Canadian Forest Service Publications
Stability of sample-based scanning LiDAR-derived vegetation metrics for forest monitoring. 2011. Bater, C.W.; Wulder, M.A.; Coops, N.C.; Nelson, R.F.; Hilker, T.; Næsset, E. IEEE Transactions on Geoscience and Remote Sensing 49(6): 2385-2392.
Available from: Pacific Forestry Centre
Catalog ID: 32515
CFS Availability: PDF (download)
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The objective of this paper is to gain insights into the reproducibility of light detection and ranging (LiDAR)-derived vegetation metrics for multiple acquisitions carried out on the same day, where we can assume that forest and terrain conditions at a given location have not changed. Four overlapping lines were flown over a forested area in Vancouver Island, British Columbia, Canada. Forty-six 0.04-ha plots were systematically established, and commonly derived variables were extracted from first and last returns, including height-related metrics, cover estimates, return intensities, and absolute scan angles. Plot-level metrics from each LiDAR pass were then compared using multivariate repeated-measures analysis-of-variance tests. Results indicate that, while the number of returns was significantly different between the four overlapping flight lines, most LiDAR-derived first return vegetation height metrics were not. First return maximum height and overstory cover, however, were significantly different and varied between flight lines by an average of approximately 2% and 4%, respectively. First return intensities differed significantly between overpasses where sudden changes in the metric occurred without any apparent explanation; intensity should only be used following calibration. With the exception of the standard deviation of height, all second return metrics were significantly different between flight lines. Despite these minor differences, the study demonstrates that, when the LiDAR sensor, settings, and data acquisition flight parameters remain constant, and time-related forest dynamics are not factors, LiDAR-derived metrics of the same location provide stable and repeatable measures of the forest structure, confirming the suitability of LiDAR for forest monitoring.
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