Many studies have shown that radar images have increased classification accuracy over spectral classifications using only LANDSAT Multispectral Band Scanner (MSS) images. It was the objective to determine if a SIRA image taken over Hayfork when used alone or inconjuction with LANDSAT MSS data would increase separation of units not identified by LANSAT spectral mixture models. Areas in the LANDSAT model of varying vegetation density (0 to 50%) that had proven to be accurate by field surveys were compared. It was found in the Hayfork area that SIRA did not increase or help delineation of vegetation or ultramific units over LANDSAT MSS

Adams, J.

Smith, M.

English

NASA Technical Reports Server

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AN EVALUATION OF A SI= IMAGE TO DETERMINE FOREST DENSITY UNDER 
CONDITIONS OF MODERATE TOPOGRAPHICAL VARIATION 
Milton Smith and John Adams 
Department of Geological Sciences 
University of Washington 
Final Report 
Jet Propulsion Laboratory 
Contract 956431 
b f f b h r  \-I5 
INBSA-CB-17S956) AN E V B L D A I I C E  O€ A SJRA N87-13836 .LEASE T O  DETEEEIIIEE FOSEST TENSI'IX U N D X B  
CCNDI'XICNS OF' 4CDERATE I O E C G F A F H I C A L  
V A A I A T I C H  Final Eeport [Washinqtoa U n i v . )  U n c l a s  
10 P CSCL 02E G3/43 4 3 6 3 0  
https://ntrs.nasa.gov/search.jsp?R=19870004403 2020-03-20T13:47:19+00:00Z
. '  
Many s t u d i e s  have shown t h a t  radar images have inc reased  
c l a s s i f i c a t i o n  accurracy over  s p e c t r a l  c l a s s i f i c a t i o n s  us ing  only 
Landsat MSS images (e.g. Ulaby e t  a l .  1982). Our a n a l y s i s  of 
spectral mixture models t o  i d e n t i f y  u l t r amaf i c  rocks i n  t he  
Klamath Mountains near  Hayfork, Ca l i fo rn ia  us ing  only  Landsat MSS 
images demonstrated an i n a b i l i t y  t o  accu r ra t e ly  s e p a r a t e  u n i t s  
t h a t  were vegeta ted  w i t h  more than 50% ground cover (Cooke et a l .  
1985) .  In  addi t ion ,  w e  had d i f f i c u l t y  sepa ra t ing  p a s t u r e  lands  
from x e r i c  spa r se  f o r e s t s  on south s lopes .  
t o  determine i f  a SIRA image taken over Hayfork when used a lone  
o r  i n  conjunct ion w i t h  Landsat MSS da ta  would inc rease  sepa ra t ion  
of u n i t s  not  i d e n t i f i e d  by Landsat s p e c t r a l  mixture  models. Our 
hypothes is  was t h a t  t h e  longer  wavelength of SIRA images could 
I t  was our  ob jec t ive  
con ta in  a s i g n i f i c a n t  and direct response t o  the  su r face  
roughness c rea t ed  by  t h e  vegeta t ion  a r c h i t e c t u r e .  
hypothes is  w e  compared areas i n  t h e  Landsat model of vary ing  
vege ta t ion  dens i ty  (0-50%) t h a t  had proven t o  be accur ra t e  by 
f i e l d  surveys.  These areas were p r imar i ly  t h e  less densely 
vege ta t ed  u l t r amaf i c s  c h a r a c t e r i s t i c  of t h e  area. 
To tes t  t h i s  
An a n a l y s i s  of t h e  second order  su r face  roughness effects 
(e .g .  diaelectric and architecture effects) i n  SIRA images 
r e q u i r e s  t h a t  t h e  primary e f f e c t s  due t o  topography be removed. 
The SIRA image of Hayfork was i n i t i a l l y  rectified and r e g i s t e r e d  
t o  provide  a p ro jec t ion  and r e so lu t ion  equ iva len t  t o  t h e  d i g i t a l  
t e r r a i n  da ta .  To remove t h a t  component of t h e  r ada r  r e t u r n  t h a t  
w a s  s p e c i f i c a l l y  due t o  topography w e  used a radar s imula t ion  
developed by Mike Kobrick at JPL. The s imula t ion  computed t h e  
2 
inc idence  angle  of  the  t r ansmi t t ed  s i g n a l  t o  s u r f a c e  topography 
us ing  d ig i t a l  t e r r a i n  d a t a  and other  parameters related t o  the 
ins t rumenta t ion  and space s h u t t l e  o r b i t .  
image (Fig.  1) i l l u s t r a t e s  t h e  relative coarseness  of  the d i g i t a l  
t e r r a i n  d a t a  by  some of t h e  f l a t  v a l l e y s  and r i d g e s .  
q u a l i t a t i v e  comparison of Fig.  1 w i t h  t h e  o r i g i n a l  SIRA image 
(Fig.  2) i n d i c a t e s  t h a t  t h e  primary f e a t u r e  highlighted i n  the  
image i s  the  topography. 
T h e  predicted rada r  
A 
An empi r i ca l  c a l i b r a t i o n  of t h e  SIRA image was performed t o  
remove t h a t  component i n  t h e  image due s o l e l y  t o  the  topography. 
The c a l i b r a t i o n  cons i s t ed  of  determining t h e  cos ine  response of 
t h e  SIRA image a s  a func t ion  of computed inc idence  angle  us ing  
d i g i t a l  t e r r a i n  data, 
DN r e t u r n  f o r  each p i x e l  rounded t o  t h e  n e a r e s t  degree of 
inc idence  angle .  
when the  d a t a  w e r e  regressed using t h e  fol lowing equat ion:  
