The estimation of canopy attributes from digital cover photography by two different image analysis methods
Francesco Chianucci , Ugo Chiavetta, Andrea Cutini
iForest - Biogeosciences and Forestry, Volume 7, Issue 4, Pages 255-259 (2014)
doi: https://doi.org/10.3832/ifor0939-007
Published: Mar 26, 2014 - Copyright © 2014 SISEF
Research Articles
Abstract
Proximal sensing methods using digital photography have gained wide acceptance for describing and quantifying canopy properties. Digital hemispherical photography (DHP) is the most widely used photographic technique for canopy description. However, the main drawbacks of DHP have been the tedious and time-consuming image processing required and the sensitivity of the results to the image analysis methods. Recently, an alternative approach using vertical photography has been proposed, namely, digital cover photography (DCP). The method captures detailed vertical canopy gaps and performs canopy analysis by dividing gap fractions into large between-crown gaps and small within- crown gaps. Although DCP is a rapid, simple and readily available method, the processing steps involved in gap fraction analysis have a large subjective component by default. In this contribution, we propose an alternative simple, more objective and easily implemented procedure to perform gap fraction analysis of DCP images. We compared the performance of the two image analysis methods in dense deciduous forests. Leaf area index (LAI) estimates from the two image analysis methods were compared with reference LAI measurements obtained through the use of litter traps to measure leaf fall. Both methods provided accurate estimates of the total gap fraction and, thus, accurate estimates of the LAI. The new proposed procedure is recommended for dense canopies because the subjective classification of large gaps is most error-prone in stands with dense canopy cover.
Keywords
Digital Cover Photography, Canopy Cover, Gap Fraction, Leaf Area Index, Dense Canopy
Authors’ Info
Authors’ address
Ugo Chiavetta
Andrea Cutini
Consiglio per la Ricerca e la sperimentazione in Agricoltura - Forestry Research Centre, v.le Santa Margherita 80, I-52100 Arezzo (Italy)
Corresponding author
Paper Info
Citation
Chianucci F, Chiavetta U, Cutini A (2014). The estimation of canopy attributes from digital cover photography by two different image analysis methods. iForest 7: 255-259. - doi: 10.3832/ifor0939-007
Academic Editor
Francesco Ripullone
Paper history
Received: Dec 20, 2012
Accepted: Mar 03, 2014
First online: Mar 26, 2014
Publication Date: Aug 01, 2014
Publication Time: 0.77 months
Copyright Information
© SISEF - The Italian Society of Silviculture and Forest Ecology 2014
Open Access
This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Web Metrics
Breakdown by View Type
Article Usage
Total Article Views: 52847
(from publication date up to now)
Breakdown by View Type
HTML Page Views: 44897
Abstract Page Views: 2169
PDF Downloads: 4455
Citation/Reference Downloads: 53
XML Downloads: 1273
Web Metrics
Days since publication: 3844
Overall contacts: 52847
Avg. contacts per week: 96.24
Citation Metrics
Article Citations
Article citations are based on data periodically collected from the Clarivate Web of Science web site
(last update: Feb 2023)
Total number of cites (since 2014): 15
Average cites per year: 1.50
Publication Metrics
by Dimensions ©
Articles citing this article
List of the papers citing this article based on CrossRef Cited-by.
References
DHP-TRACWin Manual (version 1.03). Natural Resources Canada, Saint-Hubert, Quebec, pp. 29.
Gscholar
R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Gscholar