is used to further refine the surface, remove any remaining errors, and achieve subpixel accuracy [25]. The results obtained from this algorithm were compared to surfaces generated using commercial digital photogrammetric image matching algorithm (SocetSet) and airborne laser scanning (LIDAR, 1 m point spacing) in a mire environment in Switzerland, and found that results from their algorithm were better than those obtained with the commercial system and at least as dense and of similar accuracy as those obtained from LIDAR [5]. It should be noted that the LIDAR data used in this study was relatively low resolution (1 m). However, the results from this study indicate that there is potential for using automated image matching techniques to generate accurate forest canopy surface models.

10.3 Airborne Laser Scanning

In this section, we firstly describe the principles of airborne laser scanning and then go on to detail how individual tree-level measurement are made using LIDAR. Finally, we outline the area-based approach to estimating biomass with LIDAR.

10.3.1 Principles of Airborne Laser Scanning

The other optical remote sensing technology capable of providing high resolution measurements of forest canopy structure is airborne laser scanning (also known as light detection and ranging, or LIDAR). Airborne LIDAR systems consist of a laser system that emits pulses at a very high rate (typically 100,000–167,000 Hz) in a scanning pattern beneath the aircraft. Precise measurement of the time-of-flight of an individual laser pulse, multiplied by the speed of light (a known constant), provides the range between the laser instrument and reflecting surfaces below. If the exact position and orientation of the laser system is also known at the moment each pulse is emitted, provided by airborne GPS and an inertial measurement unit respectively (the same enabling technologies used in direct georeferencing of aerial photography), then the 3D coordinate associated with each laser reflection can be calculated [4]. These so-called discrete-return airborne scanning systems generate a dense cloud of 3D points in a swath along the flight path of the aircraft. Most commercial LIDAR systems can record multiple returns from a single pulse, therefore, in a forested area, the point cloud provides information on the 3D forest canopy structure in a given area (see Fig. 10.4).

In recent years, airborne LIDAR systems have provide the entire waveform associated with each LIDAR pulse, instead of the discretized point data. These fullwaveform LIDAR systems depict the full measurement process of the LIDAR system and therefore have the potential to provide even more detailed picture of the three-dimensional distribution of forest canopy components beyond what is available from discrete-return systems [54]. Although processing and analysis of full

Fig. 10.4 Lidar data swath, upper Tanana valley of interior Alaska, USA. Points are color-coded by height (blue: low, green: medium, yellow/red: high)

waveform LIDAR data is still an evolving research field, recent progress has been made in establishing the theoretical basis for modeling the signal obtained from a full-waveform LIDAR system, where the signal is modeled as a series of Gaussian pulses [54]. Other studies have indicated great potential for using the additional information from full-waveform to characterize tree species composition and other forest attributes [45, 52].

The intensity (reflected energy level) associated with each LIDAR return (reflection) is also provided along with the 3D coordinate. Since most LIDAR systems operate in the near infrared portion of the electromagnetic spectrum (e.g. 1064 nm), which is sensitive to the chorophyll content and condition of vegetation, LIDAR intensity can provide additional information for forest characterization.

As with aerial photography, the properties of airborne LIDAR data are a function of the specific LIDAR system employed and system settings, such as pulse frequency, scan rate, beam divergence, scan angle, as well as a number of variable flight parameters, such as nominal flying height above ground level (AGL) and aircraft ground speed. In addition, LIDAR intensity information can be affected by the specific settings of the automatic gain control system and the AGL [13]. Previous studies carried out in Australia have indicated that, although acquiring LIDAR from platform altitudes as high as 3000 meters can still allow for quantification of forest structure, data acquired from higher altitudes will have fewer ground points available for generation of accurate digital terrain models, and the lower data density will have a detrimental effect on the accuracy of individual tree crown detection and measurement [16].

10.3.1.1 Lidar-Based Measurement of Terrain and Canopy Surfaces

Because LIDAR provides direct measurements of three-dimensional canopy structure, as well as the underlying terrain surface, the most fundamental products provided by airborne LIDAR are the canopy surface model and digital terrain model. Previous research has indicated that LIDAR-derived terrain models can be highly accurate (i.e. root mean square error (RMSE) <0.50 m), even under relatively dense coniferous forest canopy conditions found in the Pacific Northwest region of the