Earticle

In this study, we propose a deep learning-based forest road recognition technology and integrate it into an autonomous steering and speed control system for a forestry forwarder. We trained a YOLOv8 segmentation model on 640×480 pixel images collected from straight, curved, and occluded sections of forestry roads, achieving a precision of 0.997, a recall of 0.994, an F1 score of 0.995, and an average precision of 0.994. We developed a centerline extraction algorithm that calculates the lateral offset between the vehicle center and the detected road centerline using the segmented mask. This offset is then input into an electronic steering lever control system, which replaces the existing mechanical steering lever to enable rapid response. In field experiments conducted on actual forest roads, the maximum average path tracking error was 0.534 m over three trials, confirming that the vision-based approach can reliably guide the forwarder under various lighting conditions, shadows, and roadside structures. This method is expected to overcome the limitations of GNSS/INS-based autonomous driving systems, as it operates solely with cameras and single-board hardware. The research results suggest that deep learning-based image processing provides a solid foundation for fully autonomous forestry operations and has the potential to improve the productivity and safety of timber transport operations.

The process of sustainable forest planning and management requires accurate and reliable information. Hence, forest inventory plays an important role in this process although it is complex, costly and time consuming. With recent advanced technology, many sophisticated devices and tools have been developed for measuring stand characteristics in field inventory. In particular, mobile devices (i.e., smartphone and tablet), becoming the most popular and rapidly developing computing devices in last decades, have been integrated into forest inventory with the mobile applications. These mobile inventory applications have embedded remote sensing technology such as photogrammetry and Lidar and have been used as an alternative to traditional measurement methods. This study aims to evaluate the effectiveness of the Arboreal Forest and Trestima mobile apps after compared to traditional field measurements methods in burned forested areas. The study focuses on assessing the stand characteristics, including, diameter-at-breast height (dbh), height, density and volume, which are key variables that are assessed in forest inventories. Different burned degrees of the trees (severe and low) were used to evaluate the performance of the methods. We employed the goodness-of-fit statistics (R2, RMSE, and Error) for the comparison of the two apps and traditional method and performed an analysis of the diameter and distribution and comparison of the mean diameter, number of trees per hectare, volume and basal area. In this study, the two apps were used to measure stand parameters after the forest fire, which will help accurate and fast post-fire harvest planning. The results indicated that the use of the mobile apps time effective and provided accurate and reliable solutions in the measurement of stand parameters after the fire.

The intensifying conflict in Myanmar has led to increasing displacement into Thailand, placing greater pressure on forest resources along the border. Community forests, although part of Thailand’s national reserve system, are managed by local communities and play a crucial role in conservation. This study aimed to evaluate the application of Internet of Things (IoT) technology for forest monitoring in four community forests and one national reserve forest in Mae Hong Son Province, along the Thailand-Myanmar border. Three Spartan 4G camera traps were installed at each site to capture images and videos of moving objects, with real-time data transmission to a server and mobile application. Data were collected continuously over three months and analyzed using descriptive statistics. The cameras achieved a 100% operational rate, and 35% of the 5,168 images captured showed detectable objects. Salawin National Reserved Forest recorded the highest number of human detections (1,002 events) and weapon sightings (53 cases), compared to Pratoomuang Community Forest (354 human detections, 50 weapon sightings). Non-timber forest product (NTFP) collection activities, such as harvesting bamboo and vegetables, were detected 79 times in Salawin and 35 times in Thungpam Community Forest. Agricultural equipment, including spades and brush cutters, was rarely detected. A negative relationship between weapon detections and wildlife presence was observed, with larger forests like Salawin more heavily accessed than smaller, village-managed community forests. The findings demonstrate that IoT-based camera traps are effective for real-time monitoring and can enhance forest protection strategies in conflict-affected border regions.

