Using LiDAR to compare forest height estimates from IKONOS and Landsat ETM+ data in Sitka spruce plantation forests

Abstract

This paper compares and contrasts predictions of forest height in Sitka spruce (Picea sitchensis) plantations based on medium‐resolution Landsat Enhanced Thematic Mapper Plus (ETM+), high‐resolution IKONOS satellite imagery and airborne Light Detection and Ranging (LiDAR) data. The relationship between field‐measured height and LiDAR height is linear and highly significant (R² 0.98). Despite the difference in spatial resolution and radiometry between Landsat ETM+ and IKONOS multi‐spectral data, the strength of the relationship between field height and predicted height using the green spectral band was very similar, with R² values of 0.84 and 0.85, respectively. The inclusion of additional observations taken from the LiDAR data improved the strength of the relationship slightly for the Landsat ETM+ data (R² = 0.87), but did not change the relationship for the IKONOS data (R² = 0.84). Comparison of the height models derived from the satellite and LiDAR data shows that the optical models provide accurate predictions up to the point of forest canopy closure (10 m) in densely stocked plantations (>2000 stems ha⁻¹); beyond this point, only the LiDAR model is able to provide a reliable estimate of forest height. The results demonstrate that the retrieval of forest structure information over the lifetime of a plantation forest is best achieved by the integration of satellite, airborne and ground‐based measurements. It is possible to use optical satellite data to identify forest stands that display unexpected growth characteristics, such as areas of high natural regeneration, poor or incomplete stocking.

Acknowledgement

This research was carried out as part of an EU Life‐Environment project entitled ForestSAFE. Special thanks are due to the NERC Earth Observation Data Centre who kindly supplied some of the image data. The comments of Dr Paul Aplin and two anonymous referees greatly improved the quality and presentation of this paper. Project website: http://www.geography.dur.ac.uk/ForestSAFE.