Search Results (39)

Mountainous regions often experience a hydrological paradox where high monsoon rainfall coincides with severe dry-season water scarcity. The Chittagong Hill Tracts (CHT) of southeastern Bangladesh represent this challenge, as steep terrain, fractured geology, rapid runoff and limited monitoring constrain sustainable water-resource planning. This review critically evaluated water-resource characteristics, modeling approaches and decision-support strategies for the CHT. The literature shows that standalone models such as SWAT, MODFLOW and SWMM are useful for specific water-cycle components but do not adequately represent cross-domain processes including deep recharge, baseflow and stream–aquifer exchange in steep, complex terrain. International analogue studies indicate that coupled surface water–groundwater models can improve process representation when streamflow, groundwater-level, lithological and recharge data are available. However, their direct calibration and validation in the CHT remain limited by sparse groundwater monitoring and weak hydrogeological characterization. CHT-related and comparable Bangladesh studies indicate that machine-learning (ML) models can improve predictive suitability mapping when representative training data and independent validation are available; however, their relative advantage over the Analytic Hierarchy Process (AHP) is application-specific and depends on data quality, validation design, spatial autocorrelation, and model interpretability. The review identifies three key gaps: inadequate groundwater monitoring, absence of calibrated coupled modeling for fractured aquifers, and limited integration of socio-economic factors in rainwater-harvesting feasibility. Finally, a staged modeling pathway is proposed. Full article

As the environmental sustainability of forest management has become an increasingly important consideration, incorporating environmental performance into timber harvesting operations has grown to be correspondingly critical. This shift is reflected in a growing move away from large-scale clear-cutting toward smaller-scale harvesting operations. To conduct such small-scale harvesting efficiently, mechanized systems have increasingly been introduced into practice, yet how these systems affect the soil environment relative to conventional harvesting methods remains insufficiently understood. In the Republic of Korea, where steep, mountainous terrain predominates, this knowledge gap is particularly consequential, as the conventional (chainsaw felling and excavator-based woodgrab extraction) system often produces spatially diffuse and severe surface soil damage. This study compared surface soil disturbances between conventional and small-scale mechanized (SSM) harvesting systems across three slope gradient classes (moderate, <20°; steep, 20–25°; very steep, >25°) at five harvesting units in the Republic of Korea. Disturbance was assessed at total of 2046 systematically distributed grid points using a four-class visual disturbance protocol, with continuous disturbance surfaces derived by inverse distance weighting (IDW) interpolation. The results indicate that SSM systems shift the pattern of disturbance rather than uniformly reducing it. On moderate slopes, SSM (grapple saw felling and clambunk skidding) reduced the proportion of severe, area-wide disturbance but concentrated deep rutting along fixed skid trails, producing significantly deeper ruts than the conventional system. On the steep slope, the SSM system pairing mechanized felling with swing yarder extraction substantially reduced both the extent and the severity of disturbance relative to the conventional system by eliminating in-stand machine travel during extraction. On the very steep slope, no paired conventional unit was available for comparison, but the SSM system using a small tower yarder resulted in a notably low level of surface disturbance. These findings suggest that the soil-protective benefit of SSM systems may depend on how machine traffic is distributed during felling and extraction, offering evidence to guide slope-specific system selection for environmentally sound timber harvesting. Full article