Due to the increasing impact of climate change, the global prevalence of forest disturbances such as forest insect pests and wildfires has led to a growing volume of damaged trees. In response, the necessity of salvage logging has been highlighted as a means to recover the economic value of affected timber resources. However, the inherently hazardous nature of salvage logging stemming from unstable terrain, particulate matter, and smoke exposure poses significant safety risks to field operators. To mitigate these risks and enhance operational safety, ongoing research has focused on the teleoperation of forestry machinery. In particular, establishing a wireless communication system capable of providing reliable coverage over extensive forested areas has been identified as a critical factor influencing the effectiveness of teleoperation. Accordingly, this study developed a Wi-Fi system with a helikite and evaluated its performance by measuring the Received Signal Strength Indicator (RSSI). Based on the empirical data, a remote salvage logging operation plan was formulated and implemented in a real-world environment to assess the system's practical applicability. The findings suggest that this approach offers a viable technological solution for improving worker safety during salvage logging operations. Further research will investigate optimized deployment techniques to ensure stable system operation under diverse environmental conditions.

This study acquired the forest GIS for private and communal forests from prefectures and national forests from the Forestry Agency of Japan. Then, this study calculated incomes and expenditures such as silvicultural and harvesting as well as stumpage prices on the Japanese cedar, cypress, pine, and larch forests using the silvicultural prescriptions set based on the regional forest plans and operation systems set based on topographic conditions such as slope angles and height differences with GIS. Finally, this study estimated the availability of unused materials for woody biomass power generation plants under operation with FIT at the end of June 2020 as the supply potential from the profitable subcompartments. As a result, supply potentials of timber and forest biomass were estimated at 65,490,336 m3/year and 13,098,067 m3/year, respectively whereas those availabilities were estimated at 31,080,672 m3/year and 6,216,134 m3/year respectively. Therefore, the rate of the availabilities to the supply potentials was 47.5%. Furthermore, the rate of the availabilities to the current demands was 71.6%. Considering aggregation in the same watershed, the rate of the availabilities to the demands increased to 124.8%. Thus, the availabilities met the current demands in Japan as a whole.

Previous studies surmised that under-canopy dead branches in unmanaged/abandoned coniferous plantations could reduce throughfall kinetic energy (TKE); however, the effect of under-canopy dead branch pruning on TKE has not been clarified. We established two plots under the same stand density (2500 stems ha⁻¹) in abandoned Japanese cypress plantations: (1) one with dead branch pruning (plot 1, P1) and (2) the other with no dead branch pruning (plot 2, P2). Throughfall (TF) and TKE were measured on the weekly basis during the growing season using manual-type TF rain gauges and sand-filled splash cups, respectively. Results showed that other than dead branch structures, no other stand structures significantly differed between P1 and P2 (p < 0.05). Both stand-scale TF ratio (72.8% vs. 63.5%) and unit TKE (21.4 J m⁻² mm⁻¹ vs. 13.5 J m⁻² mm⁻¹) were higher in P1 than in P2. This implies that dead branches under the canopy had considerable impacts on raindrop fall velocity after passing through upper canopies in unmanaged/abandoned Japanese cypress plantations. Our findings clarified that under-canopy dead branches can mitigate soil erosion risk in such plantations and can provide new insights into forest management for soil conservation.

Forest areas in Türkiye are 23.4 million hectares, covering approximately 29.8% of the country's total area. Approximately 94.72% of the forests are operated as high forests and 5.28% as coppice forests. The wood-based forest products constitute the main source of economic gain from the forestry sector. In recent years, the use of advanced mechanized harvesting equipment in industrial forests has increased in order to meet the high volume wood raw material demands of companies producing wood-based panels. Therefore, harvesting equipment such as skidder, feller-buncher and harvester are used more widely. In mountainous regions, cable yarders have been effectively used by utilizing cable yarders (MOZ 300, 500GR), recently purchased by General Directorate of Forestry from Tajfun company. In recent years, certified training programs have been organized for jobs done during forest harvesting. Personnel with certification are provided with the opportunity to specialize in the profession, thus increasing production quality and labor efficiency in forest harvesting. This paper aimed to describe the current conditions in forest harvesting operations and present new approaches and strategies in forest harvesting operations in Türkiye. Besides, some suggestions have been provided to improve the proportion of using mechanization in forest operations while considering environmental, economic, social constraints.

