ınbul 2004 
to three- 
bles, and 
ovided by 
je used to 
'arameters, 
study area 
Terometric 
| explain 
; of these 
veen field- 
)). 
rious fuel 
variability 
number of 
own fuels) 
re detailed 
y are to be 
| remotely- 
number of 
were not 
indicating 
extraneous 
ure of fit. 
idicate that 
ittedly, the 
o establish 
Is. Further 
ie. physical 
> array of 
processing 
mized for 
accurate 
nple, some 
vere due to 
ough it 1s 
uture work 
the forest 
be used to 
parameters 
of forest. 
ind smoke, 
f fuels data 
begin to be 
campaigns 
ta will be 
s. 
ut and the 
ers can be 
e, resulting 
re behavior 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
Future research will be focused on analysis of multifrequency, 
polarimetric IFSAR data acquired over different forest types. A 
rigorous model validation will be carried out to determine the 
sensitivity of the model form to changes in forest type and stand 
density. 
7. REFERENCES 
Andersen, H-E, R. McGaughey, S. Reutebuch, and B. Mercer. 
2004. Estimation of forest inventory parameters using 
interferometric radar. First International Digital Forestry 
Workshop, Beijing, China, June 14-18, 2004. (in preparation) 
Beukema, S.J., D.C. Greenough, C.E. Robinson, W.A. Kurtz, 
E.D. Reinhardt, N.L. Crookston, J.K. Brown, C.C. Hardy, A.R. 
Stage. 1997. An introduction to the fire and fuels extension to 
FVS. In: Teck R., M. Moeur, M. Duffy, W. Hulslander, J. 
Brock, and J. Adams, eds. Proceedings of the Forest Vegetation 
Simulator Conference, February 3, 1997, Fort Collins, CO. 
General Technical Report INT-373. Ogden UT: USDA Forest 
Service Intermountain Research Station. 
Brown, J.K., and C. M. Johnson. 1976. Debris Prediction 
System. Ogden UT: USDA Forest Service Intermountain Forest 
and Range Experiment Station, Fuel Science RWU 2104. 28 p. 
Dutra, L., M. Elmiro, C. Freitas, J.R. Santos, J.C. Mura, and B. 
Filho. 2002. The use of multi-frequency interferometric 
products to improve SAR imagery interpretability and 
classification by image fusion. In: Anais do II] Workshop em 
Tratamento de Imagens, Junho 2002, Belo Horizonte, Minas 
Gerais, Brazil. 
Finney, M.A. 1998. FARSITE: Fire area simulator — model 
development and evaluation. Research Paper RMRS-RP-4. 
Ogden UT: USDA Forest Service Rocky Mountain Research 
Station. 
Hagberg, J., L. Ulander, and J. Askne. 1995. Repeat-pass SAR 
interferometry over forested terrain. /EEE Transactions on 
Geoscience and Remote Sensing 33(2):331-340. 
Hofmann, C., M. Schwibisch, S. Och, C. Wimmer, and J. 
Moreira. 1999. Multipath P-band interferometry — first results. 
In: Proceedings of the Fourth International Airborne Remote 
Sensing Conference and Exhibition/ 21" Canadian Symposium 
on Remote Sensing, Ottawa, Ontario, Canada. 
Hussin, Y.A., R.M. Reich, and R.M. Hoffer. 1991. Estimating 
slash pine biomass using radar backscatter. /EEE Transactions 
on Geoscience and Remote Sensing 29(3):427-431. 
Imhoff, Marc. 1995. Radar backscatter and biomass saturation: 
ramifications for global biomass inventory. /EEE Transactions 
on Geoscience and Remote Sensing 33(2): 511-518. 
Mercer, B. 2001. Comparing LIDAR and InSAR: What can you 
expect? In: Fritsch/Spiller, eds. Proceedings of the 
Photogrammetric Week 2001, Stuttgart, Germany, pp. 2-10. 
Mercer B., J. Allen, N. Glass, S. Reutebuch, W. Carson, and H. 
Andersen. 2003. Extraction of Ground DEMs Beneath Forest 
Canopy using P-band Polarimetric InSAR. Proceedings of 
ISPRS Joint Workshop of ISPRS WG 1/3 and 11/2, Three 
dimensional Mapping from InSAR and LIDAR, Portland 
Oregon, USA 17" — 19th June 2003. Unpaginated CDROM. 
Mercer, B. 2004. Personal communication. 
Mette, T., K. Papathanassiou, I. Hajnsek, and R. Zimmermann. 
2003. Forest biomass estimation using polarimetric SAR 
interferometry. Proceedings of the PollnSAR Conference, 
Frascati, Italy, January, 2003. 
Mura, J., L. Bins, F. Gama, C. Freitas, J. Santos, and L. Dutra, 
2001. Identification of the tropical forest in Brazilian Amazon 
based on the DEM difference from P- and X-band 
interferometric data. In: Proceedings of the Geoscience and 
Remote Sensing Symposium 2001, IGARSS "01, Sydney, 
Australia. IEEE, vol. 2. pp. 789-791. 
Scott, J.H., and E.D. Reinhardt. 2001. Assessing crown fire 
potential by linking models of surface and crown fire behavior. 
Research Paper RMRS-RP-29. Fort Collins CO: USDA Forest 
Service, Rocky Mountain Research Station. 
Treuhaft, R. N. and P. R. Siqueira. 2004. The calculated 
performance of forest structure and biomass estimates from 
interferometric radar. Waves in Random Media 14: S345-S358. 
8. ACKNOWLEDGEMENTS 
The authors would like to thank the Precision Forestry 
Cooperative at the University of Washington College of Forest 
Resources, USDA Forest Service Pacific Northwest Research 
Station, Washington State Department of Natural Resources, 
and the Makah Indian Tribe for providing data and support for 
this research.