ABSTRACT: 
weight (R? = 0.77). 
1. INTRODUCTION 
Accurate estimates of canopy height, canopy base height, 
canopy bulk density, and canopy fuel weight would improve the 
data layer creation process for wildfire simulation models such 
" as FARSITE (Finney, 1998) or future fire spread models. 
Previously, these data layers were generated using the, output 
from stand-level growth models such as the Forest Vegetation 
Simulator (FVS), which depend upon a tree list to drive the 
simulations (Beukema et al, 1997). Since the stand-level 
estimates generated from these models are based upon a 
relatively sparse sample of inventory attributes, they will be 
subject to sampling error and will be unable to capture 
variability in stand structure at finer spatial scales over the 
landscape. If such variables could be accurately estimated using 
remotely-sensed data, in a spatially explicit format, the 
application of fire spread models to landscapes would be 
significantly improved. 
Synthetic aperture radar (SAR) is an active sensing technology 
that emits and records the reflection of microwave radio energy. 
Airborne SAR systems typically collect data from very high 
flying heights, allowing them to collect data at a rate of 
approximately 1000 km?/hour with a cost that ranges from $10 - 
$80/km? for typical X-band digital surface models (Mercer, 
2001). The information content of radar data in forested terrain 
varies depending upon the wavelength of the transmitted pulses 
— energy with short wavelengths (— 1 cm) is reflected from the 
canopy surface while radar energy with longer wavelengths (~ 1 
m) penetrates the foliage in the canopy and reflects from large 
branches, tree stems and the terrain surface. Microwave remote 
sensing, in contrast to optical remote sensing, can penetrate 
| | cloud and smoke cover, allowing data collection in most 
  
* Corresponding author. 
KEY WORDS: Forest fire, mapping, radar, SAR, interferometer 
ESTIMATING CANOPY FUEL PARAMETERS IN A PACIFIC NORTHWEST CONIFER 
FOREST USING MULTIFREQUENCY POLARIMETRIC IFSAR 
Hans-Erik Andersen * *, Robert McGaughey °, Stephen Reutebuch ^, Gerard Schreuder ^, James Agee “, Bryan Mercer © 
* University of Washington, College of Forest Resources, Seattle, WA, 98195 USA — 
(hanserik, gsch, jagee)@u.washington.edu 
® USDA Forest Service, Pacific Northwest Research Station, Seattle, WA, 98195 USA — 
(bmcgaughey, sreutebuch)@fs.fed.us 
¢ Intermap Technologies Corp., Calgary, Alberta, Canada T2P 1H4 — bmercer@intermaptechnologies.com 
ISPRS Commission III, WG I1I/3 
Fire researchers and managers need accurate, reliable, and efficiently-obtained data for the development and application of crown 
fire behavior models. In particular, reliable estimates of critical canopy structure characteristics, including canopy bulk density, 
canopy height, canopy base height, and canopy fuel weight are required to accurately map fuel loading and model fire behavior over 
the landscape. The use of polarimetric interferometric synthetic aperture radar (IFSAR), a high-resolution active remote sensing 
technology, provides for accurate and efficient estimation of crown fire behavior variables over extensive areas of forest. In this 
study, estimates of crown fuel variables were developed from the polarimetric backscatter and interferometric information 
(elevation, coherence and phase) for an IFSAR dataset acquired within a coniferous forest in western Washington State, USA. 
Multiple regression analysis showed that plot-level IFSAR-based canopy fuel estimates were highly correlated with field-based fuel 
measurements of canopy height (R? 2 0.89), canopy base height (R? 2 0.85), canopy bulk density (R* = 0.74), and canopy fuel 
weather conditions. The resulting image represents the intensity 
of the radar backscatter throughout the illuminated region. 
While previous studies have shown that SAR backscatter 
amplitude can be used to estimate forest biomass (Hussin et al., 
1991), it has been noted that the biomass saturation limits for 
even long-wavelength SAR systems (~ 100-150 tons/ha) are too 
low to reach levels present in temperate closed forests (~300 
tons/ha) (Imhoff, 1995; Mette et al., 2003). 
The availability of three-dimensional interferometric radar 
(IFSAR) data in recent years has the potential to significantly 
expand the applicability of radar analysis for forest structure 
analysis. Radar interferometry uses the difference in phase, or 
phase shift, between two radar images acquired from slightly 
different locations to acquire information relating to the 
elevation angle to an imaged point, which is used in 
conjunction with the range information to determine the three- 
dimensional location of this imaged point (Hagberg et al, 
1995). Varying the wavelength of the emitted energy will allow 
for collection of different three-dimensional structure data - 
sensors emitting pulses with short wavelength measure the 
canopy surface while sensors with longer wavelength will 
collect information about sub-canopy and terrain features. The 
difference between the canopy elevation (X-band) and 
underlying terrain elevation (P-band) yields a canopy height 
model that represents a spatially-explicit description of canopy 
structure (i.e. volume, height, biomass, canopy fuel density) 
over a given area of forest. It has been shown that 
inteferometric observables, such as coherence and phase, arc 
more sensitive than radar power (backscatter) to forest 
structural parameters and biomass over a large range of forest 
types (Treuhaft and Siqueira, 2004). The use of IFSAR 
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