Since the dawn of modern forestry, optimization of forest operations has been at the forefront of maintaining profitable organizations. One of, if not the most expensive aspect of a boreal softwood operation is road construction which has a direct relationship with the ability to extract timber efficiently. Matthews (1942) expressed that extraction distance and road spacing optimization could be enhanced by mathematical equations; however, experience and a knowledge of the land is not replaceable. The experience Matthews (1942) referred to can undoubtably be associated with the countless variables that any given parcel of land can contribute to reducing the accuracy of “armchair, slide ruler” management. This study was conducted in the Jellicoe area of the Nipigon Forest in Ontario, Canada. Two cut blocks were each divided into four separate distance compartments. The first compartment, 0-300 meters being the assumed optimal extraction area from the landing, with three consecutive compartments of 100-meter increases that follow (301-400 meters, 401-500 meters, and 501- 600 meters). Timber extraction productivity (m3 PMH-1) variables (volume extracted, area, and PMH) were recorded to observe variation between distance compartments and within the associated production metrics. The hypothesis that spruce-pine-fir timber extracted by grapple skidder in a mostly dry site with minimal slope in a northwestern Ontario boreal forest will maintain a comparable level of productivity up to 400 meters could not be rejected as no statistical difference was found between the 0-300 and 301-400 compartments.

This study aimed to determine whether forest road concrete structures deteriorate after exposure to forest fires. Field experiments using non-destructive rebound hardness tests and laboratory experiments using compressive strength tests on fire-damaged concrete specimens were conducted. The field study targeted concrete structures located along forest roads in areas affected by large forest fires from 2020 to 2023 in Republic of Korea. Concrete strength was compared between fire-affected and unaffected structures based on both satellite imagery classification and field survey classification. The results showed no significant difference in concrete strength when classified by satellite imagery. However, when classified by field survey, fire-affected structures exhibited a decrease in compressive strength compared to unaffected structures. Additionally, laboratory tests confirmed that concrete strength significantly deteriorates after 30–40 minutes of heat exposure. These findings suggest that forest fires can weaken concrete structures on forest roads, emphasizing the need for post-fire inspections and the establishment of safety standards for fire control roads.

This study was conducted to compare the intensity of forest fire damage based on the distance from the center of forest roads in five regions where forest roads were established within areas affected by forest fires in 2023. The Difference Normalized Burn Ratio (dNBR) was utilized to quantify the intensity of forest fire damage. The results showed that the intensity of forest fire damage increased with distance from the center of the forest road, and a statistically significant difference was observed in the average dNBR values when compared to the overall fireaffected area (p<0.001). Additionally, differences were also found in the classification of burn severity levels. Regarding burn severity classifications, the proportions of ‘Unburned’ and ‘Low severity’ areas decreased as the distance from the forest road center increased, while the proportions of ‘Moderate high severity’ and ‘High severity’ areas increased. Overall, the intensity of forest fire damage in the periphery of forest roads was lower compared to the broader fire-affected regions, as indicated by average dNBR values and burn severity levels. However, a direct causal relationship between the presence of forest roads and the reduction in forest fire damage intensity in their periphery was not established. Further investigations, including satellite imagery analysis and on-site verification, are deemed necessary to better elucidate the distribution and intensity of forest fire damage in these areas.

Although mechanical harvesting equipment used in forestry operations increases productivity, it also causes significant physical impacts on the soil. Among the most prominent of these effects are road deformations and wheel rut depths caused by tractors and similar vehicles. Such deformations can disrupt the physical structure of the soil, increase the risk of erosion, and damage forest ecosystems. In this study, wheel rut depths formed during ground-based skidding operations were comparatively analyzed using both manual measurement techniques and imagery obtained via Unmanned Aerial Vehicles (UAVs). The fieldwork was conducted during forestry production activities in the Dağtekke Forest Management Chief. Manual measurements were performed using a ruler and lath along skidding trails, and the same areas were captured using UAVs and converted into digital surface models. The results obtained from both methods were compared using correlation analysis and paired sample t-tests. The findings revealed a high level of consistency between UAV-based and manual measurements, indicating that UAV technology offers a fast, contactless, and reliable alternative for monitoring. This study provides valuable insights into precision soil monitoring and assessing the environmental impacts of mechanical equipment in forestry operations.

