• Journal of Korean Society of Forest Science
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• v.90 no.3
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• pp.388-397
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• 2001

In forestry, where improvement of labor environment is quite impossible, improved posture would result in direct effects by preventing waste of physical strength, prevention of accidental injury caused by fatigue accumulated on certain body parts, and prevention of human error by inattentiveness due to weakened body. Therefore, this research carried on analysis of working posture in manual forest work(thinning using chain-saw, salvage cutting using chain-saw, clearing using hand saw, clearance of twiner using sickle, pruning using saw with a long handle, and tending of young growth using sickle) using OWAS analysis system. According to the OWAS method, percentage of OWAS action categories III and IV in the tasks using chain-saw and sickle was higher than another tasks. For the compared middle skillful worker group and low skillful worker group at felling work using chain-saw, percentage of OWAS action categories IV in middle skillful worker group was 5.1%, and low skillful worker group was 14.1%.

• Korean Journal of Agricultural Science
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• v.42 no.2
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• pp.117-124
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• 2015

In forest work, working conditions are very hard to improve. The good posture is believed to bring about direct improvements such as accident prevention. Therefore, this research carried on analysis of working posture in forest work (construct in stepping-stone) using OWAS analysis system. According to the analytical results provided by OWAS, the ratio of category III (Work posture has a distinctly harmful effect on the musculoskeletal system) has shawn that worker 2 was 32.2%, worker 1 was 25.2% and worker 3 was 15.5%. Furthermore, the ratio of category IV (Work posture with an extremely harmful effect on the musculoskeletal system) has shown that worker 2 was 9.8%, worker 3 was 1.4% and worker 1 was 1.2%. According to the OWAS method, percentage of OWAS action categories III and IV in the worker 2 was higher than another workers.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.168-182
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• 2019

The objectives of this study were to examine the production processes and methods of "Forest Type Map Actualization Production (Database (DB) Construction Work Manual)" (Work Manual) identify issues associated with the production processes and methods, and suggest solutions for them by applying evaluation items to a 1:5k digital forest type map. The evaluation items applied to a forest type map were divided into zoning and attributes, and the issues associated with the production processes and methods of Work Manual were derived through analyzing the characteristics of the stand structure and fragmentation by administrative districts. Korea is divided into five divisions, where one is set as the area changed naturally and the other four areas set as the area changed artificially. The area changed naturally has been updated every five years, and those changed artificially have been updated annually. The fragmentation of South Korea was analyzed in order to examine the consistency of the DB established for each region. The results showed that, in South Korea, the number of patches increased and the mean patch size decreased. As a result, the degree of fragmentation and the complexity of shapes increased. The degree of fragmentation and the complexity of shapes decreased in four regions out of 17 regions (metropolitan cities and provinces). The results indicated that there were spatial variations. The "Forest Classification" defines the minimum area of a zoning as 0.1ha. This study examined the criteria for the minimum area of a zoning by estimating the divided object (polygon unit) in a forest type map. The results of this study revealed that approximately 26% of objects were smaller than the minimum area of a zoning. The results implied that it would be necessary to establish the definition and the regeneration interval of "Areas Changed Artificially and Areas Changed Naturally", and improve the standard for the minimum area of a zoning. Among the attributes of Work Manual, "Species Change" item classifies terrain features into 52 types, and 43 types of them belong to stocking land. This study examined distribution ratios by extracting species information from the forest type map. It was found that each of 23 species, approximately 53% of species, occupied less than 0.1% of Forested land. The top three species were pine and other species. Although undergrowth on unstocked forest land are classified in the terrain feature system, their definition and classification criteria are not established in the "Forest Classification" item. Therefore, it will be needed to reestablish the terrain feature system and set the definitions of undergrowth.

• Korean Journal of Agricultural Science
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• v.38 no.1
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• pp.101-108
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• 2011