Small harvesting compartments and steep terrain in South Korea favor harvesting systems in which a single machine performs multiple processes. Multifunctional systems based on small tracked excavators, equipped with a grapple saw for felling and a clambunk skidder for extraction, have therefore been increasingly adopted to address labor shortages and to improve operational safety. However, because these base machines lack a chassis suspension system and their operator seats provide limited vibration isolation, operators of small-excavator-based systems may be exposed to elevated levels of whole-body vibration (WBV) and shock vibration. This study quantified operator ride-vibration exposure and assessed the associated health risks during small-excavator-based timber harvesting in accordance with ISO 2631-1; the assessment was based on measured vibration exposure rather than on direct medical evaluation. Tri-axial accelerations were measured simultaneously at the operator seat and the cab floor of a 5-ton-class excavator over eight workdays, and one representative workday was analyzed at the work-element level. The harvesting process was divided into timber felling (machine travel, positioning, clearing, and cutting and bunching) and timber extraction (machine travel on forest roads, machine travel on skid trails, and loading and unloading). Exposure was evaluated using the frequency-weighted root-mean-square (RMS) acceleration, the crest factor (CF), and the total vibration dose value (TVDV). The CF exceeded 9 for all work elements, indicating shock-dominated vibration and justifying the TVDV as the primary evaluation metric. Timber extraction generated higher vibration exposure than timber felling, and the seat TVDV differed significantly among the work elements within each operation (p < 0.001). The highest seat TVDV occurred during loading and unloading (123.05 m/s^1.75), exceeding the upper ISO 2631-1 Health Guidance Caution Zone limit for an 8-h exposure by more than eight times, and all major work elements exceeded the ISO 2631-1 health guidance limits. To our knowledge, this study provides the first work-element-level quantification of WBV exposure for small-excavator-based timber harvesting systems in South Korea. The findings underscore the need for improved seat suspension systems, vibration mitigation technologies, and vibration-aware work planning strategies. Full article

Mechanized timber harvesting on steep slopes causes soil disturbance; however, comprehensive post-harvest assessment remains challenging because terrain complexity and safety constraints render traditional field-based methods labor-intensive, spatially limited, and difficult to implement systematically. In this study, we developed and evaluated a convolutional neural network-based semantic segmentation model for detecting soil disturbances using high-resolution unmanned aerial vehicle (UAV) imagery in a steep-slope harvested area (2.50 ha, mean slope of 53.4%) in Republic of Korea. A U-Net semantic segmentation model was trained on manually annotated orthomosaic tiles incorporating RGB and digital elevation model (DEM) inputs. Ensemble predictions at an optimized threshold of 0.65 achieved Intersection over Union (IoU) of 0.55 and F1-score of 0.71. Although moderate, these values reflect the inherently challenging conditions of steep-slope forest terrain compared to similar studies conducted under gentler terrain. DEM-derived depth estimation enabled severity classification of the detected disturbances, with light disturbances predominating. Field validation using 38 pinboard measurements demonstrated reliable spatial detection (ρ = 0.567, RMSE = 6.45 cm). This approach provides an effective alternative to traditional monitoring practices in mountainous forests, where systematic trail planning is impractical, and may support evidence-based assessment of harvesting impacts for sustainable forest management. Full article

(1) Background: Austria’s use of fully mechanized harvesting systems has been continuously increasing. Technical developments, such as traction aid winches, have made it possible to drive on increasingly steep terrain. However, this has led to challenges and potential hazards for the operators, resulting in higher stand damage rates and risks of workplace accidents. Since these systems and working environments involve a highly complex interplay of various parameters, the purpose of this protocol is to propose a new set of methodologies that can be used to obtain a holistic interpretation of the psychophysiological interrelationship between the working conditions and stress of harvester and forwarder drivers. (2) Methods: We developed a research protocol to analyse the (a) environmental and (b) machine-related parameters; (c) psychological and psychophysiological responses of the operators; and (d) technical outcome parameters. Within this longitudinal exploratory field study, experienced drivers were monitored for over an hour at the beginning and the end of their workday while operating in varying steep terrains with and without a traction aid winch. The analysis is based on macroscopic (collected using cameras), microscopic (eye-tracking glasses and AI-driven emotion recognition), quantitative (standardized questionnaires), and qualitative (interviews) data. This multimodal research protocol aims to improve the health and safety of forest workers, increase their productivity, and reduce damage to remaining trees. Full article