Wildfires enhance soil water repellency by combusting surface organic matter, thereby altering soil hydrological properties. This study aimed to analyse runoff and infiltration characteristics according to the degree of soil water repellency through the rainfall simulation experiments in the wildfire-affected area. Soil water repellency was assessed using the Molarity of Ethanol Droplet (MED) method. Rainfall simulations were performed on 21 plots, and total runoff, time-specific runoff (0–10 min, 10–20 min, and 20–30 min), and infiltration were compared based on the presence or absence of soil water repellency. Rainfall experiment was conducted for 20-minute with a rainfall intensity of 80 mm·hr−1, distinguishing the 20–30 min interval as the post-rainfall runoff period. The results showed that soils exhibiting water repellency resulted in a higher total runoff, approximately 46% greater, compared to non-repellent soils. Infiltration displayed a negative correlation with water repellency severity, with higher infiltration observed in non-repellent soils. Time-specific runoff analysis revealed that repellent soils consistently exhibited significantly greater runoff across all intervals, with approximately 32% higher runoff in the 0–10 min interval, 27% higher in the 10–20 min interval, and a markedly 157% increase during the 20–30 min post-rainfall interval. These findings suggest that the influence of soil water repellency on runoff persists even after rainfall cessation.

In steep mountainous areas, debris flows can entrain large boulders with various diameters. The boulder enriched flow front imparts highly collisional stresses on the soil bed during the flow. Although, they possess highly erosive potentials, all the eroded particles are not feasibly transported to downstream. The erosion and transport capacity of granular flows are influenced by its composition of grains. Since, it has not been explicitly accounted in the continuum models, the total volume of bed transport tends to be overestimated. Therefore, it is essential to characterize the mechanisms of frictional or collisional bed yielding, transport, and surface morphology, while incorporating erosion into mobility prediction tools for hazard assessment and designing protective structures based on flow characteristics. In this study, small-scale flume experiments were performed for granular flows having a wide range of particle variations between 25mm-60mm at different slope angles of 25o-30o. After the experiment, the surface morphology evolution due to the granular flows were also assessed by scanning the surface using the hand-held laser scanner. The results infer that, increasing the grain size leads to a reduction in transported mass, while increasing the flume angle enhance the mass transportation to the downstream. The surface scanning results show that erosion zones are more widely distributed at higher angles, in contrast to the more discrete distribution observed at shallower angles.

Rainfall is a major external factor contributing to landslides. The development of a wetting front due to rainfall increases the self-weight of the soil mass and reduces the negative pore water pressure, ultimately leading to a decrease in shear strength along the slope. Therefore, accurately estimating the depth and amount of infiltration associated with rainfall is crucial for predicting landslides. Although numerous studies have been conducted to predict the movement of the wetting front and the corresponding changes in soil water content during rainfall infiltration, many of these studies assume vertical piston flow, which leads to discrepancies from actual field behavior. In reality, a transition zone exists within the wetting front, and infiltration progresses in an unsaturated state without complete saturation. In this study, it was confirmed that the transition zone within the wetting front follows a Sigmoid-shaped profile. Based on this observation, a rainfall infiltration model was developed that incorporates both unsaturated conditions and the transitional behavior of the wetting front. The proposed model was applied to infinite slope analysis under unsaturated conditions, and its results were compared with those from conventional theoretical approaches. As a result, the proposed model demonstrated improved accuracy in predicting the wetting front and effectively captured the unsaturated and transitional characteristics of the infiltration process. Furthermore, compared to existing models, the safety factor of slopes was found to be relatively higher, with a gradual variation in safety factor observed due to the influence of the transition zone.

The increasing concentration of population in major metropolitan areas has led to population decline and a rise in underutilized land in surrounding cities. This demographic shift has resulted in a proliferation of vacant urban spaces, especially in shrinking cities, where a lack of management perpetuates pollution and exacerbates ecological degradation. To address these environmental challenges, this project aimed to restore the ecological functions of abandoned urban spaces through strategic design interventions. Overlay analyses of terrain, soil, and drainage were conducted to identify optimal intervention sites. Based on these analyses, a master plan was developed that integrates six types of wetland-based blue infrastructure: natural wetlands, vegetated swales, infiltration basins, plant islands, paddy field wetlands, and bio slopes. Pollution reduction for each model was quantified. Geodesign was used to systematically identify pollution sources and to design optimized solutions for maximum purification and storage efficiency. Application of the proposed model to the Han River catchment resulted in a 16-fold increase in stormwater retention during monsoons and a 4-fold increase during droughts. Pollution loads were reduced by 11% for BOD, 10% for total nitrogen, and 18% for total phosphorus. These results demonstrate that the proposed model effectively enhances ecological resilience and water quality management, while reducing unnecessary financial and time costs.