The  p l o t  of d a t a  i n  F ig ,  3 i s  t h e  average 
T h e  p o i n t s  i n  Fig.  3 have a c o r r e l a t i o n  of 0.98 
SIRA DN = 116.27 cos( inc idence  angle)  + 73.98 
T h e  observed cos ine  response exh ib i t ed  by t h e  data provides  
evidence of the v a l i d i t y  of  the  d i g i t a l  t e r r a i n  s imula t ion  a s  
w e l l  as  i l l u s t r a t i n g  t h e  a symmetrical d i s t r i b u t i o n  of  s u r f a c e  
angles  i n  t he  a r e a .  Subt rac t ing  each p i x e l  of t h e  image us ing  
Equation (1) from t h e  SIRA image of Fig.  2 r e s u l t s  i n  a SIRA 
image without  t h e  primary response due t o  topography (Fig.  4 ) .  
Although major topographical  v a r i a t i o n s  have been removed 
(Fig.  4 )  topographica l  f e a t u r e s  s t i l l  remain a dominant component 
of the  SIRA image. T h e  only other f e a t u r e s  apparent  i n  the  image 
are bod ies  of  water (e.g. a f e w  lakes and a resevior) .  
F ig .  5 is  an image f o r  comparison where d e n s i t y  of 
3 
vege ta t ion  i s  p ropor t iona l  t o  t h e  image b r i g h t n e s s  (brightest 
areas are 100% vege ta t ion  dens i ty  - dark a r e a s  are 0% vege ta t ion  
d e n s i t y ) .  
s e p a r a t i n g  the  spectral s igna tu re  of vege ta t ion  from t h a t  of the  
shade and s u b s t r a t e .  The v i s u a l  lack of  topographica l  
information i n  Fig.  5 compared t o  Fig. 4 is  an i n d i c a t i o n  t h a t  
t h e  SIRA image is  no t  s i g n i f i c a n t l y  responding t o  changes i n  
vege ta t ion  d e n s i t y  o r  any o t h e r  vege ta t ion  a r c h i t e c t u r a l  changes. 
The vege ta t ion  d e n s i t i e s  i l l u s t r a t e d  by Fig.  5 c l o s e l y  co inc ide  
w i t h  f i e ld  work and d e p i c t  a wide range of  dens i ty  v a r i a t i o n  as 
shown by the  s p a t i a l  v a r i a t i o n  i n  b r igh tness .  
c l e a r c u t s  which appear as dark rec tangular  a r e a s  i n  F ig .  5 are 
no t  observed i n  the  SIRA image (Fig.  2) o r  i n  t he  r e s i d u a l  image 
(Fig. 4 ) ,  i n d i c a t i n g  t h a t  SIRA is no t  s e n s i t i v e  t o  vege ta t ion  
d e n s i t y  i n  t h i s  scene. 
I n  summary, w e  f i n d  i n  the  Hayfork area t h a t  SIRA does no t  
T h i s  image w a s  computed from Landsat MSS data by 
Note t h a t  t h e  
i n c r e a s e  o r  help d e l i n e a t i o n  of vege ta t ion  o r  u l t r a m a f i c  u n i t s  
over  Landsat MSS. I n  genera l ,  these r e s u l t s  suggest  a need t o  
i s o l a t e  t he  phys ica l  causes r e s u l t i n g  i n  inc reased  c l a s s i f i c a t i o n  
a c c u r r a c i e s  found i n  o t h e r  s t u d i e s ,  Many s t u d i e s  i n  f o r e s t  
inventory  have concluded t h a t  c l a s s i f i c a t i o n  accurracy of  f o r e s t s  
us ing  Landsat MSS can be increased s i g n i f i c a n t l y  by  adding 
d i g i t a l  t e r r a i n  d a t a  a lone  (e.g. Sugarbaker e t  a l ,  1 9 8 0 ) .  Our 
r e s u l t s  suggest  t h a t  SIRA images are predominately an expression 
o f  the  topography and not  of the smal l  scale s u r f a c e  roughness 
a s s o c i a t e d  w i t h  vege ta t ion  o r  d i a e l e c t i c  c o e f f i c i e n t s .  
REFERENCES 
Cooke, S., J. Adams, and M. Smith. The use of remote 
sensing in geobotanical mapping projects: mapping ultramafic 
rocks and assoicated vegetation communities in northern 
California. Submitted. 
Sugarbaker, L., T. Gregg, E. Barthmaier, and R. Scott. 
Forest cover type mapping in Eastern Washington with Landsat and 
digital terrain data. 
Regional Commission Grant X10890613. 
using airborne radar and Landsat data. IEEE Trans. Geoscience - and 
Remote Sensing 20:1,42-50, 1982. 
Final Report for Pacific Northwest 
Ulaby, F., R. Li, and K. Shanmugan. Crop classification 
5 
Figure 1 .  Simulated SIRA image using d i g i t a l  terrain of area 
south of  Hayfork, California. 
6 
. -  
Figure 2. SIRA image of area south of Hayfork, California. 
7 
z 
0 
0 ,  
250 
200 
150 
100 
50 
I I I I 
0 10 20 30 40 50 60 70 80 
+ 
90 
INCIDENCE ANGLE 
Figure 3. The cosine relation between computed incidence angle 
from digital terrain data to the average SIRA DN for 
each pixel of the scene in Fig. 2 has a correlation of 
0.98. 
Figure 4. SIRA image with the primary expression of topography 
removed using the empirical cosine calibration of 
Equation 1. 
9 
. 
, *  
Figure 5. Vegetation density resolved from spectral mixtures 
using a Landsat image of Hayfork, California. Image is 
scaled so that white is 100% vegetation density and 
black is 0% vegetation density. 
10 


An evaluation of a SIRA image to determine forest density under conditions of moderate topographical variation

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