J. B. Blair

Laser altimeter canopy height profiles: methods and validation for closed-canopy, broadleaf forests

Waveform-recording laser altimeter observations of vegetated landscapes provide a time-resolved measure of laser pulse backscatter energy from canopy surfaces and the underlying ground. Airborne laser altimeter waveform data was acquired using the Scanning Lidar Imager of Canopies by Echo Recovery (SLICER) for a successional sequence of four, closed-canopy, deciduous forest stands in eastern Maryland. The four stands were selected so as to include a range of canopy structures of importance to forest ecosystem function, including variation in the height and roughness of the outermost canopy surface and the vertical organization of canopy stories and gaps. The character of the SLICER backscatter signal is described and a method is developed that accounts for occlusion of the laser energy by canopy surfaces, transforming the backscatter signal to a canopy height profile (CHP) that quantitatively represents the relative vertical distribution of canopy surface area. The transformation applies increased weighting to the backscatter amplitude as a function of closure through the canopy and assumes a horizontally random distribution of the canopy components. SLICER CHPs, averaged over areas of overlap where altimeter ground tracks intersect, are shown to be highly reproducible. CHP transects across the four stands reveal spatial variations in vegetation, at the scale of the individual 10-m-diameter laser footprints, within and between stands. Averaged SLICER CHPs are compared to analogous height profile results derived from ground-based sightings to plant intercepts measured on plots within the four stands. The plots were located on the segments of the altimeter ground tracks from which averaged SLICER CHPs were derived, and the ground observations were acquired within 2 weeks of the SLICER data acquisition to minimize temporal change. The differences in canopy structure between the four stands is similarly described by the SLICER and ground-based CHP results. However, a chi-square test of similarity documents differences that are statistically significant. The differences are discussed in terms of measurement properties that define the smoothness of the resulting CHPs and canopy properties that may vertically bias the CHP representations of canopy structure. The statistical differences are most likely due to the more noisy character of the ground-based CHPs, especially high in the canopy where ground-based sightings are rare resulting in an underestimate of canopy surface area and height, and to departures from assumptions of canopy uniformity, particularly regarding lack of clumping and vertically constant canopy reflectance, which bias the CHPs. The results demonstrate that the SLICER observations reliably provide a measure of canopy structure that reveals ecologically interesting structural variations such as those characterizing a successional sequence of closed-canopy, broadleaf forest stands.

Sensitivity of large-footprint lidar to canopy structure and biomass in a neotropical rainforest

Accurate estimates of the total biomass in terrestrial vegetation are important for carbon dynamics studies at a variety of scales. Although aboveground biomass is difficult to quantify over large areas using traditional techniques, lidar remote sensing holds great promise for biomass estimation because it directly measures components of canopy structure such as canopy height and the vertical distribution of intercepted canopy surfaces. In this study, our primary goal was to explore the sensitivity of lidar to differences in canopy structure and aboveground biomass in a dense, neotropical rainforest. We first examined the relationship between simple vertical canopy profiles derived from field measurements and the estimated aboveground biomass (EAGB) across a range of field plots located in primary and secondary tropical rainforest and in agroforesty areas. We found that metrics from field-derived vertical canopy profiles are highly correlated (R 2 up to .94) with EAGB across the entire range of conditions sampled. Next, we found that vertical canopy profiles from a large-footprint lidar instrument were closely related with coincident field profiles, and that metrics from both field and lidar profiles are highly correlated. As a result, metrics from lidar profiles are also highly correlated (R 2 up to .94) with EAGB across this neotropical landscape. These results help to explain the nature of the relationship between lidar data and EAGB, and also lay the foundation to explore the generality of the relationship between vertical canopy profiles and biomass in other tropical regions. D 2002 Elsevier Science Inc. All rights reserved.

Validation of Vegetation Canopy Lidar sub-canopy topography measurements for a dense tropical forest

Large footprint (greater than 10 m wide) laser altimetry is a useful technique for mapping topography (including sub-canopy), canopy height and vertical structure in densely vegetated areas. In March 1998, the Laser Vegetation Imaging Sensor (LVIS), an airborne laser altimeter, mapped a ∼800 km2 area of Costa Rica including the La Selva Biological Station using 25 m-diameter footprints as part of the pre-launch activities of the Vegetation Canopy Lidar (VCL) Mission. To investigate the utility of the lidar technique for making sub-canopy topography measurements, the precision and accuracy of the LVIS elevation measurements from this mission are assessed. Crossover analysis using laser shots whose recorded waveforms contained more than 50% of the total returned energy within their lowest reflections show the elevations have a precision of better than 1 m. Comparison of the LVIS elevations with coincident in situ ground elevation data reveals that the measurements are within ∼1.5 m of each other on less than 3° slopes. All measurements are within ∼5 m of each other (on slopes of up to 30°). These are very encouraging results given that the forests of this region are some of the densest, most complex on Earth, and that mapping their sub-canopy topography are near-impossible using any other remote sensing technique. Given the similarity of the measurement processes of the LVIS and VCL systems, these results suggest that the topographic measurements made by the VCL will meet stated accuracy goals under the majority of measurement conditions.

