Earticle

Due to population growth in Türkiye, demand for wood-based raw materials continues to demonstrate an upward trend. Despite increased mechanization, the preference for chainsaw use in the cutting phase remains high. Since this still involves labor-intensive work, it is important to reduce risk factors in terms of worker health and safety. When cutting is carried out with a chainsaw, many air pollutants such as bark residues, dust, sawdust, fuel material, etc. are expelled into the environment. This situation reduces the air quality for the workers and environment. This study aims to investigate the impact of the cutting process on worker health and environmental impacts in stone pine (Pinus pinea L.) plantations in Sarıyer region. The air pollution parameters PM2.5, PM10, CO2 and HCHO levels during the cutting process were measured using a Temtop M2000 air quality meter. The results showed that when comparing these values to standard air quality metrics, it's clear that the peak values of PM2.5, PM10, and CO2 result in a "Unhealthy" environment. The average values for all three are classified as "Unhealthy" for PM2.5, and "Moderate" for PM10 and CO2. Based on the identified results, risk factors need to be determined, and corresponding measures must be taken. In this context, the use and design of personal protective equipment is significant. Updates to designs and information dissemination need to be carried out based on risk factors. There is also a need to raise awareness and provide training for forest workers on the use of protective equipment. These findings may contribute to the development of effective policies on the health of workers in wood production and environmental air quality.

Rainfall-induced landslides are mainly triggered by the change of soil moisture (soil water content) that affects the stability of surface soils. Recently, various monitoring methods have been applied to measure the change in soil water content in the field. However, there is a lack of direct correlation between the soil water content and the susceptibility of landslides. This study presents a framework to assess landslide susceptibility based on field soil water content monitoring data. The relationship between the soil water content and the landslide risk is estimated by using soil water characteristic curve that describes the correlation between the soil water content to the soil matric suction. The method was tested in a study area that widely monitored via wireless sensor network during rainy season. Based on comparison of landslides susceptibility assessment results for two conditions - the wetting process condition (in-field) and the drying process condition (in-laboratory), the safety factor of landslides was lower for wetting conditions than in the drying condition. As a result, applying the wetting condition, which represents the field condition, during the conversion from soil water content to matric suction solves the problem of underestimating landslide susceptibility when applying the drying condition, which represents the laboratory condition.

In Korea, where 63% of the land is mountainous, damage caused by shallow landslides is increasing annually. Therefore, it is crucial to evaluate shallow landslide and debris flow risks at the small mountain watershed scale and devise effective mitigation measures. This study assessed the potential for shallow landslide initiation and debris flow extent in a 16-ha small mountain watershed in Mungyeong-si, Gyeongsangbuk-do, using physics-based models, and evaluated the impact of check dam installation on damage reduction. TRIGRS (USGS) was employed for landslide simulation and RAMMS (WSL) for debris flow simulation. Both models used a 5-m DEM, and model parameters were estimated based on field measurements and conditions of nearby affected watersheds. TRIGRS simulation results identified 17% of the watershed as unstable (FS < 1), and potential collapse points were selected by comparing with the landslide hazard map. RAMMS simulations based on these points showed a debris flow area of 10.43 ha without a check dam, which decreased to 8.37 ha with the dam installed. Notably, debris flow impact downstream of the check dam was reduced by 78% after installation, significantly mitigating risk to nearby infrastructure. This study empirically examines the applicability of a physics-based model and the mitigation effect of check dams, and it is expected to serve as foundational data for planning related to mountain sediment disasters.

Landslides are a significant forest disaster in the Republic of Korea, resulting in considerable fatalities and property damage. Since the 1980s, the National Institute of Forest Science (NIFoS) has conducted numerous studies on non-structural methods to mitigate landslides, such as early warning systems and susceptibility mapping, to lessen the impact of these events. Based on the TANK model, an early warning system for landslides was developed to assist in decision-making regarding preparedness and to organize evacuations for local communities. A nationwide landslide susceptibility map with five levels was created using logistic regression, taking into account geological, geographical, and forest characteristics. Furthermore, NIFoS provides crucial data for prioritizing evacuations by debris-flow hazard zonation and evaluating societal vulnerability in the area. To improve public awareness about landslide hazards and current risks in the area, all this information is accessible through the WebGIS platform known as the “Landslide Information System.”

