The problem of data integration in oceanography is discussed. Recommendations are made for technique development and evaluation, understanding requirements, and packaging techniques for speed, efficiency and ease of use. The primary satellite sensors of interest to oceanography are summarized. It is concluded that imaging type sensors make image processing an important tool for oceanographic studies

Nichols, D. A.

English

NASA Technical Reports Server

4.6 OCEANOGRAPHIC SATELLITE R M T E  SENSING: 
REGISTRATION, RECTIFICATION, and MIA MTE6iUfIQH REQUIREHENTS 
David A. Nicbls  
Jet Fropulaicrn Laboratory 
IHSROD?JCTIOE: 
Oceanographic remote sensi3g is sti l l  i n  its beginning stages of develop- 
nent. Resrilts from t h e  e a r l y  meteorological satellites suggested t h a t  Para- 
meters of oceanographic  i n t e r e s t ,  s u c h  as sea surface t e m p e r a t u r e s ,  might  
r e a d i l y  be o b t a i n e d  by sa te l l f te  r e m o t e  sens ing .  The a c c u r a c y  of t h e  data, 
however, sas found t o  be unacceptable. Later instruments,  such aa those flown 
on  Seasa t4 ,  demons t r a t ed  t h e  f e a s a b i l i t y  of o b t a i n i n g  n e a r l y  all-neather 
ooserviztions of wind speed and d imc t io~ ,  wave height,  sea surface temperature  
and e l e v a t i o n  These data, along w i t h  those obtained by t he  latest generat ion 
of w e -  - h e r  satell i tes,  a p p e a r  t o  be o f  much greater u t i l i t y .  The r e l a t i v e l y  
l i m i t e d  experience w i t h  t hese  systems, bowever, p laces  much of oceanographic 
remote seneing a t  a s t age  where reaults are still being v e r i f i e d  and evaluated. 
Calibrated geophysical parameters are ava i l ab le  for many of the data items, but  
t h e  q u a l i t y  and s igni f icance  of tbese observat ions is only now beginniw t o  be 
understood. 
There are maay r e a s o n s  why o c e a n s  r emote  s e n s i n g  h a s  lagged behind 
me t e o m l o g i c a l  and terrestrial a p p l i c s  t i ons .  They canno t  a l l  be addres sed  
here, but a significant Impediment has beeq t h e  lack of  appiopr ia te  tools f o r  
acquiring, processing and analyzing remotely sensed data. Unt i l  very r ecen t ly  
only a f e w  oceanographic i n s t i t u t i o n s  had any semblance of an  image procewing 
c a p a b i l i t y  - a capab i l i t y  which is mandatory for processing and viewing image 
data and extremely I-seful  for processing and displaying nonimage data. T h i s  
lack of computerized tools for remotely sensed data processing, e spec ia l ly  data 
i n t e g r a t i o n ,  has been &n impediment  t o  a l g o r i t h m  development  and s e n s o r  
v e r i f i c a t i o n .  The lack of a p p r o p r i a t e  mechanisms f o r  a c q u i r i n g  t h e  da t a  
c o n t i n u e s  t o  cause problems but  is c u r r e n t l v  be ing  addressed,  t o  a l i m i t e d  
rfegree, by the  O c e a n  I i l o t  System1. 