Soybean–corn intercropping in the hilly–mountainous regions of Southwest China poses unique challenges to mechanized harvesting because of complex topography and agronomic constraints. Addressing the soybean-harvesting bottleneck in these fields requires advanced sensing and perception rather than purely mechanical redesigns. Prior reviews emphasized flat-terrain machinery or single-crop systems, leaving a gap in sensor-centric solutions for intercropping on steep, irregular plots. This review analyzes how sensors enable the next generation of intelligent harvesters by linking field constraints to perception and control. We frame the core failures of conventional machines—instability, inconsistent cutting, and low efficiency—as perception problems driven by low pod height, severe slope effects, and header–row mismatches. From this perspective, we highlight five fronts: (1) terrain-profiling sensors integrated with adaptive headers; (2) IMUs and inclination sensors for chassis stability and traction on slopes; (3) multi-sensor fusion of LiDAR and machine vision with AI for crop identification, navigation, and obstacle avoidance; (4) vision and spectral sensing for selective harvesting and impurity pre-sorting; and (5) acoustic/vibration sensing for low-damage, high-efficiency threshing and cleaning. We conclude that compact, intelligent machinery powered by sensing, data fusion, and real-time control is essential, while acknowledging technological and socio-economic barriers to deployment. This review outlines a sensor-driven roadmap for sustainable, efficient soybean harvesting in challenging terrains. Full article

Forest harvesting can alter sedimentary processes in catchments by reducing vegetation cover and exposing the soil surface. To mitigate these effects, post-harvest residue management is commonly used, though its effectiveness needs individual evaluation. This study assessed how windrowed harvest residues influence structural sediment connectivity in two forest catchments in south-central Chile with a Mediterranean climate. Using digital terrain models and the Index of Connectivity, scenarios with and without windrows were compared. Despite similar windrow characteristics, effectiveness varied between catchments. In catchment N01 (12.6 ha, average slope 0.28 m m⁻¹), with 13.6% windrow coverage, connectivity remained unchanged, but in contrast, catchment N02 (14 ha, average slope 0.27 m m⁻¹), with 21.9% coverage, showed a significant connectivity reduction. A key factor was windrows’ orientation: 83.9% aligned with contour lines in N02 versus 58.6% in N01. Distance to drainage channels also played a role, with the decreasing effect of connectivity at 50–60 m in N02. Bootstrap analysis confirmed significant differences between catchments. These results suggest that windrow configuration, particularly contour alignment, may be more critical than coverage percentage. For effective connectivity reduction, especially on moderate to steep slopes, forest managers should prioritize contour-aligned windrows. This study enhances our understanding of structural sediment connectivity and offers practical insights for sustainable post-harvest forest management. Full article

The goal of this study was to develop a GIS-based Decision Support Model for selecting the best timber harvesting systems on steep terrain. The model combines multiple layers, each representing an important factor in mechanized logging. These layers are used to create a final map that functions as a spatially explicit Decision Support Model that helps decide which machines are best suited for different forest areas. A key idea of this study is to consider not only operational criteria (slope, ruggedness, wetness, and road accessibility), but also a fundamental silvicultural aspect, i.e., the assessment of tree growth classes to enable the integration of silvicultural deliberations into timber harvest planning. The data used for this model come from orthophoto image and a Digital Terrain Model (DTM). The operational factors were analyzed using GIS tools, while the silvicultural aspects were assessed using the deep learning algorithm DeepForest and tree growth equations (allometric functions). The model was tested by comparing its results with field data taken in a Norway Spruce stand in South Tyrol/Italy. The findings show that the model reliably evaluates operational factors. For silvicultural aspects, it tends to underestimate the number of small trees, but provides a good representation of tree size classes within a forest stand. The innovation of this method is that it relies on low-cost, open-source tools instead of expensive 3D scanning devices. Full article