This study aimed to identify key factors influencing landslides and analyze their relationships in mountainous areas altered by forestry activities, such as timber harvesting and forest road construction. The study areas included Yeongju and Yecheon (2020) and Jecheon and Chungju (2023), where landslides had previously occurred. A total of 661 landslide occurrence sites and 661 randomly selected non-occurrence sites from the same watersheds were analyzed using logistic regression. Ten variables were used, including nine environmental factors Topographic Wetness Index (TWI), slope, curvature, slope length, soil depth, tree diameter class, bedrock type, aspect, and forest type and one variable representing forestry activity type. The dataset was divided into training (70%) and testing (30%) sets, and a logistic regression model was developed using backward elimination conducted across 100 iterations. The model with the highest AUC (AUC = 0.792) was selected as optimal. Based on z-values, the most influential factors were slope curvature, forestry activity (forest roads), and tree diameter class. Odds ratio analysis revealed that forestry activity (forest roads), tree diameter class, north-facing slope aspect, slope curvature, and slope angle had the strongest influence on landslide occurrence. Overall, forestry activity areas, particularly forest roads and timber harvesting sites, were more strongly associated with landslide occurrence than other environmental variables. These results indicate the need for more targeted research on forestry-impacted slopes and emphasize the importance of incorporating indicators that reflect the specific nature of forestry activities, rather than simply their presence.

Forestry education requires an outdoor-focused educational system beyond just theoretical coursework. In this context, field studies are conducted within forestry programs. Additionally, internships and field training are provided throughout academic terms. In Turkiye's forestry education system, there are 4-year forest engineering programs and 2-year vocational college forest technician programs. Some colleges and universities offering forestry education lack adequate opportunities for field experience. Many problems arise due to various factors such as being distant from forest areas, economic and logistical issues, and the need to obtain special permissions for site visits. Within this context, it is believed that virtual reality education for students who are far from forest areas will provide an opportunity to conduct studies similar to actual field work. Previous research shows increasing use of virtual reality in the education sector. In forestry, studies have been conducted using various simulators, software with 360- degree cameras, and game engineering. This study has been prepared to examine previous studies and identify their gaps and contributions as part of the first phase of a project aimed at evaluating virtual reality opportunities within a 2-year forestry program. Previous studies have indicated benefits such as increased understanding of forest ecosystems, increased interest in forestry, and reduced real-world risks.

Aggressive forest management to improve wood utilization is one of the effective measures to mitigate global warming through the CO2 sequestration function of forests. There are accumulated life cycle assessment (LCA) data for CO2 emission by manufacturing various products in Japan. For example, a possible CO2 emission reduction potential through the use of wood material can be estimated for the conversion of non-wood materials such as steel. We estimated the effect using existing related literature as well as a commercial LCA database, AIST-IDEA. The result indicated that the possible CO2 emission reduction potential by using wood material for domestic houses would be negative including the construction process, even considering the CO2 storage potential for houses. However, the potential value of using wood material for domestic houses would be much better compared to that of steel houses. We will also make a similar estimation for Taiwan, where progressive forest management has recently started to reduce CO2 emissions.

Traditionally male-dominated, forest engineering has seen a notable rise in women’s involvement in both education and the profession. University education is a pivotal phase where students develop professional identities and form perceptions about their future careers. For women students, experiences gained during this phase are significant not only for individual career planning but also for promoting gender equality, enhancing sectoral diversity, and increasing the visibility of women engineers within the profession. However, scientific studies addressing women students’ perceptions of the profession, their reasons for choosing it, and their expectations remain limited. This study aims to examine the perspectives of women undergraduate students in the Department of Forest Engineering at Bursa Technical University, Türkiye, on the profession, their views on acquiring professional competencies, and their perceptions of gender inequality both during their studies and throughout their future careers. Additionally, the study explores male students' perceptions on these issues. A survey form was designed based on literature and expert input, covering four areas: (i) student profiles and choice motivations, (ii) views on the profession and career, (iii) opinions on developing professional skills, and (iv) perceptions of gender inequality in the profession. The survey was conducted with 176 students of different year groups. Descriptive analyses and difference tests were applied to the collected data. Key findings indicate that 15.7% of women students chose the department due to family influence, 71.1% perceive greater challenges for women in the sector, and 54.2% believe women must exert more effort to secure employment.

In heterogeneous landscapes, high-resolution land cover classification is vital for planning, ecological monitoring, and green infrastructure management. This study evaluates the performance of five machine learning algorithms: Decision Tree (DT), Naïve Bayes, Support Vector Machine (SVM), Random Tree (RT), and K-Nearest Neighbors (KNN), using UAV multispectral imagery and object-based image analysis (OBIA). Five scenarios were designed to compare algorithm accuracy. Additionally, a sixth scenario applied the best-performing algorithm to a feature subset selected through Recursive Feature Elimination (RFE), to examine the effect of feature optimization. RT achieved the highest overall classification accuracy (76.75%) and Kappa coefficient (0.7066), while SVM showed limited performance in complex environments. Height features contributed most to accuracy improvements, followed by spectral and geometric features. In class-specific analysis, the Naïve Bayes algorithm yielded the highest Producer’s Accuracy (90.86%) for forest-type land cover but had a lower User’s Accuracy (70.41%), indicating overclassification. In contrast, RT showed more balanced performance (PA = 87.09%, UA = 85.71%), suggesting greater reliability. The results demonstrate the benefits of integrating algorithm selection with feature optimization to improve classification accuracy in complex settings. This approach provides methodological insights for fine-scale mapping of vegetated areas and supports future applications in landscape monitoring and urban green space assessment.