Operatioaal 
appl ica t ions  are i n  the  best pos i t i on  to  dictate  Cata in t eg ra t ion  requirements,  
but operat ional  oceanographic app l i ca t ions  usua l ly  r equ i r e  real- o r  near-real- 
t i z e  da ta .  Data i n t e g r a t i o n  s e r v i c e s ,  which are g e n e r a l l y  q u i t e  time 
consuming, are  t h e r e f o r e  precluded.  For t h i s  r ea son ,  data  i n t e g r a t i o n  i s  
l a r g e l y  a problem p e r t i n e n t  t o  research oceanography and r e q u i r e m e n t s  of  
r e s e a r c h  pro . iec ts  v a r y  w i d e l y  i n  t h e  r e q u l r e a e n t s  area. W i t h  t h e  l a u n c h  o f  
S e a s a t  i n  1978 and w i t h  t h e  improved z i c u r a c v  and a v a i l a b i l i t y  of  data f rom 
meteorological satell i tes,  ocean remote sensing is enter ing  a period i n  which 
t h e  necessary a n a l y s i s  t o o l s  are b e i n g  b u l l  t 2nd i n v e s t i g a t o r s  are becoming 
more f a m i l i a r  w i t h  t h e  v a r i o u s  s e n s o r  systems.  T h i s  shou ld  lead t o  more 
i n v e s t i g a t o r  concern  w i t h  data i n t e g r a t i o n  r e q u i r e m e n t s  f o r  s c i e n t i f i c  and 
ope ra t iona l  purposes. 
T a b l e  1 presents  a summary of t h e  primary s o t e l l i t e  sensors  of i n t e r e s t  t o  
oceanography. (See also ~ i l s c n 5 . )  Since micrbwave sensors  are so prevalent ,  
r e s o l v i n g  t h e  d i f f e r e n t  I F O V s  and s u b s a t e l l i t e  cove rages  becomes e x t r e m e l y  
d i f f i c u l t .  All present ly  operat ing oceanographic satellites pr imar i ly  Contain 
imaging-type sensor3.  T h i  mekes Image p r o c e s s i n g  a n  i m p o r t a n t  t o o l  f o r  
present-day oceanographic sfudies.  
Firm data in t eg ra t ion  requirements are d i f f i cu l t  t o  p in  down. 
105 
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ORIGINAL PAGE IS 
OF POOR Q U m  
TABLE 1 
Summary of s e n s o r s  of pr imary i n t e r e s t  t o  oceanographers  
I I 
I I I 
I 
SATELLITE SENSOR I TYPE ! CkVANELS 
I I PRIMARY 
I H A G I N W  I I GEOPHYSICAL 
PONIHAGING I IFOV I PAMMETERS 
I I I I I 
I I 
I 
Seasat ;Radar Ai- ;Act ive  i13.5 G H z  INonImaging i2.4-12 km )Wave h e i g h t  
GEOS-3 I&wter I I ! (depends o n  ! W i n d  speed 
ISea State) ISea s u r f a c e  
I I h e i g h t  
I 
I I 
I 
I(ALT) I 
I 
I I I 
1 .  
I I 
1 
I 
I 
I 
Seasat l scann lng  : P a s s i v e  I 6.6 GHz :Imaging I120 x 79 km Isea surface 
NIHBUS-7* I N u l t l -  I i10.7 GHz !(Low rate) I 74 x 49 km I temp. 
:Channel 1 118.0 GHz I I 43 x 28 km :Wind a w e d  
I Mlc mwave I 121.0 GHz 
1 Radiome :er 137.0 GHz 
I(sMMR) I I (Vertical 
I i 1 t a l  polar-  
I I 
I I I & horizon- 
I 
I I i t y )  I 
I I I 
Seasat ISeasat-A !Ac t ive  114.6 GHz 
I 38 x 25 km :Water i a p o r  
I 22 x 14 km !Liquid 
I I water 
I I 
I 
I 
i I 
I I 
I I 
Nonimaging I 16 - 23 km :Wind Speed 
~~ 
I x  :Wind Direc- 
I h i g h l y  v a r i -  I 
I t r y  
I I I Satel l i te  I 
Iscattern-I I I I 36 - 93 km I t i o n  
Imeter I I 
I(SASS) I 
I I 
:Ape r tu re  I I I :Dependent o n l S p e c t r a  
(Radar I 1 I !Ground P r o  -!Sea Ice 
i I 
I I Iable geome- I 
I 1 I 1 I 
I I 
I I I I 
I 
Seasat ISyn the t i c IAc t ive  I 1.275 GHz :Imaging I '25 meters !Wave 
I I 
I 1 ( SAR 1-1 Icessing 1 
Nimbus-7+ f C o a s t a l  I P a s s i v e  I .43 3-. 453 I Imaging .825 kn I C h l  orop hy l  1 
I I 
I 
I Zone 1.510-.530 I I concen t r a -  
!Color I 1.540-.560 I I t i o n s  
I scanne r  I 1.660-,680 I I 
I(CZCSj I !.700-.800 I 
I 11b.5-12.5 I I 
I 
I 
I I I 
I I I 1 
1 I 
IResolu- i 13.55-3.93 I I s l i g h t l y  
i t i o n  Ra- I 110.5-11.3 I I less 
NOAA-6/7* :Advanced : P a s s i v e  lO.58-0.68 !Imaging (1.1 km 
TIROS-N ;Very  High: i.725-1.1 1 ;Channel :. 
