Detecting, quantifying, and mapping urban trees' structural defects using infrared thermography: Implications for tree risk assessment and management

Abstract

Urban trees are a fundamental and key component of urban green areas, however, they are subject to several stresses which can compromise their mechanical integrity through the development of defects such as wood decay. In this study, we evaluated the structural health state of trees in four urban parks in the city of Mytilene, Greece, using structural traits of the trees, their trunk surface temperature distribution as recorded using infrared thermography, and spatial statistics both at single tree and at park level. We developed thermal indices by analyzing data from 334 trees belonging to three main species (Robinia pseudoacacia, Morus alba and Melia azedarach). We estimated temperature spatial dependence across each tree trunk using Moran's I index, while statistically significant spatial clusters were assessed using local spatial autocorrelation statistics. Relationships between tree traits, thermal, and spatial indices were established using linear and logistic regression models. Finally, we used the Getis-Ord Gi* statistic for the identification of risky tree hotspots and we applied the kriging geostatistical procedure for mapping of such hotspots. Our results have shown that the thermal and spatial indices can sufficiently predict different types of structural defect, and to identify hotspots of risky trees and their spatial extent. This approach can successfully contribute to tree risk assessment for a more effective urban park management.