Fire-induced hydrophobic soil layers inhibit rainfall infiltration, increase surface runoff, and contribute to soil erosion and secondary disasters such as landslides. Understanding the spatiotemporal patterns of soil water repellency after wildfires is crucial. This study analyzed temporal changes in soil water repellency according to wildfire burn severity (severe, moderate, low) and slope steepness (steep, moderate, gentle) in wildfire-affected forests in South Korea (Yeongdeok, Uljin, and Hapcheon) between 2022 and 2023. Soil water repellency was assessed immediately after the fire and at 6, 12, and 24 months using the Molarity of Ethanol Droplet (MED) method, with measurements taken at 1-cm intervals down to 5 cm soil depth. Higher wildfire burn severity and steeper topography formed strong water-repellent layers (MED ≥5) down to 5 cm depth. In the Yeongdeok forest, strong repellency at the 0–1 cm depth was observed, representing 66% in severely burned moderately sloped and moderately burned gently sloped sites, and 100% in moderately burned steeply sloped sites, but fully recovered to hydrophilic soils by 12 months. In the Uljin forest, soil water repellency persisted down to 4 cm depth at 12 months but largely disappeared by 24 months. In the Hapcheon forest, hydrophobic soil characteristics extended to 5 cm soil depth and persisted at 2–4 cm depths even after 24 months in severely burned areas.

Tap root and lateral root systems of trees have long been recognized for enhancing slope stability by reinforcing soil strength. Among these, the lateral root system is particularly effective in preventing shallow landslides. In South Korea, where forest soils are relatively shallow, the role of tree roots in stabilizing slopes is becoming increasingly important. This study aimed to evaluate the root cohesion of four major tree species in South Korea: Pinus densiflora, Pinus koraiensis, Larix kaempferi, and Quercus mongolica. To achieve this, we investigated the spatial distribution of their lateral root systems using the profile wall method in an experimental forest at Kangwon National University. In addition, the relationship between root diameter and tensile strength was assessed in the laboratory using a universal testing machine. Based on the findings, root cohesion was estimated using the Wu model. For all species, the number of roots and root area ratio decreased with increasing soil depth, although the extent of decrease varied by tree species. A power-law regression model effectively described the relationship between root diameter and tensile strength in all species. The average root tensile strength was higher in Q. mongolica (22.2 MPa) and L. kaempferi (20.2 MPa) than in P. densiflora (15.9 MPa) and P. koraiensis (15.0 MPa). Root cohesion estimated using the Wu model was 1.5 to 5.1 times higher than that measured by the direct shear test. After applying a reduction coefficient, root cohesion estimated by the Wu model was highest in Q. mongolica (12.9 kPa), which exhibited the greatest root area ratio and tensile strength, followed by P. koraiensis (9.1 kPa), P. densiflora (9.0 kPa), and L. kaempferi (4.3 kPa). These results provide useful information for quantifying the role of tree roots in preventing shallow landslides and can support the establishment of forest disaster management strategies.

In forested areas, rainfall changes in size and velocity as it passes through the canopy, resulting in throughfall with physical characteristics that differ from those of gross rainfall. These differences can affect soil erosion processes, highlighting the need for a clearer understanding of throughfall dynamics. This study compared the drop size distribution (DSD) and kinetic energy (KE) of raindrops in throughfall and gross rainfall using data from three optical disdrometers. The disdrometers were installed at three locations on the Chuncheon campus of Kangwon National University: a Korean pine (Pinus koraiensis) stand, an oak (Quercus mongolica) stand, and an open site. Results showed that total rainfall was greater at the open site than in the forest stands. However, the number of raindrops smaller than 1mm in diameter was higher in throughfall. In terms of volume ratio by drop diameter class, raindrops smaller than 3 mm were more dominant in gross rainfall, while those larger than 3 mm were more prevalent in throughfall. During the same rainfall events, the DSD of throughfall was more varied than that of gross rainfall. Notably, in the oak stand, throughfall during the leaf-fall period closely resembled the DSD of gross rainfall. Additionally, hourly KE analysis revealed that throughfall carried greater energy than gross rainfall, indicating a higher potential for impacting the forest floor. These findings suggest that throughfall exhibits a more diverse DSD than gross rainfall, primarily due to the splashing and aggregation of raindrops on foliage and branches. A better understanding of these patterns is essential for improving the accuracy of soil erosion modelling in forested areas.

