International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
BIOMASS ESTIMATION USING VERTICAL FOREST STRUCTURE FROM SAR
TOMOGRAGHY: A CASE STUDY IN CANADIAN BOREAL FOREST.
E. Renaudin * *, B. Mercer *, Q. Zhang ^, MJ. Collins *
* University of Calgary, University Drive NW, Calgary, AB, Canada T2N 1N4
(erwan.renaudin, mjcollins)@ ucalgary.ca - bryanm@telus.net
® Intermap Technologies Corp., #500, 635 - 6th Avenue SW, Calgary, AB, T2P OTS — qzhang@intermap.com
Commission VIII/7
KEY WORDS: POLInSAR, Tomography, Polarimetry, Interferometry, Forestry, Structure, Biomass
ABSTRACT:
A major goal of current research is to address temporal climatic variations that are related to CO2 emissions. A significant portion of
these emissions are due to forest destruction and the resulting conversion of biomass to CO2. As 30% of the earth's landmass is
forest-covered, it is important to understand the biomass content with better estimates than are currently available. This research has
addressed the determination of forest biomass in a Northern Alberta forest site, using novel techniques known as POLInSAR
(Polarimetry Interferometry SAR) to study the 3D vegetated structure of forests through using an L-Band single-pass airborne
system. Results of this study indicate strong relation between vertical structure and above ground biomass. In this paper we show the
preliminary results of the work including the resulting tomographic expression of the test forest area.
1. INTRODUCTION *standard' tomography generally requires multiple baselines
created from multiple passes and hence increased operational
The study of CO2 emissions into the atmosphere and their costs, for airborne systems at least. To overcome those
impact on climate change are of global interest. The destruction limitations a recently proposed method (Cloude, 2006A, 2006B,
of forests makes a significant contribution to the total (UNDG, 2009), named Polarisation Coherence Tomography (PCT) has
= 2008) and there is a corresponding interest in improving the —— been proposed to solve estimation of the vertical distribution of
accuracy of forest biomass estimates (Houghton ef al., 2009) in scattering, with the use of few baselines (one to three).
order to provide baseline information for subsequent monitoring Indirectly, the recovery of biomass within the vertical layers is
and for mitigation purposes. Remote sensing techniques applied derived from that vertical profile.
to date, including both optical and radar backscatter approaches,
suffer from saturation effects at higher biomass levels (Dong, ef In this paper we tackle the problem of generating those profiles
al., 2003, Le Toan et al., 1992; Beaudoin et al, 1994; Lefskyet or tomograms to highlight the possible interactions with
al., 2005; Leckie and Ranson, 1998). In this paper we describe biomass content.
results from an approach involving Polarimetric InSAR
(POLInSAR) to extract tomographic images of forest canopy In section 2, we review the basic elements of PCT including the
from which biomass estimates can be inferred (Cloude, 2006A). ultimate goal of extracting forest biomass information; in
Previous work has shown that tree height and ground elevation section 3 we summarize the data set and the system from which
can be obtained from L-Band POLInSAR methods and that tree it was derived; preliminary results in the form of the derived
height is a good proxy, through an allometric relationship, to PCT profiles or tomograms are presented in section 4 with
biomass at least for homogeneous forest types (Mette et al., conclusions and follow-on plans summarized in section 5.
2004A, 2004B). However the combination of POLInSAR with
tomography is intended to address the problem of biomass
determination when the forest contains mixed species. 2. POLARIZATION COHERENCE TOMOGRAPHY
The vertical profiles of forest canopy density (which are 2.1 Polarization Coherence Tomography
represented by the variation of backscatter signal along the
vertical) are potentially strong indicators of forest Above An underlying assumption of many approaches, including PCT,
Ground Biomass (ABG). Since the radar cross-section observed is that the forest may be represented by a slab containing a
for a given pixel is the sum or integral of contributions from all random distribution of scatterers, horizontally homogeneous in
scatterers at the same range, encompassing all heights, the their properties, but with backscatter sources distributed in the
information about vertical structure is lost. While POLInNSAR Vertical according to a structure function f(z) where z is the
techniques allow the height and ground elevations to be vertical dimension with respect to an impermeable ground
estimated, they do not recover the forest structure directly. The surface (Papathanassiou and Cloude, 2003).
virtue of the tomographic approach (Treuhaft et al, 2000;
Cloude, 2006A; Hajnsek et al, 2009) is that a three- This is referred to as the Random Volume Over Ground
dimensional image of the canopy can be obtained. However, (RVoG) model The complex coherence, which is the
* Corresponding author.