ldlometer 1 111.5-12.5 i I I 
Ocean Color 
Diffuse 
a t t e n u a t i o n  
c o e f f i c i e n t  
Cloud c o v e r  
Sea s u r f a c e  
t e m p e r a t u r e  
I 1 I I 1 (AVHRRI-I I- I 
NOTE: Nimbus-7 and  NOAA-6 a n d  7 are  t h e  o n l y  c u r r e n t l y  o p e r a t i o n a l  
NOAA-6 and TIBOS-N c o n t a i n  o n l y  4 c h a n n e l s  
sa te l l i t es  
Data integration rsquirements for  oceanographic remote se~?iq$l,6,7 CR.I be 
placed ic  several catec;oriea. Comparison of one observation w i t h  a?lother a t  
the same geographic location is important as i t  is in all disciplines. O b s e r -  
vatiLons mus t  be earth-looated and interpolated i n  orCer to  either in i t ia l ize  or 
t e s i  numerical mcdels. Observatioiis must be earth-located t o  measure magnitude 
and motion of featrlres. Finally, observations must be located, interpolated, 
and map-projected i n  order t o  provide maps depicting two-dimensional 
dis tri bu t ions, 
Comparison of observations is an importani aspect of not only disciplinary 
research b u t  a l so  senaor valiZition. Observations of a physical phenomenon 
from a given sensor need t o  be compared w i t h  observations of the same 
phenomenon from other sensors which may be on the same sa ta l l i t e ,  on a differ- 
e n t  s a t e l l i t e  o r  on a b  a i r c r a f t  platform. High-rate obserdations, s r c h  as  
AVHRR sea surface temperatures ( 1  pixel  - 0.8 km) need t o  be compared w l t h  
other observhtions of the same parameter fYom a low-rate sensor such as Seasat 
SMMR ( t  pixel - 18 x 28 km). 
The different IFOV slzes and shapes and sensor coverages on even the same 
sa t e l l i t e  make observations d i f f icu l t  to  compare (See Table 1). Added t o  t h i s  
i s  the fact that  t h e  ocean is a dynamic system so that  comparivuns of observa- 
t ions taken a t  d i f f e ren t  times (even a feu hours apar t )  requi re  temporal 
interpolation as well 89 spatial interpolation before va l id  comparisons can be 
made, 
Correcton of one sensor w i t h  da ta  f r o 3  another leads t o  an addi t ional  
integration requirement. A single sensor is often incapable of making all the 
measurements necessary t o  derive a pa r t i cu la r  geophysical parameter. For 
example, t o  make efficient path-length corrections to  the Seasat Altimeter aea 
surface eievation measurements, Seasat SMMR water vapor content estimates are 
used where available. The SMMR is also used t o  ad jus t  scat terometer  (SASS) 
returns for atmospheric attenuation effects. If an outside correction source 
i s  on a d i f f e r e n t  s a t e l l i t e  or even i n  an e n t i r e l y  d i f f e r e n t  form (e.&, map 
form) t h e  data integration problen: becomes even more acute. 