Winch-assisted harvesting has expanded considerably in recent years as it enables ground-based machines to work safely on steep slopes. To analyze operator exposure to whole-body and hand–arm vibration (WBV, HAV) and noise exposure (LA_eq, LC_peak) during winch-assisted harvesting (TW) and harvesting without winch assistance (NTW), a field study using a Ponsse Scorpion King harvester and an Ecoforst T-winch traction winch was conducted. Vibrations were measured at three locations inside the cabin (seat, seat base/floor, control lever), while noise exposure was recorded both inside and outside the cabin. WBV exposure during work time operations was highest in the Y-direction, both on the seat (0.49–0.87 m/s²) and on the floor (0.41–0.84 m/s²). The WBV and HAV exposure levels were highest while driving on the forest and skid road. Exposure during the main productive time was significantly influenced by the harvesting system, diameter at breast height (DBH), and tree species. Noise exposure was higher, while WBV and HAV exposures on the seat, floor and control lever were lower during non-work time than during work time. The daily vibration exposure on the seat exceeded the EU action value, while LC_peak noise exposure surpassed the limit value of 140 dB(C) on all measured days. Noise and vibration exposure were constantly higher during TW than NTW harvesting but differences were small. Compared to other studies, the results show that harvesting on steep terrain increases noise and vibration exposure, while non-work time has the opposite effect on vibration and noise exposure. Full article

Most forest harvesting operations are performed using two or more forestry machines in combination; in the typical forest production system in steep terrain in Japan, there are four production processes: felling, yarding, processing, and forwarding. It is essential to evaluate the overall productivity of such combined production systems, but the calculation method that indicates the productivity has not been fully established. In this study, we built simulation models of serial, parallel, and sequential production systems by using system dynamics to evaluate their productivity regarding the combined machine productivity (CMP) and combined labor productivity (CLP) indices. Comparing the three types of forest harvesting systems in Japan, the parallel production system had the highest CMP, while the serial production system had the highest CLP; the sequential production system lay between the serial and parallel production systems in terms of CMP and CLP. The overall productivity of Japanese forest production systems was lower than that of Central Europe, where processor tower yarders (PTYs) are used. Thus, the CLP of Japanese forest production systems was improved by 12.8 to 26.5% by incorporating the concept of a PTY, and it can be further improved by eliminating the forwarding process. Full article

Machine traffic during timber harvesting operations induces soil compaction, which is particularly evident in the formation of ruts. Visual inspection of rut formation is labor-intensive and limits the volume of data that can be collected. This study aims to contribute to the limited knowledge base regarding the extent of soil physical disturbance caused by machine traffic on steep slopes and to evaluate the utility of LiDAR and UAV photogrammetry techniques. The selected traffic trails included single-pass uphill, single-pass downhill, three-pass round trip, and five-pass round trip trails, with an average slope of 70.7%. Traditional methods were employed to measure rut depth using a pin board and to assess soil bulk density (BD) and soil porosity (SP) from soil samples. The results revealed that the average rut depth was 19.3 cm, while the deepest ruts were observed after a single pass (uphill: 20.0 cm; downhill: 22.7 cm), where BD and SP showed the most significant changes. This study provides a rare quantitative evaluation of the applicability of remote sensing methods in forestry by comparing surface height data collected via a pin board with that derived from a Mobile LiDAR System (MLS) and UAV photogrammetry using structure-from-motion (SfM). When compared to pin board measurements, the MLS data showed an R² value of 0.74 and an RMSE of 4.25 cm, whereas the SfM data had an R² value of 0.62 and an RMSE of 5.27 cm. For rut depth estimation, SfM (16.0 cm) significantly underestimated values compared to the pin board (19.3 cm) and MLS (19.9 cm). These findings not only highlight the potential and limitations of remote sensing methods for assessing soil disturbance in steep forest environments but also contribute to addressing the knowledge gaps surrounding the effects of soil compaction in steep terrain. Full article

To address the challenges of digging deep-rhizome Chinese herbal medicines in northwest China’s hilly terrain, including difficulty, incompleteness, and herb damage, a specialized self-propelled digger with interlocking teeth has been developed. Designed for complex topography, small fields, and resistant soil, this digger provides an efficient and precise alternative to traditional methods. The prototype features in-place reverse differential steering, 360-degree digging capability, and minimized root and soil damage to promote future planting. Key components, including the digging mechanism, vibratory system, crawler chassis, hydraulic transmission system, and worm gear rotary hydraulic reducer, were analyzed and optimized through theoretical, graphical, and simulation studies using RecurDyn. Field tests demonstrated the digger’s effectiveness, achieving depths exceeding 600 mm with minimal herb damage and loss. The digger successfully navigated steep slopes and operated within noise regulations, surpassing industry standards, with less than 1.4% herb damage and a loss rate under 3%. The digger was capable of ascending gradients over 20° with driver noise levels below 92 dB. This innovative solution offers a valuable reference for developing specialized diggers for harvesting traditional Chinese medicinal materials in challenging conditions. Full article