Climate change has increased both the frequency and intensity of forest fires in recent years, raising concerns about secondary disasters such as soil erosion and shallow landslides in fireaffected forests. To prevent these secondary disasters, various techniques, such as mulching and seeding, have been implemented globally to support forest restoration. Furthermore, Naturebased Solutions (NbS) have gained international attention in recent years as an effective approach for both disaster mitigation and the restoration of fire-damaged forest ecosystems. This study aimed to conduct a comparative bibliometric analysis of research trends related to the restoration of fire-affected forests and the application of NbS in South Korea and abroad. Domestic research articles were collected using the RISS database, while international research articles were sourced from the SCOPUS database, covering the period from 1980 to 2024. Research on wildfire restoration has primarily focused on data-driven restoration and management strategies, analysis of forest ecosystem resilience to fire intensity, and the relationship between soil properties and vegetation recovery. Studies on NbS in fire-affected forests have emphasized their role in forest restoration and management, as well as the evaluations of effectiveness and policy-related approaches. In South Korea, research has mainly addressed ecosystem recovery, forest management, and soil biodiversity following wildfires. However, studies specifically exploring restoration techniques that incorporate NbS remain limited. Therefore, further investigation into such techniques, along with postmonitoring evaluations of their effectiveness, is essential for the sustainable management of wildfire-affected forests.

In recent years, the frequency of earthquakes and heavy rainfall has increased, leading to unprecedented damages caused by landcreep, a type of slow-moving landslide. Due to the slow movement of soil layers without rapid topographic changes, landcreep is difficult to detect in advance and often results in significant damage. However, research on landcreep occurrence remained limited in the Republic of Korea. This study assessed the landcreep susceptibility in mountainous forests using the Weight of Evidence (WOE) method, a statistical approach commonly used in natural hazard analysis. With independence tests and the explanatory power of landcreep occurrence factors, five landcreep susceptibility models were developed by combining different factors. The developed models were evaluated by comparing the frequencies of landcreep occurrences according to the landslide susceptibility index (LSI) and the areas under the receiver operating characteristic curves (AUCs). Among the models, Model 3, which incorporated elevation, slope, forest type, bedrock type, distances to faults, roads, and streams, and plan curvature, exhibited the best performance with an AUC of 63.2%. Additionally, the validation efforts using independent datasets resulted in a final AUC of 59.4%. Although the predictive accuracy was relatively moderate, the WOE-based model remains a useful tool for identifying vulnerable areas and supporting disaster management for landcreep in the country.

Accurate measurement of tree diameter at breast height (DBH) is crucial for forest management and biomass estimation. This study aimed to assess the accuracy of DBH measurements obtained using the LiDAR sensor on an iPhone through two different data collection methods: (1) walk-through scanning by walking past the trees and (2) walk-around scanning by walking around each tree. Manual measurements with a diameter tape served as the reference standard. Data were collected from three experimental plots in a teak plantation. The accuracy of each method was evaluated using mean absolute error (MAE), root mean square error (RMSE), and bias. Additionally, paired t-tests were conducted to determine the statistical differences between methods. The study also considered the time required for data collection to assess efficiency. Results indicated that the walk-around scanning method provided significantly higher accuracy compared to the walk-through method, although it required more time. These findings suggest that the walk-around iPhone LiDAR scanning approach is more suitable for applications requiring high precision in tree measurements, while the walk-through method could be used for rapid surveys when time efficiency is prioritized.

Türkiye maintains a substantial forest coverage of 21.5 million hectares, representing 26.6% of its total territory. A significant portion - approximately 75% - of these forested areas is situated on challenging terrain with gradients exceeding 40%. In Turkish forestry operations, transportation is accomplished through three primary methods: manual labor, animal-based transport, and mechanical systems. Skylines are used for primary transport device. These skylines are Koller K300, URUS MIII, Gantner and Tajfun MOZ 500GR skylines. Koller K300, URUS MIII and Gantner skylines were used during logging from forest areas of mountainous Eastern Black Sea Region of Turkey. In Turkey, forest skylines are various categories such as 1) short distance skyline (300 m – Koller K300), 2) middle distance skyline (600 m and 800 m – URUS MIII and MOZ 500GR) and 3) long distance skyline (1500 m – Gantner). This research synthesizes findings from multiple studies conducted by researchers across Türkiye. Our assessment examines the productivity metrics, cost-benefit analysis, and practical implementation approaches of skyline systems utilized in forest management operations. Furthermore, each study provided detailed operational parameters including transportation distances, product specifications, quantity metrics, terrain gradients, and volumetric data. For the Koller K300 and URUS MIII skylines, the average efficiency at a distance of 225 m and 600 m was determined as 7.20 m³/h and 4.84 m³/h, the average cost was determined as $8.27/m³ and $5.24/m³. For the Gantner and MOZ 500 GR, the average efficiency at a distance of 1050 m and 125 m was determined as 4.34 and 6.85 m³/h and the average cost was determined as $9.04/m³ (For Gantner).

