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Canopy Gap Mapping from Airborne Laser Scanning: An Assessment of the Positional and Geometrical Accuracy

Lookup NU author(s): Dr Rachel Gaulton

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Canopy gaps are small-scale openings in forest canopies which offer suitable micro-climatic conditions for tree regeneration. Field mapping of gaps is complex and time-consuming. Several studies have used Canopy Height Models (CHM) derived from airborne laser scanning (ALS) to delineate gaps but limited accuracy assessment has been carried out, especially regarding the gap geometry. In this study, we investigate three mapping methods based on raster layers produced from ALS leaf-off and leaf-on datasets: thresholding, per-pixel and per-object supervised classifications with Random Forest. In addition to the CHM, other metrics related to the canopy porosity are tested. The gap detection is good, with a global accuracy up to 82% and consumer’s accuracy often exceeding 90%. The Geometric Accuracy (GAc) was analyzed with the gap area, main orientation, gap shape-complexity index and a quantitative assessment index of the matching with reference gaps polygons. The GAc assessment shows difficulties in identifying a method which properly delineates gaps. The performance of CHM-based thresholding was exceeded by that of other methods, especially thresholding of canopy porosity rasters and the per-pixel supervised classification. Beyond assessing the methods performance, we argue the critical need for future ALS-based gap studies to consider the geometric accuracy of results.


Publication metadata

Author(s): Bonnet S, Gaulton R, Lehaire F, Lejeune P

Publication type: Article

Publication status: Published

Journal: Remote Sensing

Year: 2015

Volume: 7

Issue: 9

Pages: 11267-11294

Online publication date: 02/09/2015

Acceptance date: 27/08/2015

Date deposited: 28/08/2015

ISSN (electronic): 2072-4292

Publisher: MDPI

URL: http://dx.doi.org/10.3390/rs70911267

DOI: 10.3390/rs70911267


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