnel were notified of the problem. The SAR analyst was able to get the
recorder to work by changing the size of the gray wedge in the image files.
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Task Assignment 110
September 1984
150 Spectrometry
The progra-a PCMAIN.FOR of principal component analysis and a supplemental
program HEDIT . FOR for generating sampled data sets have been developed. The
procedures of performing principal component analysis an a subscene by using these
programs are described as follows:
1. A 512 by 512 pixel subscene is sampled into 128 by 128 - 4 by 4 pixel grids.
HEDIT.FOR samples the subscene data and calculates the mean µix and
standard deviation (SD) Qik for each grid. An option for generating
radiometrically calibrated data has been included by applying normalized
gains and offsets from either TRAPP repor-. or TIPS QAR report line-by-line
to the image.
2. In PCMAIN.FOR, pure pixel grid masks are generated by using coefficient
variation (CV) thresholding criterion that pure pixel grid is defined as the grid
whose CV, CV= 0/y, is less than a given threshold value.
3. Mean µi and SD Oi for each band are calculated based on the pure pixel
grids of the subscene.
4. The covariance matrix Cij for the subscene is calculated from the equation
1 ^
Cij - n _-N  k (µik -µ i )(µ jk -Pi
wher n is the total number of pure pixel grids, N is the number of bands,
and	 is summing over all pure pixel grids.
5. Eigenvah.,es Ai and eigenvectors t it are obtained by diagonalizing the
covariance matrix Cij
0161 tiJ =	 A i tij
Xi indicates the i elative importance of each p. incipal component.
6. The correlation matiix Yij among the spectral bands is calculated from the
covariance matrix
Cij_
Yid	 (Cij) 1/ 	(C j,) /
7. The correlation matrix Ri ,j between the spectral bands and the transformed
principal components i.-- obtained as
t i j (Ilj> i/2
Rij	 (C )1/
ii
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A.	 /^ ..^ ►,
	 0
Task Assignment 110
September 1984
8. An option for study of principal component analysis on the Z-transform data
is included. An arbitrary normalized mean /d and SD U are chosen as
P = range/2
Q = range /6
range .255
to cover the whole range. Z-transform is defined as
Pik - a ik 17 + P
and
k Pik - PiZi =	 Gi
It normalizes all spectral bands to the same mean and SD. Steps 3 through
will then be performed to get statistics of principal component analysis.
Subscene WS1 through WS11 of Landsat-5 White Sands scene w%re studied. The first
and the sixth components appear consistently in all scenes, ,snd correspond to the
fast and sixth TM Tasseled Cap compon-nts, respectively.
200 TRAPP
Subroutine RCPARREA.FOR has been modified to distinguish Landsat-4 and
Landsat-5 in orbit reference parameter files.
Subroutine RCRDDEFL.FOR has been modified to provide different sets of
reference channels for TRAPP runs.
Subroutines RCDUMPHAT.FOR, ICDUMST.FOR, RCINJDISK.FOR, and
RCLABREAD.FOR lave been modified to change the TAE root to distinguish ADDS
and CALDUMP runs.
310 Bright-Target Saturation
Bright-target saturation internal calibration (IC) lamp rtate dependence has been
examined by using calibration data of night scene 50052-02182, WRS 111/212 over
Harrisburg, PA. Eight scan lines corresponding to eight IC lamp states were plotted
out. Only reverse scans were used because there are not enough background data
after IC pulse in the forward scans. No bright-target saturation was observed in any
plot, including plots of state 111, the brightest IC state. The 111 state in band 1 is
higher than 200 and has been used as t}ie threshold to search for the bright-target
boundary of Landsat-4 TM. This indicates either Landsat-5 has a different response
than Landsat-4 TM, or the IC pulse, which is only about 40 pixels wide, is not thick
enough to trigger the bright-target saturation.
aJ
3/6
lO
Task Assignment 110
September 1984
330 Scan-Correlated Shifts
Task personnel have routinely generated plots of line average background versus
scan number for monitoring scan-correlated shifts. Plots have been generated for
the following Barker specials.
Scene ID WRS Location
40171-17080 33/37 White Sands, NM
50129-17075 33/37 White Sands, NM
40608-15463 20/37 Birmingham, AL
50014-15460 20/37 Birminham, AL
50014-15465 29/39 Pensacola, FL
50052-02182 111/212 Harrisburg, PA
40392-18152 44134 San Francisco, CA
Scan-correlated shifts appear in all scenes and t6- -haracteristics are the same as
reported in the Barker Result and Recommendataion paper. For the Landsat-5
scene, the background after dark current (DC) restoration stays the same as the
background before DC restoration in most of the chapels, but not for several
charnels in bands 1 and S. For es ample, band 1 channels 2, 12, 14, and 16. This
indicates that a strong DC res oration effect exists in these chapels. The
bnt ,,t-target saturation effect was observed in the Landsat-4 White Sands scene,
whic. , is due to a large area of snow covering on the ground.