Forest fires significantly impact forest ecosystems through tree mortality, necessitating scientific understanding of factors influencing post-fire survival for effective forest management. Using three predictive modelling approaches, this study identified critical factors affecting post-fire survival in Pinus densiflora (Korean red pine), a dominant species in Korean forest. We examined 734 fire-damaged pine trees across four burn sites, collecting data through field surveys, remote sensing, and meteorological observations. Three predictive models (logistic regression, Cox proportional hazards, and random forest) were compared to identify survival factors. The random forest model demonstrated superior performance with an AUC of 0.924 and sensitivity of 0.8919, due to its ability to capture non-linear relationships between variables. For tree-specific factors, diameter at breast height (DBH) and bark scorch index (BSI) emerged as key mortality indicators. Among topographic and meteorological factors, slope, elevation, isothermality, and temperature seasonality significantly influenced survival outcomes. Survival probability ranged from 16.9% to 77% depending on these variables. Notably, the influence of these factors on mortality became more pronounced 12 months after fire occurrence. This research provides a scientific basis for ecological management and restoration strategies in fire-affected P. densiflora forests, which constitute a significant portion of South Korea's forest ecosystem.

The Korea Forest Service is pushing for the creation of solid forest roads as part of its policy to prevent damage due to sedimentary disasters caused by abnormal climate conditions. However, concerns regarding the negative contribution of forest roads to forest landscape have also been raised. In this study, we evaluated impact of forest road surfaces with three materials (concrete, crushed stone, and soil) on landscape, which are commonly applied to forest road construction in South Korea. Here, we tried to use human physiological and psychological indicators for the evaluation and recruited 39 subjects without the related knowledge or experience. The subjects remained stable by viewing the gray screen in the room controlling external factors; viewed images of forest roads presented at random; filled out questionnaires; and took a rest to wash out residual sensitivity. This procedure was repeated for three materials. The result showed that physiological responses of subjects did not differ significantly among road surface materials. However, in the Semantic Differential method, the surface covered with soil was perceived to be much more 'natural' than it with crushed stones. Also, in the Perceived Restorativeness Scale, the road surface covered with crushed stones scored higher in terms of 'legibility' compared to other materials. The Profile of Mood States showed no significant difference among the road surface materials and indicated non-negative responses. Our findings indicate that the surface materials of forest roads do not affect landscape perception and suggest that construction of forest roads should prioritize securing physical stability over aesthetic factors.

South Korea's territory is approximately 62% forested, and urban residential development near mountainous areas has become inevitable. However, localized heavy rainfall from climate change and increased forest destruction have led to a rise in sediment-related disasters in urban mountainous regions. To prevent such disasters, the Korea Forest Service developed a landslide hazard map, but it tends to overestimate risks on steep slopes, showing limitations in accurately predicting landslide occurrences. This study focuses on the Bangbae-dong area in Seoul, where debris flow damage occurred in August 2022. Using a digital terrain model, SINMAP, an infinite slope stability analysis method, was applied to predict landslide-prone areas. Subsequently, FLO-2D, a two-dimensional numerical model, was used to analyze debris flow behavior at locations identified as hazardous by SINMAP. The results classified the area as a slope-type debris flow region, with strong agreement between predicted hazard areas and actual debris flow events. Additionally, it was found that installing debris flow barriers at the affected sites could effectively block debris flows without overflow.

