• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.341-354
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• 2021

A large part of Gapyeong is occupied by Korean pine (Pinus koraiensis) and Japanese larch (Larix kaempferi) plantations. Abies holophylla stands are scattered throughout Gapyeong, but little information on their distribution is available. This study explored the potential of succession from planted species to native A. holophylla in plantations. Trees were inventoried and regeneration of A. holoplhylla and stand management history were examined in Korean pine, Japanese larch, and A. holophylla-dominated stands. The importance percentage of A. holophylla was the highest among species with a range of 36.1% to 79.1% in all stands and the density of A. holophylla in understory (DBH <2 cm or <1.3 m height) ranged from 50 to 5,820 trees ha^-1. Non-metric multidimensional scaling classified stands into four types, AN, AP, AM, and P. The AN type showed a reverse J-shape DBH distribution, which was similar to that in natural A. holophylla stands. Both AP and AM types included Korean pine plantations with A. holophylla seed trees within stands. For AP, A. holophylla competed with planted species in overstory and deciduous broadleaved species in understory. The AM type was once thinned from below, thus stem density in the mid DBH classes was lower than upper or lower DBH classes. The P type consisted of plantations without A. holophylla seed trees. However, understory regeneration of A. holophylla was abundant through seed supply from A. holophylla in adjacent stands. Plantations with A. holophylla seed trees within or in adjacent stands showed vigorous natural regeneration of A. holophylla, highlighting the potential for succession from planted species to native A. holophylla in the Gapyeong area. Further studies can help develop techniques to restore plantations to native species-dominated natural stands using ecological succession.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1329-1340
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• 2021

The intertidal zone, which is a transitional zone between the ocean and the land, requires continuous monitoring as various changes occur rapidly due to artificial activity and natural disturbance. Monitoring of coastal topography changes using remote sensing method is evaluated to be effective in overcoming the limitations of intertidal zone accessibility and observing long-term topographic changes in intertidal zone. Most of the existing coastal topographic monitoring studies using remote sensing were conducted through high spatial resolution images such as Landsat and Sentinel. This study extracted the waterline using the NDWI from the GOCI-II (Geostationary Ocean Color Satellite-II) data, identified the changes in the intertidal area in Gyeonggi Bay according to various tidal heights, and examined the utility of DEM generation and topography altitude change observation over a short period of time. GOCI-II (249 scenes), Sentinel-2A/B (39 scenes), Landsat 8 OLI (7 scenes) images were obtained around Gyeonggi Bay from October 8, 2020 to August 16, 2021. If generating intertidal area DEM, Sentinel and Landsat images required at least 3 months to 1 year of data collection, but the GOCI-II satellite was able to generate intertidal area DEM in Gyeonggi Bay using only one day of data according to tidal heights, and the topography altitude was also observed through exposure frequency. When observing coastal topography changes using the GOCI-II satellite, it would be a good idea to detect topography changes early through a short cycle and to accurately interpolate and utilize insufficient spatial resolutions using multi-remote sensing data of high resolution. Based on the above results, it is expected that it will be possible to quickly provide information necessary for the latest topographic map and coastal management of the Korean Peninsula by expanding the research area and developing technologies that can be automatically analyzed and detected.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.959-974
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• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.51-60
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• 2021

