Chan-Ryul Park

Forest type maps require periodic revision, yet field inspection of every stand is impractical. This study tested whether stand-level disagreement between a Sentinel-2 U-Net classifier and the Republic of Korea’s forest type map could support screening for revision. A seven-class U-Net was trained using seasonal Sentinel-2 composites from 2025, and pixel predictions were aggregated to forest stands. Disagreeing stands passing dominance and confidence thresholds were flagged and assessed by blinded interpreters using high-resolution basemaps supplemented by Sentinel-2 composites. Stand-level agreement with the map was 0.69 by stand count and 0.76 when area-weighted. In the primary analysis, high-precision-class flags were mismatched in 41.3% of interpreted stands (29.7% when population-weighted), compared with 7.7% of controls. Test-set class precision, the pre-specified prioritization criterion, did not distinguish more reliable flags in this analysis. An exploratory partition by flag type yielded weighted rates of corresponding mismatches of 80.9% for stocking-status flags and 26.0% for species-dominance flags, representing 12.3- and 2.4-fold enrichment over their respective region-wide baselines. Approximately 35% of flagged stands were estimated to be mismatches, and the flags captured approximately 7.5% of estimated mismatches. These findings support model–map disagreement as a potential tool for prioritizing stand verification in the study region.

The urban heat island (UHI) effect exacerbates heat-related health risks and undermines urban sustainability. Urban forests, which serve as essential cooling infrastructure by regulating the urban microclimate and mitigating the UHI effect, are a prominent Nature-based Solution (NbS). We proposed a multi-scale cooling network framework for Seoul, South Korea, by integrating 25-year land surface temperature dynamics, circuit theory-based landscape connectivity, and energy-balance modeling. Based on size and cooling effect, urban forests were classified into a three-tiered node hierarchy: 60 priority core patches (PCPs) functioning as persistent cooling islands since 1999, 271 core patches, and 29,450 small patches of less than 2 ha. Using Linkage Mapper and Circuitscape, we mapped 137 active cooling corridors among the PCPs, explicitly identifying priority barriers (areas impeding flow) and pinch points (areas of concentrated airflow) at the 90th percentile. To supplement the network at the landscape scale, the 271 core patches were categorized into four actionable management quadrants based on their structural connectivity and cooling intensity. Furthermore, we assessed cooling potential by quantifying the temperature reduction effects of targeted tree cover interventions within the critical barrier and pinch point zones using the i-Tree Cool Air model. Ultimately, the three-tiered hierarchical management framework proposed in this study can be utilized to implement strategic urban forest management and climate adaptation interventions linking city, landscape, and site scales.

With accelerating urbanization, urban forests have gained attention as a potential solution for reducing fine particulate matter (PM2.5). However, while trees reduce PM2.5 through foliar adsorption and uptake, they may simultaneously promote its formation by emitting biogenic volatile organic compounds (BVOCs). To elucidate the spatiotemporal variation in PM2.5 reduction by urban forests and its sources, seasonal changes in PM2.5 concentrations and stable carbon and nitrogen isotope ratios (δ13C, δ15N) were examined in two regions. In Gomae, PM2.5 was analyzed along a gradient from the expressway edge into the forest interior, whereas in Sihwa, across an industrial complex and a residential area separated by an urban forest. During the growing season, δ13C was depleted, indicating a BVOC contribution to PM2.5 formation. Nevertheless, concentrations inside the forests remained lower than outside, confirming that removal outweighed formation. This difference, however, disappeared during the non-growing season, indicating that leaf presence and physiological activity are key to PM2.5 reduction. In Sihwa, δ15N was enriched during the non-growing season, indicating increased coal combustion, whereas no seasonal difference occurred in Gomae, suggesting a persistent vehicle influence. Receptor modeling revealed that source contributions shifted with wind direction and that PM2.5 reflected both local sources and long-range transport up to 48 hours earlier. Overall, urban forests clearly mitigate PM2.5, but this effect weakens during the non-growing season, when air-quality management is most critical. Our findings therefore emphasize that PM2.5 mitigation through urban forests must proceed in parallel with emission reduction at the source.

The urban heat island (UHI) effect exacerbates heat-related health risks and undermines urban sustainability. Urban forests, which serve as essential cooling infrastructure by regulating the urban microclimate and mitigating the UHI effect, are a prominent Nature-based Solution (NbS). We proposed a multi-scale cooling network framework for Seoul, South Korea, by integrating 25-year land surface temperature dynamics, circuit theory-based landscape connectivity, and energy-balance modeling. Based on size and cooling effect, urban forests were classified into a three-tiered node hierarchy: 60 priority core patches (PCPs) functioning as persistent cooling islands since 1999, 271 core patches, and 29,450 small patches of less than 2 ha. Using Linkage Mapper and Circuitscape, we mapped 137 active cooling corridors among the PCPs, explicitly identifying priority barriers (areas impeding flow) and pinch points (areas of concentrated airflow) at the 90th percentile. To supplement the network at the landscape scale, the 271 core patches were categorized into four actionable management quadrants based on their structural connectivity and cooling intensity. Furthermore, we assessed cooling potential by quantifying the temperature reduction effects of targeted tree cover interventions within the critical barrier and pinch point zones using the i-Tree Cool Air model. Ultimately, the three-tiered hierarchical management framework proposed in this study can be utilized to implement strategic urban forest management and climate adaptation interventions linking city, landscape, and site scales.

