Investigating the potential of thermal infrared UAS imagery for detecting the health status of pine trees

Natural and anthropogenic stressors such as increasing drought, pests, and diseases exert increasing pressure on the condition of forests. Forest health assessment, mapping and monitoring are crucial for targeted management interventions and conservation. Direct forest health assessment in the field, although accurate, is a labour-intensive approach. Remote sensing (RS) is widely used in forest health assessment to create standardized methods that reduce subjectiveness, extrapolate observations in unvisited, inaccessible areas and reduce labour and costs. Unmanned Aerial Systems (UAS) have gained popularity in many forest-related management activities and research. Stress in trees causes a change in their physiological process, resulting in a temperature rise of the canopy. Thermal infrared (TIR, 7.5 -13.5 μm) remote sensing data can detect such canopy temperature changes. Previous research has confirmed the ability of UAS imagery to detect plants' health status. This study aims to investigate whether UAS-TIR imagery can be used to accurately map the health status of Pine trees (Pinus brutia). The usefulness of UAS acquired thermal data was examined in an open Mediterranean Pine forest in west Crete, Greece. The UAS campaign was conducted between 1 and 2 September 2021 over two sites covering 105.9 hectares. During fieldwork, the defoliation and decolouration of individual trees were recorded, and preliminary analysis was done using 56 observation data. Average canopy temperature was calculated for the delineated crowns and used to classify trees health status. In line with past research in other ecosystems, the present study results indicate a positive but weak correlation between defoliation and canopy temperature (R= 0.38). Further investigation is needed to assess the performance of thermal data in combination with multispectral and hyperspectral imagery.