Type of Submission
Poster
Keywords
Forest canopy, openness, leaf area index, mobile applications, hemispherical photography, GLAMA, Canopeo
Proposal
Plant canopy architecture results from the relationships of species composition, historical land use, succession, and species competition. Each forest’s canopy architecture influences the plant and animal community that live below. Key variables used to quantify the canopy architecture are leaf area index (LAI, m2 leaf m-2 ground) and canopy openness. The objective of our study was to analyze the accuracy of several mobile phone applications in interpreting the varying light environments of a second-growth forest in Ohio as compared to the standard technique using hemispherical photography. For this pilot project we measured 30 randomly selected points throughout a 15 acre forest stand in Greene County, Ohio. Mean canopy openness (minimum - maximum) for the site was 14.7 (5.7 - 23.8) and 46.1 (20.0 - 77.4) for GLAMA and Canopeo, respectively. Additionally, we processed digital hemispherical photographs using Gap Light Analyzer (GLA v 2.0) and calculated a mean % openness of 20.6 (12.2 - 45.5) and LAI of 2.1. When compared to the standard method of hemispherical photographs Canopeo and GLAMA described 41 and 19% of the total variability in forest canopy openness as measured by GLA. Our data show that GLAMA consistently over estimated while Canopeo underestimated openness. The data from this study reveals how each application used image processing methods to calculate canopy openness. The various applications showed inadequacies regarding the typical methods used to calculate canopy openness; none of the applications proved to be more accurate at calculating canopy openness than the others.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
A Comparison of Methods to Estimate Forest Canopy Structure in Cedarville, Ohio
Plant canopy architecture results from the relationships of species composition, historical land use, succession, and species competition. Each forest’s canopy architecture influences the plant and animal community that live below. Key variables used to quantify the canopy architecture are leaf area index (LAI, m2 leaf m-2 ground) and canopy openness. The objective of our study was to analyze the accuracy of several mobile phone applications in interpreting the varying light environments of a second-growth forest in Ohio as compared to the standard technique using hemispherical photography. For this pilot project we measured 30 randomly selected points throughout a 15 acre forest stand in Greene County, Ohio. Mean canopy openness (minimum - maximum) for the site was 14.7 (5.7 - 23.8) and 46.1 (20.0 - 77.4) for GLAMA and Canopeo, respectively. Additionally, we processed digital hemispherical photographs using Gap Light Analyzer (GLA v 2.0) and calculated a mean % openness of 20.6 (12.2 - 45.5) and LAI of 2.1. When compared to the standard method of hemispherical photographs Canopeo and GLAMA described 41 and 19% of the total variability in forest canopy openness as measured by GLA. Our data show that GLAMA consistently over estimated while Canopeo underestimated openness. The data from this study reveals how each application used image processing methods to calculate canopy openness. The various applications showed inadequacies regarding the typical methods used to calculate canopy openness; none of the applications proved to be more accurate at calculating canopy openness than the others.