This study analyzed the spatial distribution characteristics of soil moisture content by forest type in the upper Nakdong River Basin (Yeongju and Bonghwa regions) using the WRF-Hydro hydrological model. The model was constructed based on a 30 m × 30 m regular grid structure, with the soil profile divided into four layers. Land cover-specific parameters such as maximum canopy interception capacity per unit area, canopy height, vegetation density, rooting depth, monthly leaf area index, and monthly stem area index were assigned. Soil parameters, including pore distribution, saturated soil moisture content, and saturated hydraulic conductivity, were calibrated according to regional characteristics. Meteorological input data were derived from the Korea Meteorological Administration and Korea Forest Service weather observation networks, quality-controlled, and spatially interpolated using the inverse distance weighting (IDW) method to generate high-resolution input datasets. Model calibration and validation were conducted using forest flow and streamflow observations from 2021. The simulation results showed distinct spatial and temporal differences in soil moisture distribution among forest types. Coniferous forests generally maintained lower soil moisture contents, whereas broadleaf forests exhibited higher soil moisture levels, with mixed forests demonstrating intermediate characteristics. This study provides fundamental data for analyzing hydrological characteristics by forest type using forest hydrological modeling and is expected to contribute to future research on forest water resource management, forest disaster risk management, and climate change adaptation.

Accurate determination of rainfall thresholds is essential for effective landslide prediction and early warning. This study compares two methodologies for analysing landslide-triggering rainfall thresholds in South Korea: one using data from the single nearest station selected through recent site verification, and the other based on averaged rainfall data from multiple nearby observation stations. I–D and E–D curves were derived using quantile regression with consistent rainfall event thresholds, and predictive performance was evaluated using ROCbased classification accuracy (AUC). The single observation station approach exhibited considerable variability, whereas the average-based method produced more stable and consistent threshold estimates. The comparison identifies the strengths and limitations of each approach depending on the availability and distribution of observational infrastructure, providing insights into effective data utilization strategies for landslide early warning systems

Forest ecosystems are increasingly vulnerable to a range of natural disasters such as wildfires, landslides, and windstorms, which cause significant ecological and economic damage. As postdisaster recovery becomes a priority in forest management, the reuse of site-specific byproducts, including timber, debris, and eroded materials, serves as a viable strategy to enhance ecological restoration and support emergency rehabilitation. Despite growing interest, the scientific landscape surrounding forest disaster recovery and the utilization of residual materials remains unexplored. This study aims to synthesize the current body of research on forest disaster recovery and byproduct utilization to prevent secondary disturbances. We conducted a text mining approach to explore the current landscape of research on forest disaster recovery and the utilization of byproducts. We collected a dataset of research abstracts and titles from publicly available databases, such as PubMed, Crossref, and Google Scholar, using targeted keyword queries (e.g., “forest disaster”, “restoration”, “rehabilitation”, “recovery”, “byproduct utilization”, and related terms). The text data were pre-processed to remove stop words and standardize terms. We then conducted word frequency analysis, term co-occurrence mapping, and topic modelling to identify dominant themes, conceptual linkages, and emerging trends. These findings provide a foundational understanding of existing research directions, inform the design of subsequent field-based technology development phases, and help identify emerging opportunities for interdisciplinary collaboration. Ultimately, this literature-based insight will support the development of practical, standardized, and locally adaptable technologies for post-disaster forest restoration and sustainable byproduct reuse, aligned with national and global sustainability goals.

In Korea, many forests are damaged due to forest fires in spring every year. Forest fires have averaged 481 cases per year and 1,087 ha of forest damage has occurred in Korea over the past 10 years. The risk of secondary damage such as soil erosion and landslides is increasing due to rainfall concentrated in the summer after forest fires in spring. This study was conducted to quantitatively compare the difference in soil erosion due to mulching in forest fire-damaged areas and to discuss policy utilization measures to prevent secondary damage. The study site was Uljingun, Gyeongsangbuk-do, Korea, where about 16,301ha of large forest fires occurred from March 4 to 13, 2022. Areas with severe wildfire damage were divided into areas with and without wood chip mulching, and areas without damage were set as controls (total of 3 sites). In addition to forest fire damage and mulching, other environments were selected to be similar, such as pine forest, slope direction (eastern aspect), and gradient (about 55%). A silt fence was installed for soil erosion monitoring, which has been used in research as an economical and effective measurement method (reference). Silt fences were installed in four 5m * 10m sizes (on three sites). In addition, in the forest fire damage area, four silt fences were add installed to monitor the amount of soil erosion depending on the logging in the future. Therefore, in this study, 8 forest fire areas, 8 forest fire-mulching areas, and 4 control areas were used. Mulching used three 72-liter wood chip bags per silt fence. During the study period, the total rainfall was 753 mm. The total soil deposit was 488.38 kg/ha in site 1, 153.15 kg/ha in site 2, and 76.64 kg/ha in site 3. The amount of silt fence deposited was higher with more precipitation, and it was the highest in September-October. The soil deposit was very high in site 1. It was 3.2 times more than site 2 and 6.4 times more than site 3. It is thought that soil erosion was reduced due to the surface covering effect due to mulching. The soil deposit of site 2 was 2.0 times higher than that of site 3. It is thought that urgent restoration is necessary because more soil erosion occurs in forest firedamaged areas than in control areas. As a result of this study, it was quantitatively confirmed that mulching prevented soil erosion. Therefore, mulching may be effective in preventing secondary damage in dangerous areas around houses.