Ensuring the safety of forestry workers is a key challenge, particularly when working with partly mechanized harvesting systems. Cable yarding is typically used in steep terrain timber harvesting. For long-distance extraction, one of the few alternatives is to use sledge yarders, but these machines may expose workers to high doses of noise. The goal of this study was to model haulers’ exposure to noise in sledge-based cable yarding operations, based on a simulation approach that considered variable factors such as the yarding distance, lateral yarding distance, and average skyline height. Taken into consideration were 165 scenarios developed by examining the variation in yarding distance (500 to 1500 m, with a step of 100 m), lateral yarding distance (10 to 50 m, with a step of 10 m), and average skyline height above the ground (10, 15, and 20 m). The simulations assumed an 8-h working day with a break of 1 h. The models and statistics published by other studies were used to calculate the time consumption and number of work cycles completed within a working day. These data were used to compute the equivalent exposure to noise (LAeq) for each scenario, as well as for those work elements that were likely to expose the haulers to noise the most. The presented findings indicated that (i) the exposure to noise was higher than 100 dB(A), irrespective of variation in the considered factors; (ii) the trend in exposure was characterized by polynomials in relation to the extraction distance, and the magnitude of exposure was consistently affected by variation in the considered factors; and (iii) without hearing protection, the empty and loaded turns exposed workers to noise over the permissible limits. These findings strongly suggest the use of hearing protection when working in close proximity to sledge-based cable yarding operations. The methods proposed in this study in the form of simulation may help benchmark other forest operations. Full article

Expanding markets for renewable energy feedstocks have increased demand for woody biomass. Concerns associated with forest biomass harvesting include increased erosion, the applicability of conventional forestry Best Management Practices (BMPs) for protecting water quality, and reduced woody debris retention for soil nutrients and cover. We regionally compared the data and results from three prior independent studies that estimated erosion, BMP implementation, and residual woody debris following biomass and conventional forest harvests in the Mountains, Piedmont, and Coastal Plain of Virginia. Estimated erosion was higher in the Mountains due to steep slopes and operational challenges. Mountain skid trails were particularly concerning, comprising only 8.47% of the total area but from 37.9 to 81.1% of the total site-wide estimated erosion. BMP implementation varied by region and harvest type, with biomass sites having better implementation than conventional sites, and conventional Mountain sites having lower implementation than other regions. Sufficient woody debris remained for BMPs on both harvest types in all regions, with conventional Mountain sites retaining twice that of Coastal Plain sites. BMPs reduced the estimated erosion on both site types suggesting increased implementation could reduce potential erosion in problematic areas. Therefore, proper BMP implementation should be ensured, particularly in Mountainous terrain, regardless of harvest type. Full article

Despite similarly steep terrain, the productivity of forest harvesting operations in Japan is lower than in Central Europe. Harvesting systems in Japan are typically characterized by the four production processes of felling, yarding, processing, and forwarding, whereas in Central Europe they have mostly been reduced to just two through the use of a PTY (Processor Tower Yarder). This study investigated the number of production processes as a reason for the relatively lower productivity of forest harvesting in Japan using the Combined Machine Productivity (CMP) and Combined Labor Productivity (CLP) indices. The CMP and CLP were 1.81 m³/h and 0.45 m³/worker/h, respectively, for a parallel production model based on a typical Japanese forest harvesting system in Japan. The CMP and CLP values were improved to 2.51 m³/h and 0.63 m³/worker/h, respectively, when the forwarding process was removed from the model. The CMP and CLP values were further improved to 3.04 m³/h and 0.76 m³/worker/h, respectively, when yarding and processing were integrated into a single process. Reducing the number of the production processes can therefore improve the productivity of forest harvesting operations in Japan. Full article