Using fractal analysis of crown images to measure the structural condition of trees

Observations of tree canopy structure are routinely used as an indicator of tree condition for the purposes of monitoring tree health, assessing habitat characteristics or evaluating the potential risk of tree failure. Trees are assigned to broad categories of structural condition using largely subjective methods based upon ground-based, visual observations by a surveyor. Such approaches can suffer from a lack of consistency between surveyors; are qualitative in nature and have low precision. In this study, a technique is developed for acquiring, processing and analysing hemispherical images of sessile oak (Quercus petraea (Matt.) Liebl.) tree crowns. We demonstrate that by calculating the fractal dimensions of tree crown images it is possible to define a continuous measurement scale of structural condition and to be able to quantify intra-category variance of tree crown structure. This approach corresponds with traditional categorical methods; however, we recognize that further work is required to precisely define interspecies thresholds. Our study demonstrates that this approach has the potential to form the basis of a new, transferable and objective methodology that can support a wide range of uses in arboriculture, ecology and forest science.