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Original Articles

Development of an automated individual tree detection model using point cloud LiDAR data for accurate tree counts in a Pinus radiata plantation

, , , &
Pages 126-136 | Received 28 Jul 2015, Accepted 30 Jan 2016, Published online: 23 Jun 2016
 

ABSTRACT

We develop and evaluate a new individual tree detection (ITD) algorithm to automatically locate and estimate the number of individual trees within a Pinus radiata plantation from relatively sparse airborne LiDAR point cloud data. The area of interest comprised stands covering a range of age classes and stocking levels. Our approach is based on local maxima (LM) filtering that tackles the issue of selecting the optimal search radius from the LiDAR point cloud for every potential LM using metrics derived from local neighbourhood data points; thus, it adapts to the local conditions, irrespective of canopy variability. This was achieved through two steps: (i) logistic regression model development using simulated stands composed of individual trees derived from real LiDAR point cloud data and (ii) application testing of the model using real plantation LiDAR point cloud data and geolocated, tree-level reference crowns that were manually identified in the LiDAR imagery. Our ITD algorithm performed well compared with previous studies, producing RMSE of 5.7% and a bias of only −2.4%. Finally, we suggest that the ITD algorithm can be used for accurately estimating stocking and tree mapping, which in turn could be used to derive the plot-level metrics for an area-based approach for enhancing estimates of stand-level inventory attributes based on plot imputation.

Acknowledgments

The authors thank Bob Cooper (NSW Forestry Corporation) who surveyed the field plots.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The results in this paper came from a larger study funded by the Forest and Wood Products Australia (www.fwpa.com.au/images/resources/FWPA_PNC305_1213_Final_Report_Feb2015_amended.pdf) and are presented in our report to that organisation within a more comprehensive discussion and review of other ITD techniques.

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