Modern society is becoming more informed and intelligent with the development of digital technology, in which humans, objects, and networks relate with each other. In accordance with the changing times, a garden system has emerged that makes it easy to supply the ideal temperature, humidity, sunlight, and moisture conditions to grow plants. Therefore, this study attempted to grasp the concept, perception, and trends of smart gardens, a recent concept. To achieve the purpose of this study, previous studies and text mining were used, and the results are as follows. First, the core characteristics of smart gardens are new gardens in which IoT technology and gardening techniques are fused in indoor and outdoor spaces due to technological developments and changes in people's lifestyles. As technology advances and the importance of the environment increases, smart gardens are becoming a reality due to the need for living spaces where humans and nature can co-exist. With the advent of smart gardens, it will be possible to contribute to gardens' vitalization to deal with changes in garden-related industries and people's lifestyles. Second, in current research related to smart gardens and users' experiences, the technical aspects of smart gardens are the most interesting. People value smart garden functions and technical aspects that enable a safe, comfortable, and convenient life, and subjective uses are emerging depending on individual tastes and the comfort with digital devices. Third, looking at the usage behavior of smart gardens, they are mainly used in indoor spaces, with edible plants are being grown. Due to the growing importance of the environment and concerns about climate change and a possible food crisis, the tendency is to prefer the cultivation of plants related to food, but the expansion of garden functions can satisfying users' needs with various technologies that allow for the growing of flowers. In addition, as users feel the shapes of smart gardens are new and sophisticated, it can be seen that design is an essential factor that helps to satisfy users. Currently, smart gardens are developing in terms of technology. However, the main components of the smart garden are the combination of humans, nature, and technology rather than focusing on growing plants conveniently by simply connecting potted plants and smart devices. It strengthens connectivity with various city services and smart homes. Smart gardens interact with the landscape of the architect's ideas rather than reproducing nature through science and technology. Therefore, it is necessary to have a design that considers the functions of the garden and the needs of users. In addition, by providing citizens indoor and urban parks and public facilities, it is possible to share the functions of communication and gardening among generations targeting those who do not enjoy 'smart' services due to age and bridge the digital device and information gap. Smart gardens have potential as a new landscaping space.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1143-1154
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• 2021

The selection of activation function has a great influence on the groundwater level prediction performance of artificial neural network (ANN) model. In this study, five activation functions were applied to ANN model for two groundwater level observation wells in the middle mountainous area of the Pyoseon watershed in Jeju Island. The results of the prediction of the groundwater level were compared and analyzed, and the optimal activation function was derived. In addition, the results of LSTM model, which is a widely used recurrent neural network model, were compared and analyzed with the results of the ANN models with each activation function. As a result, ELU and Leaky ReLU functions were derived as the optimal activation functions for the prediction of the groundwater level for observation well with relatively large fluctuations in groundwater level and for observation well with relatively small fluctuations, respectively. On the other hand, sigmoid function had the lowest predictive performance among the five activation functions for training period, and produced inappropriate results in peak and lowest groundwater level prediction. The ANN-ELU and ANN-Leaky ReLU models showed groundwater level prediction performance comparable to that of the LSTM model, and thus had sufficient potential for application. The methods and results of this study can be usefully used in other studies.

• Journal of the Korean earth science society
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• v.42 no.3
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• pp.247-263
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• 2021

Climate change has been accelerating in coastal waters recently; therefore, the importance of coastal environmental monitoring is also increasing. Chlorophyll-a concentration, an important marine variable, in the surface layer of the global ocean has been retrieved for decades through various ocean color satellites and utilized in various research fields. However, the commonly used chlorophyll-a concentration algorithm is only suitable for application in clear water and cannot be applied to turbid waters because significant errors are caused by differences in their distinct components and optical properties. In addition, designing a standard algorithm for coastal waters is difficult because of differences in various optical characteristics depending on the coastal area. To overcome this problem, various algorithms have been developed and used considering the components and the variations in the optical properties of coastal waters with high turbidity. Chlorophyll-a concentration retrieval algorithms can be categorized into empirical algorithms, semi-analytic algorithms, and machine learning algorithms. These algorithms mainly use the blue-green band ratio based on the reflective spectrum of sea water as the basic form. In constrast, algorithms developed for turbid water utilizes the green-red band ratio, the red-near-infrared band ratio, and the inherent optical properties to compensate for the effect of dissolved organisms and suspended sediments in coastal area. Reliable retrieval of satellite chlorophyll-a concentration from turbid waters is essential for monitoring the coastal environment and understanding changes in the marine ecosystem. Therefore, this study summarizes the pre-existing algorithms that have been utilized for monitoring turbid Case 2 water and presents the problems associated with the mornitoring and study of seas around the Korean Peninsula. We also summarize the prospective for future ocean color satellites, which can yield more accurate and diverse results regarding the ecological environment with the development of multi-spectral and hyperspectral sensors.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.245-256
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• 2021