This study presents a case analysis of the effects of a large-scale wildfire (3100 hectares) on aboveground biomass and soil erosion using remote sensing data and the Google Earth Engine (GEE) platform. The wildfire, which occurred on August 13, 2024, in the Yamanlar region of İzmir, Türkiye, also impacted residential areas. The entire study was conducted using openly accessible datasets within the GEE environment. In the initial phase, the burned area boundary and burn severity were delineated using Sentinel-2 satellite imagery. Pre-fire aboveground biomass was modelled using the Global Ecosystem Dynamics Investigation (GEDI) LiDAR Aboveground Biomass Density (AGBD) data, incorporating 14 different parameters through the Random Forest regression method. Subsequently, fire-induced biomass loss was quantified based on burn severity classifications. Additionally, soil loss before and after the wildfire was assessed using the Revised Universal Soil Loss Equation (RUSLE) to evaluate the impact of the fire on erosion. The results demonstrate the effectiveness of GEE-based analysis in rapidly and efficiently assessing the effects of large-scale wildfires on soil and vegetation. This study highlights the potential of remote sensing and cloud-based geospatial analysis in post-fire environmental assessments, providing valuable insights into fire-induced biomass loss and erosion dynamics. The findings contribute to the development of improved wildfire management and mitigation strategies.

A smart thinning operation uses advanced technologies and methods for implementation of efficient and precise logging activities. It consists of forest resource survey and spatial inventory construction using LiDAR, optimal selection of trees to be removed using machine learning techniques, and felling operations based on a real-time positioning system. In felling activities for a smart thinning operation, a chainsaw operator can accurately locate trees to be felled using a positioning system without any flagging on trees. This study evaluated the field applicability of a GNSS-RTK system (R12i, Trimble) for a felling operation in a 1-ha area of Pinus and Larix thinning stands. A comparative field simulation was conducted between smart and traditional felling operations, each repeated twice, to assess the accuracy of tree localization and operational times. The results showed that the accuracy of navigating trees to be felled of the smart felling operation was satisfactory in both pine and larix stands, averaging 80.3% and 97.0%, respectively. The operational time for the smart felling operation in pine and larix stands showed 47.6 sec/tree and 49.9 sec/tree, respectively, which represents 5.2 times and 3.0 times higher each compared to the traditional chainsaw felling operation. In smart felling operation, the operational time decreased by an average of 20.3% in the second phase compared to the first phase of the simulation, indicating the operational time can be improved through enhancing the operators’ proficiency of the GNSS-RTK equipment.

One of the areas most at risk of forest fires in Turkey is the Mediterranean region. Although the reasons for fire outbreaks change over the years, they result in the loss of forest assets in the area due to fire. Fires also cause major ecological damage. Forest fires reduce or eliminate many forms of vegetation from the land surface. The Kavaklıdere-Muğla-Yatağan-Yılanlı fire, which occurred between 2 and 8 August 2021, damaged a large area. Therefore, the study aims to investigate the land use and land cover (LULC) changes in 2020, 2021 and 2024 in Kavaklıdere district, Muğla. In this study, six LULC classes, agriculture (A), bare + other (BO), forest (F), urban (U), water (W) and burned areas (BA), were obtained using Sentinel-2 satellite imagery with the random forest classification technique on the Google Earth Engine (GEE) platform. In addition, land surface temperature (LST) data were obtained using the splitwindow algorithm on Landsat-8 data. The results show that LULC changes are clearly in fireaffected areas and that LST values are particularly high in burned areas compared to other classes. The results demonstrate the effectiveness of remote sensing techniques in monitoring changes in land cover and surface temperature following fire.

