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ISRN Ecology
Volume 2012, Article ID 619842, 11 pages
Research Article

Development of a Rapid and Precise Method of Digital Image Analysis to Quantify Canopy Density and Structural Complexity

1Department of Natural and Social Sciences, Francis Close Hall, University of Gloucestershire, Swindon Road, Cheltenham, Glos GL50 4AZ, UK
2St Briavels, Forest of Dean, Gloucestershire, UK

Received 21 October 2011; Accepted 4 December 2011

Academic Editors: A. Chappelka and M. Rossetto

Copyright © 2012 Anne E. Goodenough and Andrew S. Goodenough. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Estimation of canopy density is necessary for ecological research and woodland management. However, traditional manual methods are time consuming and subject to interobserver variability, while existing photographic methods usually require expensive fish-eye lenses and complex analysis. Here we introduce and test a new method of digital image analysis, CanopyDigi. This allows user-defined threshold to polarise the 256 grey shades of a standard monochrome bitmap into dark “canopy” and light “sky” pixels (the threshold being selected using false-colour images to ensure its suitability). Canopy density data are calculated automatically and rapidly, and, unlike many other common methods, aggregation data are obtainable using Morisita’s index to differentiate closed (diffuse light) and open (direct light) canopies. Results were highly repeatable in both homogeneous and heterogeneous woodland. Estimates correlated strongly with existing (nondigital) canopy techniques, but quicker and with significantly lower interobserver variability (CV = 3.74% versus 20.73%). We conclude that our new method is an inexpensive and precise technique for quantifying canopy density and aggregation.