Due to the earthquake in Türkiye, the importance of preventing earthquake damage has increased worldwide. Korea is not safe from earthquakes, either. In 2016 and 2017, a Gyeongju earthquake with a record-high magnitude (ML 5.8) and the Pohang earthquake (ML 5.4) occurred. In addition, in Korea, earthquakes with a magnitude of 3.0 or higher have occurred about 12 times a year on average in the last 10 years (2013-2022), so it is necessary to prepare for damage prevention. The objective of this study is to explain the measures to prevent landslides caused by earthquakes in Korea. Since there are no cases of earthquake-induced landslides in Korea, the evaluation factors were derived by analyzing overseas studies. In addition, the applicability of the landslide hazard map on the national scale of Korea was examined. The earthquake-induced landslide hazard map was also established on a pilot basis based on the fault zone and epicenter of Pohang using seismic attenuation. Finally, an experimental study was conducted for critical rainfall adjustment for early warning after the earthquake. Three soil samples were collected from the cut-slope area in mountains and a direct shear test was performed to calculate the strength parameters according to the change in the water content ratio. In addition, the ring shear test according to the change in the water content ratio and the change in shear strength due to water supply during the shear was analyzed. Since Korea's landslide hazard map reflects topography, geology, and forest floor conditions, it has been shown that it is reasonable to evaluate the risk of earthquake-induced landslides using it. As a result of evaluating the risk of landslides based on the fault zone and epicenter in the Pohang area, the risk grade was changed to reflect the impact of the earthquake. As a result of the direct shear test, the cohesion decreased linearly as it approached the saturation state. When water was supplied during the ring shear test, the maximum shear strength decreased by 65.7-74.8% and the residual shear strength decreased by 53.5-60%. The risk map based on the fault zone is effective when used in the selection of a target site for preventive erosion control work to prevent damage from earthquake-induced landslides. In addition, the risk map based on the epicenter can be used for efficient follow-up management in order to prioritize damage prevention measures, such as to investigate the current status of landslide damage after an earthquake, or to restore the damaged area. Also, it is more likely that landslides will occur due to rainfall after the earthquake.

In this study, we analyzed the effect of forest damage caused by forest fires or shallow landslides on the rainfall thresholds needed to initiate bedload transport in mountain watersheds. Two bedload monitoring systems were used: a slot sampler and a hydrophone. These were installed in a forest fire-damaged site, a shallow landslide-damaged site, and a control site. A total of 199 effective rainfall-bedload data were collected from 2014 to 2016. Total rainfall amount (TR) and peak rainfall intensity (PRI) were found to be the most effective rainfall indices to predict bedload transport initiation. We also used linear functions to estimate percent threshold lines of the rainfall indices and used performance evaluations to select a representative threshold line for each site. As a result, the forest fire-damaged and shallow landslide-damaged sites had lower TR and PRI reference values than the control site, indicating that lower TR and PRI values can initiate bedload transport in damaged mountain forest areas. Although our study results may be limited by different characteristics between the study sites and insufficient data collection, it still indicates that forest damage caused by forest fires and shallow landslides affects bedload transport. Future studies are needed to further confirm these findings.

Climate change is a significant global concern. The primary cause of climate change is the greenhouse effect induced by greenhouse gas. Carbon dioxide (CO₂) is the most prevalent greenhouse gas, and it is produced in significant quantities from the combustion of fossil fuels. Various initiatives are underway to mitigate carbon emissions, and forests are again being recognized for their capacity to sequester carbon. Bamboo is a fast-growing plant identified as a promising species for carbon storage. In this study, 188 sites were selected from bamboo forests across South Korea. The biomass of bamboo was analyzed by region and species to compare and evaluate carbon stocks. The carbon storage of bamboo forests by region was found to be proportional to forest area. Accordingly, Jeollanam-do and Gyeongsangnam-do had higher levels of carbon storage. In terms of carbon storage by bamboo species, Phyllostachys edulis forests stored more carbon than those dominated by Phyllostachys reticulata or Phyllostachys nigra var. henonis. This greater carbon storage in Phyllostachys edulis forests is attributed to the species’ larger culm diameter and thicker culm walls compared to the other bamboo species. These findings can serve as a valuable reference point for formulating future afforestation policies that employ bamboo as a key component.

