• Journal of Korean Society of Forest Science
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• v.86 no.3
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• pp.365-377
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• 1997

Much of the Cumberland Plateau of Tennessee, USA is in mixed hardwoods for which there are no applicable growth and yield predictors. Use of site index as a variable in growth and yield prediction models is limited in most stands because their history is not known and many may not be even-aged. Landtypes may offer an alternative to site index for these mixed stands because they were designed to include land of about equal productivity. To determine vegetation by landtype, dependency between landtype and detailed forest type was tested with Chi-square. Differences in productivity among landtypes were tested by employing regression analyses and analysis of variance(ANOVA). Basal area growth was fitted to the nonlinear models developed by Moser and Hall(1969). Basal area growth and volume growth were also predicted as a function of initial total basal area and initial volume with linear regression by landtype and by landtype class. Differences in basal area growth and volume growth by landtype were tested with ANOVA. Dependency between site class and landtype was tested with Chi-square. Vegetation types seem to be related to landtypes in the study area although the validity of the test is questionable because of a high proportion of sparsely occupied cells. No statistically significant differences in productivity among landtypes were found in this study.

• Korean Journal of Environment and Ecology
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• v.16 no.3
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• pp.223-232
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• 2002

For the zoning of natural ecosystem, Vegetation Index is calculated from the vegetation data surveyed on Baekdudaegan (Pijae-Doraegijae). Five factors -biodiversity, conservation value of the stand, environmental quality, longevity of the stand, site productivity- are considered in the calculation of Vegetation Index. Vegetation Index might be a useful zoning tool for management of Baekdudaegan. For Vegetation Index I, 59 sample plots 52.2% of total 113 sample plots are belong to core area, 34 sample plots 30.l% and 20 sample plots 17.7% are belong to buffer zone and transition area, respectively. For Vegetation Index II, 49 sample plots 43.4% of total 113 sample plots are belong to core area, 38 sample plots 33.6% and 26 sample plots 23.0％ are belong to buffer zone and transition area, respectively.

• Journal of Korean Society of Forest Science
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• v.98 no.6
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• pp.646-651
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• 2009

In this study, it was intended to prepare a stem volume table (with or without bark) and a stand yield table for Juglans mandshurica, plantations in Chungju, located in Chungcheongbuk-do, Korea. For the calculation of stem volume, we applied Kozak's growth model, which showed the best fitness index (97%). With this model, it was able to prepare the first yield table for Juglans mandshurica in Korea. Site index model, an indicator of forest productivity, was derived by using the Chapman-Richard model, in which the basic stand age was set to 30 years. The resulted site index ranged between 16 and 22. Based on the yield table of Juglans mandshurica resulted from this study, the volume for a 70-year-old stand with a midium site index class was estimated to be $238m^3/ha$, which is $100m^3/ha$ higher than the volume estimated from the yield table of Quercus acutissima. The yield table of oak trees has been used in the estimation of most broadleaf stands in Korea. However, the result of this study indicated that it is necessary to generate a stand yield table for each broadleaf species. The annual $CO_2$ removals of 30-year-old Juglans mandshurica plantations in the ChungJu region was estimated to be $5.84tCO_2/ha$. The stem volume and stand yield table of Juglans mandshurica plantation resulted from this study would provide a good information in decision making for forest management in ChungJu region.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.484-491
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• 2015

The productivity of Manila clam(Ruditapes philippinarum) aquaculture farm is closely related to suitable site selection, so it is essential to assess the habitat suitable for aquaculture species in order to manage yield. This study evaluated the habitat suitable index(HSI) with 9 sites for tidal flat farm, Gochang(Hajun) on May 2014. The suitability index was selected Growth(hydrodynamics, chlorophyll a), Survival(sediment-sand, silt-clay) and Water Environment(dissolved oxygen, salinity). Both Weight and No weight were tried for objective judgment as HSI scoring method. As a result, it shows lower tidal flat(HSI; No weight: 0.60~0.76, Weight: 0.47~0.70) is higher than upper(HSI; No weight: 0.25~0.27, Weight: 0.09~0.10), hydrodynamics and sediment particle size are the most effective. This research can consider the potential suitable site for Manila clam through scientific approach, and provide the basis for optimal management practices in tidal flat farm.

• Journal of The Korean Society of Grassland and Forage Science
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• v.40 no.4
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• pp.196-202
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• 2020

Rye, whole-crop barley and Italian Ryegrass are major winter forage species in Korea, and yield monitoring of winter forage species is important to improve forage productivity by precision management of forage. Forage monitoring using Unmanned Aerial Vehicle (UAV) has offered cost effective and real-time applications for site-specific data collection. To monitor forage crop by multispectral camera with UAV, we tested four types of vegetation index (Normalized Difference Vegetation Index; NDVI, Green Normalized Difference Vegetation Index; GNDVI, Normalized Green Red Difference Index; NGRDI and Normalized Difference Red Edge Index; NDREI). Field measurements were conducted on paddy field at Naju City, Jeollanam-do, Korea between February to April 2019. Aerial photos were obtained by an UAV system and NDVI, GNDVI, NGRDI and NDREI were calculated from aerial photos. About rye, whole-crop barley and Italian Ryegrass, regression analysis showed that the correlation coefficients between dry matter and NDVI were 0.91~0.92, GNDVI were 0.92~0.94, NGRDI were 0.71~0.85 and NDREI were 0.84~0.91. Therefore, GNDVI were the best effective vegetation index to predict dry matter of rye, wholecrop barley and Italian Ryegrass by UAV system.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.97-108
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• 2024