Due to high ergonomic risks, forestry considered a high-priority issue in forest workers' health. Timber production workers usually work in open environments, where harsh conditions such as rough terrain and extreme weather. Lack of experience, improper equipment and other related factors can negatively impact occupational health and safety (OHS). In this study, work posture analysis was performed by using computer vision technique. Real-time joint angles were calculated using a MediaPipe-supported system based on machine learning (ML) technique. Real-time joint angle data extracted from video frames were used to compute Rapid Entire Body Assessment (REBA) scores instantly. Besides the entire body analysis, each limb could be assessed separately. The initial user impressions regarding the system were assessed. This method enables the collection of detailed data, which can regularly accumulate into a largescale dataset appropriate for big data applications. CV-based work posture analysis is promising technique as a method open to development as an adaptive system. The risk of biased evaluations in expert observations during body posture analysis can be minimized.

Remote sensing and satellite images are important tools for monitoring land cover changes. The MODIS Land Cover product (MCD12Q1) which follows 17 International Geosphere- Biosphere Programme (IGBP) global land cover classifications, is widely used for global-scale land cover monitoring. Its accessibility makes it a practical choice for stakeholders, as it allows easier data processing compared to other complex machine learning techniques that require extensive training and expertise. However, its coarse resolution and classification system do not capture some ecological details and struggles to distinguish small and diverse land cover types, especially wetlands, particularly at a regional or sub-national scale. To address this limitation, we integrated MCD12Q1 data with very high-resolution (VHR) imagery from Google Earth to uncover certain categories within the IGBP permanent wetlands in Myanmar for the year 2018. By using widely and publicly accessible optical satellite data from MODIS and Google Earth, along with minimal GIS and computational expertise, we ensure that our approach remains practical for regional applications. We analyzed 250 random sample points taken from the 500- meter MCD12Q1 raster polygons for the permanent wetland category, reclassified these points by following standard guidelines from various references and visually verified them using VHR Google Earth imagery and finally applied the calibration approach to estimate the actual area of each land cover type found within the IGBP permanent wetlands in Myanmar. Our findings reveal that the majority of areas classified as IGBP permanent wetlands were actually mangroves (54.8%), while others include aquaculture farms (16.4%), mangroves and croplands (4.8%), reservoirs (15.2%), river/lake (4.8%), mudflats (2%) and peatlands (2.4%).

This study aims to estimate annual soil loss and map the spatial distribution of potential erosion risk in the Narlıdere watershed, located in the Kestel district of Bursa province, using a remote sensing and Geographic Information Systems (GIS)-based Revised Universal Soil Loss Equation (RUSLE) model. The model integrates five factors: precipitation erosivity (R), soil erodibility (K), topography (LS), vegetation cover (C), and support practices (P), analyzed through numerical data within a GIS environment. Based on 21 years of precipitation data (2000–2021) from the Kestel station, the average annual rainfall was calculated as 716.8 mm. The R factor ranged between 671.75 and 1014.89 MJ mm ha⁻¹ h⁻¹ year⁻¹. The K factor varied between 0.014 for Calcic Cambisols (BK) and 0.022 for Eutric Cambisols (BE). LS values ranged from 0 to 726.75, the C factor between 0 and 0.07, while the P factor was set at 1 due to the absence of soil conservation practices. Findings indicate that erosion risk in the watershed has increased over time, with its spatial extent expanding. Unregulated agricultural activities, which degrade natural vegetation, emerged as a key factor accelerating soil loss. The severity of erosion was particularly pronounced in steep and vegetation-free areas. These results highlight the urgent need to implement soil conservation measures in erosion-prone zones. Expanding erosion control interventions in the Narlıdere Watershed is crucial for promoting the sustainable management of soil and water resources.