In forest work, working conditions are very hard to improve. The proper distribution of work time and good posture is believed to bring about direct improvements such as accident prevention. On this, this study has analyzed forest workers' posture and their working hours in order to improve their working conditions in stone channel work. Authors has chosen several core elements of stone channel work to focus on, which include stone masonry, excavation of bed, moving stone, directing work, choosing stone, and breaking stone. The ratio of real working time over total working time was shown as 84.6%. As for the time ratio of each elemental work over the real working time, the stone masonry was 60.4%, the directing work was 15.1%, moving stone was 12.1%, choosing stone was 7.1%, breaking stone was 3.3%, and excavation of bed was 2.0%. According to the analytical results provided by OWAS, the ratio of category III (Work posture has a distinctly harmful effect on the musculoskeletal system) has shown that moving stone turned out 65.2%, choosing stone was 61.5%, stone masonry was 46.1%, breaking stone was 14.3%, excavation of bed was 12.5% and directing work was 6.8%. Furthermore, the ratio of category IV (Work posture with an extremely harmful effect on the musculoskeletal system) has shown that excavation of bed turned out 37.5%, breaking stone was 28.6%, stone masonry was 27.3%, choosing stone was 7.7%, moving stone was 6.1% and directing working was 4.5%. These results are expected to be utilized for the improvement with respect to both working methods in the stone channel work and the workers' working posture.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.4_2
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• pp.593-601
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• 2020

This study was conducted to analyze the physical strain with heart rate monitor in timber harvesting operations in order to reduce occupational accidents. The timber harvesting activities are manual cutting(felling, limbing and bucking) with a chainsaw and extraction by cable yarder. The study took place on Japanese larch stand. The average height was 26m and average diameter at breast height(DBH) was 3 7cm. The havest unit was gentle slope to steep slope. Results showed that the heart rate increases for chocking, felling, limbing and bucking were 94.0%, 87.9%, 84.8% and 56.4% respectively. The rate of Work Load Index was higher in the limbing(61.4%) activity than other activities chocking(55.2%), felling(54.1%) and bucking(32.1%). During 50% working heart rate test it was found that limbing(1.09), chocking(1.05) and felling(1.04) was exposed to high work intensity compared to bucking(0.83). The results showed that maximum acceptable work times(felling, chocking and limbing) were 2.30 hour, 1.85 hour and 1.60 hour respectively. To avoid occupational accidents, timber harvest workers may use a suitable working hour schedule to felling, chocking, limbing.

• Journal of Forest and Environmental Science
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• v.39 no.4
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• pp.203-212
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• 2023

Directional felling is a felling method practised by the Forestry Department in Peninsular Malaysia as prescribed in Field Work Manual (1997) for Selective Management Systems (SMS) in forest harvesting. Determining the direction of tree felling in Peninsular Malaysia is conducted during the pre-felling inventory 1 to 2 years before the felling operation. This study aimed to predict and analyze the direction of tree felling using the vector-based path distance back link method in Geographic Information Systems (GIS) and compare it with the felling direction observed on the ground. The study area is at Balah Forest Reserve, Kelantan, Peninsular Malaysia. A Path Distance Back Link (spatial analyst) function in ArcGIS Pro 3.0 was used in predicting tree felling direction. Meanwhile, a binary classification was used to compare the felling direction estimated using GIS and the tree felling direction observed on the ground. Results revealed that 61.3% of 31 trees predicted using the vector-based projection method were similar to the felling direction observed on the ground. It is important to note that dynamic changes of natural constraints might occur in the middle of tree felling operation, such as weather problems, wind speed, and unpredicted tree falling direction.

• Journal of Biosystems Engineering
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• v.22 no.3
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• pp.289-294
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• 1997

The chestnut is a well-known and important forest product in Korea. The annual production of chestnut is about 100, 000tons and its cultivating area is 80, 000ha. However, the peeling process of outer and inner skins of chestnut is very difficult due to hardness and adhesiveness of chestnut skin. The peeling process of chestnut was operated by manual work and the performance of chestnut peeling machine is very low. The purpose of this study is to develope the prototype of new chestnut peeling system. The hardness of chestnuts was tested with six different drying conditions and its range was from 949$g/mm^2$ to 2, 149$g/mm^2$. The hardness of chestnuts was decresed gradually during the drying process. The chestnut peeling Process includes sorting, storage, drying, outer skin cutting, flame peeling, continuous frictional skin peeling, and inner skin cutting operation. The developed chestnut peeling system consists of outer skin cutter, flame peeler, continuous frictional skin peeler and inner skin cutter. The system can peel domestic chestnuts at 150$kg/hr$ with peeling rate of 78%.

• Spatial Information Research
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• v.8 no.1
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• pp.1-14
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• 2000

Zoning data such as national land use planning map, urban land use planning map, agricultural promotion zoning ap, forest land zoning map has a relationship each other in law and spatial context. But difficulties in data share and the lack of accuracy of manual work makes serious inconsistence son zoning data relationship. This causes many trial and error in land use. For resolving this problem the data modellingmethod is presented as a technical solution.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.