600 Investigator Support
Task personnel generated a data set of along scan high frequency matrix of
Landsat-4, scene 40109-15140, over Washington, DC, for B. Markham. The ADDS
tape was processed on Nov. 3, 1952.
800 Data Processing
Task personnel developed command procedures for batch job processing of image
data transfer and BRU tape processing.
Task personnel processed three sets of in-orbit data and six BRU tapes.
900 Multispectral Scanner Subsystem (MSS) Coherent Noise Analysis
Histograms were made of the calibrated radaance numbers for the March 31, 1984,
Landsat-4 and April 24, 1984, Landsat-5 detector responses for an area of water.
Empty radiance number bins that were found in the calibrated data were different
for the different detectors. As a result, empty radiance bins are complicating the
analysis of coherent noise, particularly in the I.andsat-5 data, which has a very low
noise variance.
4/6
Task Assignment 110
September 1984
To reduce the impact of the empty bins, the NASA scientist suggested averaging the
magnitudes of the Fourier transformed data for several 512 sample segments
scattered throughout the water areas in each image. Six consecutive 6-line by
512-sample segments were chosen from each band, Fourier transformed, and the six
magnitudes of the Fourier-transformed data were averaged and plotted. SAR
identified the major coherent noise frequency peaks in the plots for both Landsat-4
and -5. The frequencies in the Landsat-4 data correspond closely to those reported
in the literature. There were fewer noise peaks in the Landsat-5 data and the peaks
were of much smaller magnitude than those found in the Landsat-4 data.
In addition, the NASA scientist requested that SAR do a coherent noise analysis of
the unity radiance look-up table (RLUT) data when it becomes available. While
waiting for the data, SAR investigated the possibility of inverting the radiometric
calibration by using the calibration information contained within the ancillary and
image files -)n the A-tapes. Four numbers are used in the calibration process; the
filtered gain and c`fset values, which can be found in the image file records, and the
multiplicative gain and additive offset values, which are found in the ancillary file.
Only the filtered gain and offset values could be extracted from the tapes provided.
The other two values were found to contain zeroes for each detector. It should be
noted that due to roundoff and truncation errors, the calibration process is not
absolutely reversible. Thus, it is preferable to use the unity RLUT data. The NASA
scientist was notified of these problems.
The NASA scientist gave SAR a unity RLUT tape of Landsat-4 data for the
March 16, 1984, MSS scene. Pixel subimages (512 by 512) were extracted from, the
Unity RLUT and the calibrated A-tapes. Examination on a display device revealed
that the unity RLUT data was not of the same area. The NASA scientist was
notified of the problem.
Si	 scant Accomplishments:
On their own initiative and with ATR approval, task personnel d°veloped software for the
principal component analysis with and without Z-transform on both raw and calibrated data.
Problem Areas:
The LAS system was down eight working days during this month.
Forty-five BRU tapes received from Santa Barbara Research Center (SBRC) have a parity
error on them. Task personnel have tried to modify subroutine PCBRUDATA.FOR to avoid
this problem.
Schedule Conformance:
Work on this task has been completed.
5/6
,^ VA4 ^3
a	 rs
Task Assignment 110
September 1984
Work Planned for Next Month:
A new task (132) will be assigned for the new fiscal year.
150 Spectrometry
Task personnel will study the principal (,-)mponent analysis on the classified data.
Deliverables Submitted:
Films and Graphics: Landsat-5 scene 50129-17075 JVhite Sands desert area
Originator:	 Y. P. Lee
Plots: Bright-target saturation IC lamp state dependence
Originator: Y. P. Lee
Plots: Line average background versus scan number
Originators: J. Wang and Y. P. Lee
Listing: Principal component analysis of White Sands subareas
Originator: Y. P. Lee
Listings: Pixel counts of radiance numbers for .14  detectors for Landsat-4 and
-5 for an area of water
Originator: W. Hallada
Listings: Observed coherent noise peaks in Landsat-4 and -5 data for the first
six detectors and for a sample of 512 pixels
Originator: W. Hallada
Graphics: Plots of the average magnitude of the Fourier transformed data for
Landsat-4 and -5 for a sample of 512 pixels from six detectors
Originator: W. Hallada
Graphics: Polaroid prints of pseudocolored TM bands 1, 5, and 7
Originators: W. Hallada and Y. P. Lee {I
Computer Utilization:
The estimated computer time used this month is as !'ollows:
Minutes	 Computer
3090 (wall clock)	 HP-3000 (IDIMS)
200 (wall clock)	 HP-3000 (ERRSAC;
6/6
it


LANDSAT instruments characterization

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