The canopy, the aggregate of all crowns in a stand of vegetation, is critically important for a variety of processes. The canopy houses the machinery of photosynthesis and controls growth and production, affects microclimates at various scales, and provides habitat for a diversity of organisms. The structure of the canopy is an important influence on, and indicator of, all these functions. Aspects of structure can indicate the stand developmental stage and potential for growth, the diversity of included habitats, and may predict stand attributes important in stand management, such as stem density, basal area and above-ground biomass.
Common measurements of canopy structure are simple spatial summaries, such as the fraction of ground overlayed by foliage (coverage), the maximum stem height and the leaf area per unit ground area (leaf area index, LAI). Such summaries are often inadequate for predictions of growth, carbon dioxide exchange, structural complexity and habitat quality; structural information on the spatial distribution of canopy components is more useful than summary measures (Parker 1995; Lefsky et al. 2002).
In the common ground-based method for characterizing the vertical distribution of foliage (optical point quadrats, OPQ), an observer determines, at many locations in the stand, the height to the nearest leaf overhead. This is done by manually focusing an upward-viewing telephoto lens calibrated to measure distance (MacArthur & Horn 1969). The resulting distribution of intercepted distances is adjusted for the effect of the occlusion of far targets by near ones, to yield the relative vertical distribution of leaves, the foliage height profile (FHP). This adjustment, referred to as the MacArthur–Horn transformation (M-H), assumes that the probe is infinitely thin and that canopy elements are Poisson-randomly distributed in space. The transformation is sensitive to differences in canopy cover, so accurate estimation of cover is important (Radtke & Bolstad 2001). The OPQ method does not yield absolute LAI but it provides relative height profiles (Aber 1978; Hedman & Binkley 1988; Brown & Parker 1994) and has been validated in broad-leaved forests by Fukushima, Hiura & Tanabe (1998). Because this approach is very labour intensive it has only been used for plot- and stand-scale summaries.
The basis for detailed canopy structure information is a set of spatially referenced distance measurements. Light detection and ranging (LIDAR), which measures distance by time-of-flight using pulsed laser light (Bufton 1989), can provide these. Lefsky et al. (2002) distinguish two main types of LIDAR systems used in remote sensing of vegetation, waveform-recording and discrete-return. Waveform-recording systems measure the vertical distribution of intercepted canopy surfaces and the underlying ground surface within a single footprint using high-speed digitization of the backscattered return from a short-duration laser pulse (Harding et al. 2001). This technology has been employed experimentally from aeroplanes (Blair, Rabine & Hofton 1999; Harding et al. 2000) and NASA spacecraft (Garvin et al. 1998; Zwally et al. 2002). The diameter of the laser footprint is large for these airborne (5–25 m) and space-based (70–100 m) sensors.
Harding et al. (2001) showed that waveform-based vegetation height profiles retrieved from an airborne platform were similar, in several forests, to coincident OPQ height profiles obtained from the ground, when both were corrected for occlusion. However, because LIDAR systems do not easily distinguish leaves from other surfaces (Radtke & Bolstad 2001; Lefsky et al. 2002) the derived vertical profile is termed a canopy height profile (CHP), in contrast with the FHP described by MacArthur & Horn (1969). By analogy with terminology for foliar structure (Parker 1995), the height profile of the complete surface area is denoted C(h), and its sum over all heights is the canopy area index, CAI.
Discrete-return LIDAR systems measure the distances to one or a few surfaces in a small diameter spot from which the backscattered laser energy exceeds a detection threshold. They are most commonly employed in terrain mapping (Baltsavius 1999) but have also been used in research on vegetation canopies (Nelson, Krabill & Tonelli 1988; Ritchie et al. 1993; Parker & Russ 2004). Airborne LIDAR systems that record the range to the first and/or last intercepted surface have been utilized to determine the height of vegetation and the topography of the outer canopy surface (Nelson, Krabill & Tonelli 1988; Ritchie et al. 1993; Nilsson 1996; Magnussen, Eggermont & LaRiccia 1999; Naesset & Bjerknes 2001). However, the relatively large diameter laser beam, typically 0·5–1 m, in these studies means that, for closed canopies, the laser pulse is intercepted by vegetation at or near the outer canopy surface, with few observations on the internal organization of the canopy. Discrete-return LIDAR systems that distinguish multiple (as many as five) targets per laser pulse are now in use commercially. Although these have the potential to characterize better the distribution of surface area within the canopy, that capability has not yet been demonstrated. LIDAR systems with very closely spaced small footprints (e.g. 0·1 m), typically deployed on helicopters, can range through small gaps, yielding a distribution of first intercepts that more completely samples surface area throughout the canopy (Blair & Hofton 1999).
Several limitations hinder the utility of airborne and space-based LIDAR systems for investigations of canopy structure. For typical airborne systems, the costs for instrument deployment and data acquisition and processing are high, making studies of small areas impractical, and frequent, repeated measurements to observe temporal variations are prohibitively expensive. Data from the NASA satellite-based systems, while available at no cost, are limited in geographical and temporal coverage and of low spatial resolution.
A variety of ground-based LIDAR systems can acquire ranges for angles in two dimensions. For example, Vanderbilt (1985) studied the geometry of a row crop with a scanning system. Tanaka, Yamaguchi & Takeda (1998) reconstructed 3-dimensional forest geometries by triangulation using images of the planar trace of a visible laser beam intercepting canopy elements. However, such instruments are generally not portable and often have a limited range.
A portable system is needed for rapid and accurate measurement of canopy structure at ecologically significant scales. It should be readily assembled from commercially available components, straightforward in operating principle, and easy to use under a variety of field conditions. Our objectives were to describe and evaluate such a system, to demonstrate some numerical and graphical products, and illustrate its utility for studies of vegetation structure and processes that depend on that structure.
We chose not to design and build a waveform-recording system because this would not be easily assembled or widely available. Instead we investigated existing commercial systems that record discrete ranges using pulsed laser diodes. We identified desirable characteristics of the system, evaluated several available laser rangefinders, and selected one that best met the requirements. We evaluated this instrument in laboratory tests and then adapted it for field use by integrating it with a rugged carrying frame, power supply and data acquisition system. We tested the system in a variety of canopies and canopy situations to compare it with other methods and to understand its biases, repeatability and capacity to detect a variety of structures. We also developed approaches to reduce the data, measures useful for characterization and comparison, and some visualizations of the resulting volumetric data.