This research delves into the escalating concerns of accidents and fatalities in the construction industry over the recent five-year period, focusing on the development of a Safety Perception Model to augment safety measures. Given the rising percentage of elderly workers and the concurrent drop in productivity within the sector, there is a pronounced need for leveraging Fourth Industrial Revolution technologies to bolster safety protocols. The study comprises an in-depth analysis of statistical data regarding construction-related fatalities, aiming to shed light on prevailing safety challenges. Central to this investigation is the formulation of a Safety Perception Model tailored for small-scale construction projects. This model facilitates the quantification of safety risks by evaluating safety grades across construction sites. Utilizing the DWM1000 module, among an array of wireless communication technologies, the model enables the real-time tracking of worker locations and the assessment of safety levels on-site. Furthermore, the deployment of a safety management system allows for the evaluation of risk levels associated with individual workers. Aggregating these data points, the Safety Climate Index(SCLI) is calculated to depict the daily, weekly, and monthly safety climate of the site, thereby offering insights into the effectiveness of implemented safety measures and identifying areas for continuous improvement. This study is anticipated to significantly contribute to the systematic enhancement of safety and the prevention of accidents on construction sites, fostering an environment of improved productivity and strengthened safety culture through the application of the Safety Perception Model.

• Journal of Construction Engineering and Project Management
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• v.5 no.2
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• pp.16-23
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• 2015

In this paper, a survey related to excavation construction activities among national and international construction companies was conducted to evaluate site productivity in construction industry. To analyze the respective productivity levels of each construction company, a benchmarking measures analysis that featured calculations of the performance ratio (PR) and performance management index (PMI) was performed. As a result of these analyses, it has been found that the work performed by local companies was marked by lower productivity and that of international companies was characterized by good productivity. Further analysis of construction workforce resources P% revealed that a construction company's productivity is largely dependent on production capacity and consumption resources, which means that the retention of skilled workers and utilization of high-quality resources yields the highest level of productivity. These results suggest that for a local construction company to be competitive in the construction work market, it must retrain skilled craftspeople, foremen, engineers, and project managers, and strengthen its building capability by leveraging new equipment and technologies.

• Journal of The Korean Society of Grassland and Forage Science
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• v.35 no.3
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• pp.225-231
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• 2015

Improving current pasture productivity by precision management requires practical tools to collect site specific pasture biomass data. Recent developments in unmanned aerial vehicle (UAV) technology provide cost effective and real time applications for site specific data collection. For the mapping of herbage biomass (BM) on a hill pasture, we tested a UAV system with digital cameras (visible and near-infrared (NIR) camera). The field measurements were conducted on the grazing hill pasture at Hanwoo Improvement Office, Seosan City, Chungcheongnam-do Province, Korea on May 17 and June 27, 2014. Plant samples were obtained from 28 sites. A UAV system was used to obtain aerial photos from a height of approximately 50 m (approximately 30 cm spatial resolution). Normalized digital number (DN) values of Red and NIR channels were extracted from the aerial photos and a normalized differential vegetation index using DN ($NDVI_{dn}$) was calculated. The results show that the correlation coefficient between BM and $NDVI_{dn}$ was 0.88. For the precision management of hilly grazing pastures, UAV monitoring systems can be a quick and cost effective tool to obtain site-specific herbage BM data.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.89-97
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• 2022

Recently, various problems such as reduced productivity, insufficient inflow of skilled manpower, reduced quality, and concerns about increasing safety accidents have appeared in the domestic construction industry. Stakeholder of construction project are considering the Off-Site Construction (OSC) method rather than the conventional on-site construction as an alternative. Despite the importance of decision making in the early stage of the adoption of OSC, there is a lack of methodologies for rational decision making. In this study, a decision making system has been developed to derive the final construction cost score by deriving the project characteristics, selecting the construction difficulty index, and developing a cost model for each construction method alternatives to calculate the standard construction cost. Using this system, the OSC method can be effectively evaluated in terms of its feasibility in the early stage of construction

• Korean Journal of Environment and Ecology
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• v.18 no.2
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• pp.158-166
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• 2004

For the zoning of natural ecosystem, Vegetation Index is calculated from the vegetation data surveyed on Baekdudaegan (from Namdeogyusan to Sosagogae). Five factors-biodiversity, conservation value of the stand, environmental quality, longevity of the stand, site productivity- are considered in the calculation of Vegetation Index. Vegetation Index might be a useful zoning tool for management of Baekdudaegan. For Vegetation Index I, 8 sample plots 12.l％ of total 66 sample plots are belong to core area, 21 sample plots 31.8％ and 37 sample plots 56.l％ are belong to buffer zone and transition area, respectively. For Vegetation Index II, 37 sample plots 41.9% of total 60 sample plots are belong to core area, 19 sample plots 28.8％ and 19 sample plots 28.8% are belong to buffer zone and transition area, respectively.