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

Abstract

<jats:p>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.</jats:p>

Quantifying the Severity of Phytophthora Root Rot Disease in Avocado Trees Using Image Analysis

“…Red, green, blue (RGB) photographs acquired by digital cameras have been successfully used to estimate canopy density, tree architecture, and growth in forest trees and grapevines [13][14][15][16]. Canopy porosity (crown porosity) or gap distribution was calculated from the proportion of sky area visible within the canopy extent [14,[17][18][19].…”

Effects of Fragment and Vegetation Structure on the Population Abundance of Ateles hybridus, Alouatta seniculus and Cebus albifrons in Magdalena Valley, Colombia

“…At each starting point we took a digital photograph of the tree canopy from breast height for canopy density analysis. CanopyDigi software [Goodenough and Goodenough, 2012] was used to estimate the percent of canopy coverage. After the initial point had been selected using dice, subsequent points were randomly selected in a direction dictated by the second hand of an analogue watch 5 m from the previous point.…”

Reptile embryos and climate change: Modelling limits of viability to inform translocation decisions

“…This implies that shade was overestimated and consequently had a net effect of lowering the predicted temperatures relative to observed temperatures. In our study shade and vegetation cover were estimated visually using a quadrat, which is prone to subjectivity and inconsistency (Goodenough and Goodenough, 2012). A combination of gap light analysis from hemispherical photography (Frazer et al, 1999) and use of small quadrats to accurately measure vegetation cover may yield more accurate predictions.…”