This study assesses the spatiotemporal dynamics of land cover changes in the Upper Bago River Basin, Myanmar, from 1988 to 2025. Using supervised classification of Landsat imagery in Google Earth Engine (GEE), we categorized land cover into six classes: dense vegetation, sparse vegetation, agriculture, water, built-up areas, and bare land. Our preliminary findings show a significant decline in dense vegetation, from 1,831.09 km² in 1988 to 1,084.58 km² by 2025, indicating a 41% reduction over the study period. Sparse vegetation increased, particularly between 1995 and 2005, suggesting shifts in land use patterns. Agricultural land expanded slightly, with notable increases in built-up areas, particularly in urbanized regions. A slight decrease in overall vegetation cover, from 2,407.03 km² in 1988 to 2,250.06 km² in 2025, further highlights the ongoing transformation of the landscape, driven by both natural and anthropogenic factors. These results underscore the growing pressure on forest cover and the need for integrated land use planning to mitigate potential impacts on watershed hydrology and biodiversity in the region. The study provides critical insights for future land use modelling and policy development in Myanmar.

In recent years, smartphones with LiDAR sensors have begun to be used as an economical, fast and effective alternative for tree diameter measurement. In this study, the capabilities of a LiDAR-enabled smartphone were tested in measuring tree diameters of Stone pine (Pinus pinea) and Cypress trees (Cupressus sempervirens) located in Bursa Technical University campus in Bursa, Türkiye. iForester, a user-friendly and AI-assisted application, was used for breast height diameter (DBH) of sample trees. In the study, the performance of the smartphone application was evaluated with the classical measurement method carried out using a caliper. The accuracy of the LiDAR-enabled smartphone application was investigated based on Mean Square Error (MSE) and Root Mean Square Error (RMSE) methods. The results showed that the smartphone method provided good accuracy for both tree species. MSE values for Stone pine and Cypress were determined as 3.89 and 0.99, respectively, when using DBH measurement mode. RMSE values of the species were determined as 1.97 and 0.99, respectively. When the tree species were compared, the tree diameter was determined with higher accuracy in the sample area with cypress trees, due to relatively more cylindrical and smooth stem formation.

Today, most forest harvesting operations are carried out with modern forestry machines, and their efficiency depends not only on the performance of each forestry machine, but also on how they are used in combination and on various site characteristics. In Japan, forest harvesting is usually carried out using several forestry machines in combination, and the most typical forest harvesting system in steep terrain has four production systems: felling, yarding, processing, and forwarding using a chainsaw, swing yarder, processor, and forwarder, respectively. In this study, the system productivity of this forest harvesting system was evaluated in the combined machine productivity (CMP) and combined labor productivity (CLP) indices by using system dynamics simulation, focusing on the variation of system productivity when the speed of each production process is changed. As a result, it was found that the speeds of the yarding and forwarding processes, which depend on the extraction distance, are the potential bottlenecks of the Japanese forest harvesting systems. The system productivity of Japanese forest harvesting systems in steep terrain can be improved by replacing swing yarders with more powerful tower yarders and by increasing the travel speed or maximum load of forwarders.

This study aimed to investigate the short-term effects of chainsaw lubricating oils—biodegradable, mineral-based, and recycled—on forest soil contamination and vegetation growth, with the goal of providing scientific evidence to guide lubricant selection for timber harvesting operations. Two experiments were conducted: Experiment 1 assessed the growth of Larix kaempferi (Lamb.) Carrière seedlings under artificially induced contamination at a nursery site, while Experiment 2 examined total petroleum hydrocarbon (TPH) dynamics, soil bacterial community structure and function, and sprout growth of Quercus mongolica Fisch. ex Ledeb. stumps under operational contamination at a harvesting site. Biodegradable oil treatments exhibited lower TPH concentrations and faster recovery compared to mineral-based and recycled oils. Soil bacterial functional profiles remained more similar to the control under biodegradable oil, whereas mineral-based and recycled oils induced partial functional shifts. Soil CO₂ efflux decreased by 1.1%, 11.5%, and 7.7% under biodegradable, mineral-based, and recycled oils, respectively, although differences were not statistically significant. Soil CH₄ uptake increased across all oil treatments, indicating potential microbial resilience. Despite detectable biochemical and microbial alterations in soils, no statistically significant effects were observed on the growth of seedlings or sprouts. These findings suggest that chainsaw lubricant application may exert subtle effects on microbial and certain functional aspects of soil properties, but its short-term impacts on soil productivity appear to be limited depending on species.