Feature identification, measurement and ncvement tracking requires earth- 
located data. Examples of these operations are found i n  the current warm ring 
analyses8,g bein, performed a t  severai institutions. Sa te l l i t e  projections do 
not  a l low distance measurements i n  the image i n  l ine  and  sample coordinates, 
A t ransformation from l i n e  and sample to  geographic coordinates ( l a t i -  
tude/longitude) m u s t  be obtained and used. I t  is a l s o  necessary t o  compute 
this t r a n s f o r m t i o n  t o  measure fosturc movement through time. The dynamic 
ocean system prec ludes  s imple  scene l scene  r e g i s t r a t i o n  and s i m p 1 2  
differencing. 
The two-dimensional. display of sensor observations implies mapping. Vaers 
a re  accustomed t o  reading maps w i t h  spec i f i c  01 ' en ta t ions ,  projections,  and 
cartographical characteristics. Satel l l tes  have yet t o  provide uaps directly 
w h i c h  s a t i s f y  these predictions. I n  fact, many sa t e l l i t e  projections are so 
distorted that i t  is unreasonable to  expect investigators t o  become acclistomed 
t o  them. I t  becomes necessary, therefore, a t  some stage of analysis, to place 
t t e  data i n t o  a su i tab le  map project ion and c rea t e  a map using conventional 
cartographic met hods (albeit  automated). 
107 
Happing o f  i m a g e r y  d a t a  seems f a i r l y  s t ra ightforward.  However, i t  is 
d s o  impor t an t  t o  create maps which are based on data from noniaaging sensors 
s u c h  a s  t h e  Seasat A l t i m e t e r 3 .  F h e s i  da ta  are, i n  q e c e r a l ,  
randomly spaced. For a number of reasons, a p a r t i c u l a r  sample may be mi:31ng 
or wreadable, I n t e r p o l a t i o n  t echn iques  f o r  establ ish;% a r eazonab l s  value 
are needed. A l t e r n a t i v e l y ,  c a r t o g r a p h i c  t e c h n i q u e s  a r e  r e q u i r e  A ''or 
i n d i c a t i n g  m i s s i n g  v a l u e s ,  y s t  p r o v i d i n g  a n  e a s i l y  readable map. Ocecu 
ographers  are concerned no t  on ly  w i t h  two-dimensional d i s t r i b u t i o n s  bat  al SO 
with  three-dimensional d i s t r i b u t i o n s  shown ei ther  s y n o p t i c a l l y ,  time e rei aged, 
or as a t iae cont inuum. The o n l y  e f f e c t i v e  way t o  d i s p l a y  t h e  f o u r -  
dimensional i n f o r s a t i o n ,  89 t h e  l a t t e r  requirement  implies ,  is v i a  anipat! in 
The art  and s a l e n c e  o f  computer g r a p h i c s  p rov ides  the  technoZogica1 bass  for 
a n i m a t i o n  I t  2s necessary,  though, to  map-project, register, t empora l ly  and 
s p a t i a l l y  i n t e r p o l a t e ,  and reformat t h e  data t c  t a k e  advantage of t ha t  techno- 
logy. 
(See F i g u r e  1.) 
P o s i t i o n a l  accuracy r equ i r emen t s  for oceanography are n o t  as stringent as 
for terrestrial remote s e n s i n g  bu t  are more i n  l i n e  w i t h  me teo ro log ica l  . .ppli- 
c a t i o n s .  Using p r e s e u t  nav1gat:on ( e a r t h - l o c a t i o n )  t e c h n i q u e s  f o r  polar- 
orbiting Image data sets2, accLracic.3 are adequate for all b u t  micro- and f i n e -  
sca le  s t u d i e s .  Open-ocean p o s i t - c  ?a1 c o n f i d e n c e  is p r o b a b l y  wi th i . ,  5 
k i lometers  w i t h  a c c u r a c y  b e i n g  w i t h i n  a k i l o m e t e r  n e a r  l andmarks .  These  
a c c u r a c i e s  are  a d e q u a t e  f o r  niacm- and m e s o s c a l e  s tud ie s .  Addit ional  posi- 
t i o n a l  accuracy i n  open-ocean ar tas  would enable much more a c t i v i t y  in f i n e -  
scale research. Table 2 p r e s e n t s  the  spatial scales associated w i t h  v a r i o u s  
classes of oceanographic research. 