Many tree species produce sap, which has been utilized in various ways, including as a food source, since ancient times. In Korea, Acer pictum Thunb. var. mono is the most representative sap-producing species. Acer tataricum also produces sap, and local residents near its natural habitats have traditionally harvested it for consumption. However, only a few studies have investigated the sap of Acer tataricum to date. Previous research has shown that Acer tataricum sap has a higher yield and contains more potassium and sugar than that of Acer pictum var. mono. Recently, Acer tataricum sap was officially recognized as a food ingredient by the Korean Ministry of Food and Drug Safety, highlighting its potential as a new forestry resource. Despite this potential, afforestation strategies for Acer tataricum remain underdeveloped, making its cultivation challenging. Therefore, this study aimed to determine the optimal planting density to support the growth of Acer tataricum. In 2020, a test site was established in Jinju-si, Gyeongsangnam-do, where 2,000 seedlings were planted across a 0.8-hectare area using five different planting methods: fixed spacings of 1.5 m, 2 m, and 4 m; 3-tree cluster planting; and circular radial planting. The largest root collar diameter was observed at the 1.5 m spacing. In the circular radial planting layout—comprising twelve concentric circles of varying diameters—the greatest root collar diameter was recorded among trees planted at 1.2 m ntervals along the 10 m diameter ring. These findings can provide valuable insights for future afforestation efforts involving Acer tataricum.

This study utilizes the Hyper KANAKO program to compare and analyze the effectiveness of permeable and impermeable erosion control dams in mitigating debris flows, considering the unique topographical characteristics of Korea. The aim is to provide fundamental data for selecting and designing the most effective type of erosion control dam under Korean geographical conditions. We quantitatively analyzed the maximum debris flow depth, deposition thickness, and combined cumulative depth before and after the installation of both types of erosion control dams. Through this analysis, we assessed the effectiveness of each erosion control dam type in reducing sediment and flow rate. Repeated experiments using the Hyper KANAKO program, based on actual Korean topography, confirmed that permeable and impermeable erosion control dams exhibit similar performance under specific height conditions. The findings of this study are expected to contribute to optimizing erosion control dam design and disaster prevention efforts in Korea's specific topographical conditions.

In recent years, the spread of pine wilt disease in South Korea has resulted in a steady increase in tree mortality within coniferous forests. To prevent further transmission of the disease, salvage logging operations are being carried out in affected areas. This study evaluated the productivity and costs of a salvage logging system employing a cut-to-length method, in which sawlogs and logging residues are separately collected and treated. The harvested sawlogs were fumigated, while the residues were chipped using a mobile chipper, enabling safe utilization of the timber products without the risk of disease transmission. The sawlog production process consisted of chainsaw felling and processing, woodgrab-based extraction, and minor transporttation operations. Residue collection did not incur additional felling costs due to the free-ride effect, as it was generated as a by-product during sawlog felling. The results showed the unit costs for sawlog felling, processing, and extraction were 2.42 USD/m³, 2.48 USD/m³, and 4.00 USD/m³, respectively. For logging residues, the unit costs for processing, extraction, minor transportation, and chipping were 3.84 USD/GT, 15.44 USD/GT, 7.33 USD/GT, and 8.67 USD/GT, respectively.

For sustainable forest management and the circular use of forest resources, it is essential not only to undertake afforestation and silviculture but also to perform timber-harvesting operations within a safe working environment. In Korea, the number of workers engaged in timber harvesting has been declining and aging, prompting active research into the mechanization of harvesting systems to enhance productivity. In particular, conventional chainsaw-based felling and forwarding operations are gradually being replaced by excavator-based processes. However, excavators operated in rough terrain during felling and forwarding operators to elevated whole-body vibration, which may precipitate musculoskeletal disorders and ultimately degrade work performance. Currently, research investigating operators’ whole‐body vibration exposure during individual task elements of excavator‐based forestry machinery remains scarce. Therefore, in this study we categorize the vibrations experienced by excavator operators during felling and forwarding into discrete sub-tasks and analyze their dynamic characteristics using parameters such as crest factor, maximum vibration amplitude, cumulative vibration exposure, and root-mean-square (RMS) acceleration. Finally, by applying the calculated TWRMS and TVDV values cumulative exposures to the health-guidance risk levels and comfort-response criteria defined in ISO 2631-1, we quantitatively evaluate the whole-body vibration exposure of operators performing excavator-based harvesting and forwarding operations. Excavator-based harvesting and forwarding tasks exhibited TWRMS and TVDV values exceeding ISO 2631-1 health thresholds during 4–8 hours of operation, inducing comfort ratings from “uncomfortable” to “very uncomfortable.” Forwarding showed higher exposure than felling, and attachments alone provided insufficient mitigation. Future research should explore remote-controlled harvesting to reduce operator vibration exposure.