343 
FOREST HEIGHT ESTIMATION FROM INDREX-II L-BAND POLARIMETRI INSAR 
DATA 
Q. Zhang 2 ’ *, J.B. Mercer 2 , S.R. Cloude b 
2 Intermap Technologies Corp., #1200, 555 - 4 th Avenue SW, Calgary, AB, Canada T2P 3E7 - (qzhang, 
bmercer)@intermap.com 
b AEL Consultants, 26 Westfield Avenue, Cupar, Fife KYI5 5AA, Scotland, UK - aelc@mac.com 
Commission I, WG 1/2 
KEY WORDS: Forestry, SAR, Mapping, Vegetation, Estimation, DEM 
ABSTRACT: 
This paper presents some results of forest canopy height estimation from L-Band polarimetric InSAR data. Three approaches have 
been tested using a set of PolSARproSim simulated data as well as real data from the INDREX-II campaign. The approaches are: 1) 
DEM differencing, 2) 2-D search, and 3) Combined. The results show that the DEM differencing approach tends to underestimate 
the forest height by one third, while the other two approaches can achieve about 90% accuracy when there is sufficient ground return. 
1. INTRODUCTION 
Forest canopy height is one of the important parameters that can 
be utilized for purposes of indirect forest biomass estimation 
allometry [Mette, et al., 2004]. Recent advancement in 
Polarimetric SAR Interferometry (PolInSAR) [Cloude and 
Papathanassiou, 1998; Papathanassiou and Cloude, 2001; 
Cloude and Papathanassiou, 2003; Cloude, 2006] has made it 
possible to estimate the forest height through the use of the 
Random Volume over Ground (RVoG) model [Treuhaft and 
Siqueira, 2000; Papathanassiou and Cloude, 2001]. In this paper 
we will address the problem of tree height estimation using both 
simulated data [Williams, 2006] and real data from the 
INDREX-II campaign [Hjansek and Hoekman, 2006]. 
Yv = 
(2) 
where K z is the vertical wave number calculated from the 
incidence angle (6) , the difference of two incidence angles 
from two antennas (Aff) and the wavelength (A,) of the radar 
system as in Equation (3). 
K 
z 
4M 6 
A sin 6 
radians/meter 
(3) 
2. METHODOLOGIES 
According to the RVoG scattering model, the complex 
interferometric coherence y , can be written as [Papathanassiou 
and Cloude, 2001]: 
f« = exp 0) 
1 + m(w) 
where (f> {) is the phase related to the ground topography, m is 
the effective ground-to-volume amplitude ratio (accounting for 
the attenuation through the volume) and W represents the 
polarization state. y v denotes the complex coherence for the 
volume alone (excluding the ground component), and is a 
function of the extinction coefficient a for the random volume 
and its thickness h v as expressed in Equation (2). 
The key point of interest for this application is the assumption 
that m is polarization dependent while y v is not. Manipulating 
Equation (1), it can be seen that the complex coherence values 
will lie upon a straight line as a function of m within the unit 
circle on the complex plane [Cloude and Papathanassiou, 2003]. 
In particular, for large m, the straight line intersects the unit 
circle and the associated phase at this point relates directly to 
the desired ground elevation. In the limit of no ground 
component (m=0), the observed coherence is given by the 
volume coherence y v rotated through (f)^ . A main objective of 
much of PolInSAR effort has been to develop robust methods to 
estimate h v through an inversion process. In this work, we will 
be comparing three of these approaches. 
In RVoG model inversion, the ground phase (f) Q is usually 
estimated first. This can be achieved by calculating the line- 
circle intersection on the complex plane [Cloude and 
Papathanassiou, 2003]. The straight line can be either fitted 
from a set of observed complex coherences (e.g., lexicographic 
coherences, Pauli decomposition coherences, and magnitude 
optimized coherences) or formed by the two ends of the 
estimated coherence region resulting from phase optimization 
Corresponding author.