I 
I RESEARCH FEATURE S I Z E  
I I 
1 I I 
macroscale g l o b a l  f 
I mesoscale 1 10-1000 km 
2-5 km I f i n e - s c a l e  I I 
1 nicroscale < 1 kr 
1 I 
I I 
I 
I I I 
I 
1 
I I 
I I I I 
TABLE 2 
Comparison of oceanographic r z z - a r c h  areas a A  spatial scales. 
AREAS FOR RESEARCH AND DEVELOPMENT 
Data I n t e g r a t i o n  is a problen:  f o r  o c e a n o g r a p h y  just a s  f o r  a n y  o t h e r  
d i s c i p l i n e .  Areas where progress is needed inc lude  technique development and 
e v a l u a t i o n ,  u n d e r s t a n d i n g  r e q u i r e m e n t s ,  and packag ing  t echn iques  f o r  speed,  
e f f i c i e n c y  and  ease of use. Same s p e c i f i c :  t o p i c s  f o r  f u t h e r  research and  
development are p:esented below. 
1 os 

TECHNICUE EVALUATION BND DEVELOPMENT 
- Evaluate techniques f o r  e s t a b l i s h i n g  geophysical 
values in amirs of missing d a t a  
- Eva lua te  techniques f o r  temporal interpolat ion 
- Compare a136 evaluate slternative navigation strategies. 
- Develop algorithms f o r  automated coastl ine detectiob and correla- 
t i o n  w i t h  vector-coded c o a s t l i n e  data (e.g., World Data Banks I 
and X I ) .  
FURTHER CEVELOPHENT OF REQU1:REWNTS 
- Define spatial scale requirements f o r  fine-scale stadies. 
9 DePine requirements f o r  band-to-band r e g i s t r a t i o n  of mu1 t i b a n d  
imagery. 
- Define requirements for muftisensor da t a  Integration, where 
sensors may be tn the same apte l l i t e ,  a different  s a t e l l i t e ,  G r  
on a i rc raf t  and satellites. 
9 Define data integration reqiiSments for operatlorral applications. 
PACKAGING AND SYSTEH D E S I G N  
- Produce a well-organized, e f f i c i e n t l y  accessed, c o a s t l i n e  and 
landmark f i l e  fo r  use i n  i n t e r a c t i v e  a d j u s t m e n t s  t o  navigat ion 
parameters. 
- Develop automated methods of acquiring, managing, and u t i l i z ing  
o r b i t a l  psrameters and clock a d j u s t s e n t s  provided by t r a c k i n g  
f acU i t ies .  
= Develop analysis systems w i t h  u s e r - f r i e n d l y  interfaces enabling 
researchers  t o  r o u t i n e l y  perform da ta  i n t e g r a t i o n  t a s k s  i n  a 
short period of time. .,lese sys t ems  would a l so  provide the basis 
for. evaluating new integratizn techniques as they are  developed 
i n  research activit ies.  
Provide t r a n s p o r t a b l e  sof tware  s o  t h a t  tire m i n i m u m  amount of 
e f f b .  t has t o  be expended in d u p l i c a t i n g  da ta  i n t e g r a t i o n  
c a p a b i l i t i e s  a t  var ious  sites. T h i s  is important  because t h e  
research nature of oceanogr3Dhic remote sensing d a t a  integration 
i m p l i e s  decent ra l ized  a c t i v i t i e s .  Also, t h e  w i d e  v a r i e t y  of 
sensors of in te res t  suggests that  centralized data integration 
capabi l i t ies  w l l l  not exis t ,  a t  l e a s t  u n t i l  full-scale discip- 
l i n a r y  data systems a r e  b u i l t .  
110 
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111 


Oceanographic satellite remote sensing: Registration, rectification, and data integration requirements

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