Urban forests (UFs) are increasingly promoted as a nature-based solution for mitigating particulate matter (PM) pollution, yet their removal performance can vary depending on surrounding emission sources and environmental conditions. Here, we quantified the particulate matter reduction efficiency (PMRE) of UFs located near roads, industrial complexes, and urban areas, together with background forests in South Korea, based on field observations during the late autumn–spring period across two consecutive years (November–May in 2021–2022 and 2022–2023). We applied vector autoregression (VAR) to examine the dynamic relationships between PMRE and meteorological and air pollutant variables across eight representative sites. The results revealed that PM mitigation dynamics were strongly particle-size-dependent and context-specific. Across all sites, ΔPM₁₀ RE was predominantly self-driven, explaining over 90% of its own variance, whereas fine-particle dynamics showed stronger interdependence. In particular, ΔPM_2.5 RE consistently acted as a key mediator, accounting for up to 70%–80% of the variation in ΔPM_1.0 RE depending on source context. Industrial-complex-adjacent UFs exhibited the strongest cross-variable interactions, while urban-core UFs were largely governed by intrinsic mitigation processes. Roadside UFs showed site-specific responses associated with CO and temperature variability. Notably, PMRE responses exhibited damped oscillation patterns across all source contexts, converging toward equilibrium over time, indicating stabilization of mitigation performance following disturbance events. These findings demonstrate that urban forest air-quality benefits are highly context dependent and governed by particle-size-specific dynamics. Our results provide evidence-based guidance for designing and managing urban forests, emphasizing the need for source-specific strategies and prioritization of PM_2.5-oriented mitigation, particularly in industrial and roadside environments where fine-particle interactions are strongest.

We analyzed the effect of reducing particulate matter in a forest by comparing concentrations and particle number concentrations (PNCs) between urban and background forest areas with the use of aerodynamic particle sizers. PM was observed at forest and urban sites during the high particulate matter events from 22 to 30 April 2019. Comparing the PM concentrations measured, PM₁₀ and PM_2.5 were 61.6 μg/m³ and 36.9 μg/m³, respectively, in the urban site, while PM₁₀ and PM_2.5 were 53.9 μg/m³ and 31.8 μg/m³, respectively, in the forest site. Most PNCs at both sites ranged in particle size from less than 0.5 μm (99%). During high-concentration events, the mass concentration of PM10 was not significantly different, but PNCs of the accumulation mode particles (≤0.5 µm) and coarse mode particles (>0.5 µm) were differed between two sites. The re-duction rate of coarse mode particles (>0.5 µm) was lower 20% at large urban green space. A large urban green space showed the high slope value of decrease at the relationship between aerodynamic diameter and PNC at all times. These results indicate that not only mass concentration but PNC could support to understand the PM traits at large urban green space during the PM pollution of episode.

Urban forests offer a range of environmental, climatic, economic, and social benefits to citizens. However, these effects have not been systematically measured owing to the localized nature of urban forests. This study developed a framework to assess the effects of urban forest ecosystem services and elucidate the service and benefit pathways of its indicators. Two PRISMA-guided scoping reviews were conducted using Web of Science and Scopus to identify English peer-reviewed articles (2015–2024) on the effects of urban forests and indicators. The studies on the urban forest effects were analyzed to systematically code and classify the criteria, effects, methods, and techniques based on the nature-based solutions. In terms of indicators, the ecosystem service cascade was employed to organize indicators across four pathways with structures/function, service, benefit, and value. The review revealed that temperature regulation, air pollution reduction, and carbon sequestration were the most studied effects, followed by social effects; in contrast, economic benefits and sound and noise were the least studied and assessed. Furthermore, indicator pathways were found to vary by effects. Drawing on this scoping review, a standard and expanded indicator assessment framework was developed. The proposed framework provides a decision-support tool to assess urban forest performance based on evidence, facilitating link between biophysical properties and human outcomes.

We analyzed the effect of reducing particulate matter in a forest by comparing concentrations and particle number concentrations (PNC) between urban and forest areas with the use of aero-dynamic particle sizers. PM is observed at a forest and urban site during the high events of par-ticulate matter from April 22 to April 30, 2019. Comparing the PM concentrations measured, PM10 and PM2.5 were 61.6㎍/㎥and 36.9㎍/㎥, respectively in urban, while PM10 and PM2.5 were 53.9㎍/㎥, 31.8㎍/㎥, respectively, in forest. PNCs are classified by particle size and analyzed by dividing them into 0.5㎛. Most PNCs at both sites ranged in size of particles less than 0.5㎛ (99%). Comparing the distribution of PNC in the forest, the smaller the particle size, the higher the reduction rate. In low concentration events, the ratio of coarse mode particles (>0.5㎛) among forest PNC distributions was similar to that of urban, but the reduction rate of coarse mode particles was 20% in the high concentration event. For accumulation mode particles (< 0.5㎛), forests were 18% lower in low concentration events and 11.5% lower in high concentration events. These results indicate the forest can have the capacity to reduce the accumulation mode particles during high concentrations of PM.