A Model Combining Forest Environment Images and Online Microclimate Data Instead of On-Site Measurements to Predict Phytoncide Emissions

Abstract

In the existing phytoncide-prediction process, solar radiation and photosynthetically active radiation (PAR) are difficult microclimate factors to measure on site. We derived a phytoncide-prediction technique that did not require field measurements. Visual indicators extracted from forest images and statistical analysis were used to determine appropriate positioning for forest environment photography to improve the accuracy of the new phytoncide-prediction formula without using field measurements. Indicators were selected from the Automatic Mountain Meteorology Observation System (AMOS) of the Korea Forest Service to replace on-site measured climate data and the phytoncide-prediction equation was derived using them. Based on regression analyses, we found that forest density, leaf area, and light volume above the horizon could replace solar radiation and PAR. In addition, AMOS data obtained at 2 m altitudes yielded suitable variables to replace microclimate data measured on site. The accuracy of the new equation was highest when the surface area in the image accounted for 25% of the total. The new equation was found to have a higher prediction accuracy (71.1%) compared to that of the previous phytoncide-prediction equation (69.1%), which required direct field measurements. Our results allow the public to calculate and predict phytoncide emissions more easily in the future.

Effects of Plant-Emitted Monoterpenes on Anxiety: A Propensity-Matched Observational Cohort Study

“…The elucidation and quantification of a specific healing mechanism of forest environments can offer a powerful tool to direct the widespread efforts to plan and optimize forest therapy trails, often relying on the prediction of MT concentration based on plant species and meteorological variables [31,32,34,76].…”

“…MT emission rates and chemical profiles vary widely among different species of forest trees [28,29], and they depend on physiological (plant age and developmental stage), and physicochemical factors, i.e., related to leaf structure (presence or absence of storage structures, stomatal openness) [30]. The individual perception of benefits induced by plant-emitted MTs stimulated research efforts to expedite the modeling and prediction of forest emissions [31,32], along with preliminary studies aimed at predicting nose-level concentrations of BVOCs [33]. Important efforts have also been made to design forest therapy programs and trails based on potential emissions of BVOCs released by dominant plant species [34].…”

“…Recently, several studies aimed at assessing and quantifying BVOCs in forest sites have been published [20,31,32,35,36], owing to the need of gaining further insights into forest characteristics potentially related to specific effects on health outcomes [34,[37][38][39][40][41][42].…”

Effects of Plant-Emitted Monoterpenes on Anxiety Symptoms: A Propensity-Matched Observational Cohort Study

“…MT emission rates and chemical profiles vary widely among different species of forest trees [28,29] and they depend on physiological (plant age and developmental stage) and physicochemical factors, i.e., related to leaf structure (presence or absence of storage structures and stomatal openness) [30]. The individual perception of benefits induced by plant-emitted MTs has stimulated research efforts to expedite the modeling and prediction of forest emissions [31,32], along with preliminary studies aimed at predicting nose-level concentrations of BVOCs [33]. Important efforts have also been made to design forest therapy programs and trails based on potential emissions of BVOCs released by dominant plant species [34].…”

“…Recently, several studies aiming at assessing and quantifying BVOCs in forest sites have been published [20,31,32,35,36], owing to the need to gain further insights into forest characteristics potentially related to specific effects on health outcomes [34,[37][38][39][40][41][42].…”