This study aims to quantify the proportion of forest area accessible for cable yarding without being obstructed by ridges or other terrain features, relative to the total area theoretically accessible in planar terms. The analysis assumes a lateral yarding distance of 20 meters and a maximum span length of 500 meters, without the use of intermediate supports. All potential cable lines were simulated from points along existing roads. For each simulated line, the area of forest within the lateral yarding distance was calculated. Separately, the total forest area within the maximum span from roads was calculated without accounting for topographic obstructions. The ratio of the area accessible via unobstructed cable yarding to the total theoretically accessible area was then computed. As a case study, an analysis was conducted for a 1,670- hectare basin in Morotsuka Village, located in the southwestern part of Japan. In this area, 1,563 hectares were located within the maximum span from roads, and 1,316 hectares were accessible via cable yarding. This ratio serves as a quantitative measure of the feasibility of cable yarding in mountainous terrain and can be used as a basic indicator for the effective deployment of tower yarders in forest operations planning.

Improving forestry operational efficiency is a critical issue for sustainable forest management. In Taiwan, the cessation of natural forest harvesting since 1990 and the subsequent stagnation of plantation management have led to significant challenges. With the government declaring 2017 as the "First Year of Domestic Timber" to align with the 2050 carbon neutrality goal, revitalizing the forestry sector has become urgent. However, the current domestic timber usage rate remains below 1%. This study investigates the operational efficiency of harvesting activities in Taiwan, using a combination of field surveys, literature reviews, and GIS analysis. Factors such as road network conditions, slope, and tree diameter were analyzed to evaluate harvesting efficiency. The study highlights infrastructural, technological, and workforce challenges and provides recommendations based on successful practices in Japan. These findings suggest that with appropriate investment and system reform, Taiwan can significantly enhance its forestry productivity.

Steep and difficult terrain presents persistent operational, safety, and environmental challenges for forest harvesting. This presentation outlines recent innovations in forest operations that aim to improve efficiency, safety, and sustainability under such conditions. Historically reliant on manual labor and conventional ground-based equipment, steep slope forestry is undergoing rapid transformation driven by technological advancement and international best practices. Key developments include the emergence and adoption of winch-assist systems—mechanized equipment supported by tensioned cables that improve traction and stability on inclines. First adopted in Europe and New Zealand, these systems are now increasingly used in North America. Their benefits include expanded use of mechanized felling and extraction on slopes previously limited to manual operations, reduced soil disturbance, and enhanced operator safety. Cable yarding systems remain vital, especially in coastal and mountainous regions. Ongoing improvements in grapple yarders and integration with winch-assist systems support more flexible and efficient operations. Future opportunities lie in automation, in-forest connectivity, and autonomous machinery, which offer the potential to revolutionize forest logistics and wildfire mitigation. This presentation also discusses the broader system-level considerations such as road infrastructure, equipment compatibility, workforce training, and regulatory factors. Insights are drawn from applied research and industry experience across North America and international contexts. Through these innovations, the forest sector is better positioned to operate on steep terrain while minimizing environmental impact and improving safety and productivity across the value chain.

Particulate matter (PM) consists of solid particles suspended in the air, which can have significant health effects depending on their sizes. Particles smaller than 10 microns (PM10 and PM2.5) can penetrate deep into the respiratory tract and reach the lungs, causing serious health risks. In this study, the PM2.5 exposure levels of operators working with cabinless tractors commonly used in forestry were evaluated. In field studies conducted in the Osmangazi Forest Management Chief, measurements were taken on a New Holland TT55B model tractor using two different devices. The average PM2.5 concentration measured with an industrial device (PCE-PCO-2 Particle Meter) was 206.22 μg/m³, while the value recorded with the TriSensor 4.0 multi-measurement device (Arduino based) was 188.94 μg/m³. Similarly, in the Dağtekke Forest Management Chief area, PM2.5 measurements were conducted on a Türk-FIAT 80-66 model tractor. The average PM2.5 concentration was found to be 114.98 μg/m³ with the industrial device and 165.35 μg/m³ with the TriSensor 4.0 device. These results indicate that operators working with cabinless tractors are exposed to high levels of particulate matter, which poses a serious occupational health risk. The study emphasizes the need for preventive measures to improve occupational health and safety in forestry operations.