Volumetric lidar return patterns from an old-growth tropical rainforest canopy

Rainforests represent the epitome of structural complexity in terrestrial ecosystems. However, measures of three-dimensional canopy structure are limited to a few areas typically < 1 ha with construction crane or walkway/platform access. An innovative laser profiling system, the Laser Vegetation Imaging Sensor (LVIS), was used to map canopy structure (i.e. based on height and vertical distribution of laser returns) of a tropical rainforest in Costa Rica. Within a 1km2 area of mature rainforest, canopy top height ranged from 8.4 to 51.6m based on the altimeter measures. The laser return density was most concentrated in the horizontal layer located 20-30m above the ground. Spatial patterns of the return were found to be isotropic based on north-south versus east-west vertical return profiles and exhibited properties of self-similarity.

Laser altimeter return pulse correlation: a method for detecting surface topographic change

Abstract Quantifying and monitoring of many natural hazards requires repeated measurements of a topographic surface whose change reflects a geological or geophysical process. Topography and topographic change measurements are routinely made using techniques such as Interferometric Synthetic Aperture Radar and GPS, but both of these techniques have limitations for these purposes. A technique attracting increasing attention for its ability to perform accurate high-resolution topographic mapping (including sub-canopy) is laser altimetry, or lidar. Here, we evaluate the feasibility of a new method for using laser altimeter return echoes, or waveforms, to detect relative elevation change. The method, dubbed the return pulse correlation method, maximizes the shape similarity of coincident laser return waveforms from two observation epochs by shifting them vertically. We evaluate the accuracy of the pulse correlation method using laser altimeter data acquired over the NASA Wallops Flight Facility, VA, a region where no elevation change is expected within the time period of the surveys, and at Assateague Island, MD, a highly dynamic barrier island where several meters of erosion and deposition have been observed. Results show that use of the pulse correlation method generates elevation change estimates similar in magnitude to those obtained by simply differencing coincident laser altimeter elevation measurements (dubbed the spot comparison method). Along the beach at Assateague Island, MD, similar patterns of accretion and deposition are detected using both the pulse correlation and spot comparison methods, although some horizontal resolution is lost using the pulse correlation method because of the wide footprint spacing of the waveform-recording laser altimeter used in the study. In the test case presented here, increasing the size of the laser footprint from 25 to 60 m caused the magnitude of the vertical change signal to be underestimated, confirming that the resolution of the measurement technique and the scale of the deformation features should be considered when planning survey missions. The use of this method can improve the accuracy of surface change estimates made using laser altimeter waveforms, especially beneath vegetation, by eliminating the subjective interpretation of waveforms used to extract a single elevation measurement. ©

Comparison of SRTM-NED data to LIDAR derived canopy metrics

Forest canopy height derived from the SRTM-NED were compared to three LIDAR vegetation metrics for the Sierra Nevada forest. Generally the SRTM-NED was found to under estimate the vegetation canopy height. The SRTM SAR signal was found to penetrate, on average, into 44% of the canopies. The residual errors as a function of LVIS canopy height and cover were found to generally increase with height and cover. Likewise, the RMSE was found to initially increase with canopy height and cover but saturates at 50 m height and 60% cover.

Comparison of Forest Canopy Structures in SRTM to LIDAR Data

Forest canopy height derived from the SRTM 30m grid DEM were compared to LVIS and ICESAT footprint data of three US sites, namely Sierra Nevada in California, Coweeta in North Carolina and Hubbard Brook in New Hampshire. It was found that in dense forest, such as the Coweeta forest, the SRTM data better estimate forest canopy height. By modeling the SRTM estimated mean canopy heights, the RMSE was found to improve significantly. In comparison to LVIS, the RMSE was reduced from 12.25m to 8.92m, 12.57m to 7.61m and 9.21m to 4.85m, respectively for the Sierra, Coweeta and Hubbard Brook sites. For the ICESAT data of the Sierra site, the RMSE was reduced from 15.49m to 8.75m.