379 
A COMPARISON OF ESTIMATING FOREST CANOPY HEIGHT 
INTEGRATING MULTI-SENSOR DATA SYNERGY 
A CASE STUDY IN MOUNTAIN AREA OF THREE GORGES 
Lixin Dong, Bingfang Wu * 
Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, P. R. China 
Datun Road No. 3, P. O. Box 9718, 100101, Beijing, P. R. China, dlx_water@163.com 
KEY WORDS: Forest Canopy Height, Lidar, Multisensor Integration, Three Gorges, Spatial models 
ABSTRACT: 
Forest canopy height is an important input for ecosystem and highly correlated with aboveground biomass at the landscape scale. In 
this paper, we make efforts to extracte the maximum canopy height using GLAS waveform combination with the terrain index in 
sloped area where LiDAR data were present. Where LiDAR data were not present, the optical remote sensing data were used to 
estimate the canopy height at broad scale regions, we compared four aspatial and spatial methods for estimating canopy height 
integrating large footprint Lidar system (GLAS) and Landsat ETM+: ordinary least squares regression, ordinary kriging, cokriging, 
and cokriging of regression residuals. The results show that (1) the terrain index will help to extract the forest canopy height over a 
range of slopes. Regression modles explained 51.0% and 84.0% of variance for broadleaf and needle forest respectively.(2) some 
improvements were achieved by adding additional remote sensing data sets. The integrated models that cokriged regression residuals 
were preferable to either the aspatial or spatial models alone.The integrated modeling strategy is most suitable for estimating forest 
canopy height at locations unsampled by lidar. 
1. INTRODUCTION 
Measurements of forest structure are critical for biomass esti 
mation (Sun et al., 2008), biodiversity studies (North et al.1999), 
fire modelling (Finney, 1998), carbon stock estimation (Skole 
& Tucker, 1993), et,al.. Meantime, forest canopy height is an 
important input for ecosystem and is highly correlated with bio 
mass (Lefsky, 2005). Traditionally, these attributes have been 
measured in field using handheld equipment, which are time- 
consuming and limited in scope to mapping at the landscape 
scale (Hyde et al. 2006). For passive optical sensors (Landsat 
TM/ETM+), it provide useful structure information in the hori 
zontal plane (Cohen & Spies, 1992), but is difficult to pene 
trating beyond upper canopy layers (Weishampel et al., 2000). 
Full waveform digitizing, large footprint LiDAR provides 
highly accurate measurements of forest canopy structure in the 
vertical plane (Nilsson, 1996, Lefsky et al. 1999). However, 
current lidar sensors have limited coverage in horizontal plane 
(Lefsky et al. 2002, Hyde et al. 2006). 
In present time, due to no single technology is capable of 
provide all broad scale information of vertical structure, there 
have been several calls for improving the applicability of 
remote sening data through multisensor integration (Hudak et al. 
2002), combining information from multiple sensor is a pro 
mising efforts to improving the accuracy of canopy height esti 
mation at landscape scales (Slatton et al., 2001, Wulder et al. 
2004). 
Lidar-Landsat TM/ETM+ integration has immediate relevance 
due to the anticipated launches of the Ice, Cloud, and Land 
Elevation Satellite (ICESat) (Hudak et al. 2002). In this study, 
our mainly objective was to estimate canopy height at broad 
scales by integrating the lidar and Landsat TM/ETM+ at the 
lidar sample locations. The basic data from GLAS (maximum 
canopy height) and biophysical attributes from Landsat 
TM/ETM+ (LAI, Forest cover and vegetation indices) were 
used for estimation of canopy height. We compared and tested 
four widely used empirical estimation methods: ordinary least 
squares (OLS) regression, ordinary kriging (OK), and ordinary 
cokriging (OCK), and the mixed model of cokriging of 
regression residuals. 
Our study area lies in mountain area of Three Gorges, which is 
representative of the age and structural classes common in the 
region. For forests on level ground, the waveform peaks of 
canopy surfaces and underlying ground within the footprint 
were easily separate. However, over sloped areas, the extent of 
waveform increased which inducing some errors. Harding and 
Carabajal (2005) point out that the vertical extent of each 
waveform increases as a function of the product of the slope 
and the footprint size, and returns from both canopy and ground 
surfaces can occur at the same elevation. In order to effectively 
extracting the canopy height in the sloped area, a new technique 
using Terrain Index algorithms was used for estimation of 
canopy height GLAS system in Three Gorges. 
2. STUDY AREAS AND DATA PROCESSING 
2.1 Sduty Areas 
Three Gorges area is a key area of the natural protective regions 
in China. It is located in 106°00'~111°50'E, 29 0 16'~31 0 25'N, 
and covers an area of approximately 5.8* 10 4 km 2 . It lies in the 
lower part of the upper reaches of the Yangtze. To the north is 
* Corresponding author. Email: wubfiirsa. ac. cn..