This study was conducted to identify the applicability of a LiDAR sensor to forest resources inventories by comparing data on a tree's position, height, and DBH obtained by the sensor with those by existing forest inventory methods, for the tree species of Criptomeria japonica in Jeolmul forest in Jeju, South Korea. To this end, a backpack personal LiDAR (Greenvalley International, Model D50) was employed. To facilitate the process of the data collection, patterns of collecting the data by the sensor were divided into seven ones, considering the density of sample plots and the work efficiency. Then, the accuracy of estimating the variables of each tree was assessed. The amount of time spent on acquiring and processing the data by each method was compared to evaluate the efficiency. The findings showed that the rate of detecting standing trees by the LiDAR was 100%. Also, the high statistical accuracy was observed in both Pattern 5 (DBH: RMSE 1.07 cm, Bias -0.79 cm, Height: RMSE 0.95 m, Bias -3.2 m), and Pattern 7 (DBH: RMSE 1.18 cm, Bias -0.82 cm, Height: RMSE 1.13 m, Bias -2.62 m), compared to the results drawn in the typical inventory manner. Concerning the time issue, 115 to 135 minutes per 1ha were taken to process the data by utilizing the LiDAR, while 375 to 1,115 spent in the existing way, proving the higher efficiency of the device. It can thus be concluded that using a backpack personal LiDAR helps increase efficiency in conducting a forest resources inventory in an planted coniferous forest with understory vegetation, implying a need for further research in a variety of forests.

• The Korean Journal of Blood Transfusion
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• v.29 no.3
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• pp.301-309
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• 2018

Background: If donors who were deferred due to the reactivity or grey zone in HBV surface antigen (HBsAg) assay want to donate blood again, they need to pass reentry tests. On the other hand, approximately half of the donors who are subject to the reentry tests cannot be reentered. This study examined the association between the sample to cutoff (S/Co) value of the HBsAg assay and the final results of the reentry test. Methods: This study analyzed the S/Co values of the HBsAg assay and the final results of the reentry tests for the 3,947 donors from January 2008 to December 2017 using the database of Blood Information Management System of the Korean Red Cross. Results: 1,767 donors (44.8%) were not reentered among 3,947 deferred donors. Among 1,585 donors showing ${\geq}10$ of the S/Co value in the HBsAg screening test, 1,542 donors (97.3%) were not reentered. The additional reentry tests were performed on 120 donors who were not reentered in the first reentry test; 98 donors (81.7%) were still not reentered. Overall, 4.6% of the donors showing a grey zone in the HBsAg assay were not reentered. Conclusion: The reentry test needs to be restricted for the deferred donors showing a more than 10 S/Co value. The application of the grey zone of current HBsAg assay will need to be continued to enhance the HBV-related blood safety.

• Journal of vocational education research
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• v.36 no.1
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• pp.77-103
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• 2017

The purposes of this study are 1) to analyse the importance and performance of the success factors in steps of Formation process Of Cooperation NetWork(FoCNW) of educational institutions and businesses, and 2) to draw the success factors that need improvement. To achieve these purposes a survey research was conducted with a group of 1,098 (professors, teachers and workers in charge of cooperation at universities, technical colleges, vocational high schools and businesses which are equipped with a cooperation system), and 339 questionnaires were analyzed. The major results of the study are as follows. Firstly, while cooperation workers showed high recognition on the importance of success factors in steps of FoCNW, their performance of those factors was relatively low. Secondly, both the recognition of importance and performance of success factors in steps of FoCNW was higher in educational institutions than in businesses. Thirdly, the success factors in need of improvements from both educational institutions and businesses are 'collecting outer information and consulting' and 'publicizing cooperation competency', 'setting cooperative activities (programs) and contents of agreements', 'managing cooperation quality formally', 'drawing plans for sustainable cooperation improvement' and 'diffusing cooperation network'. The success factors in need of improvements from educational institutions are 'perceiving necessity of and forming consensus on cooperation' and 'deciding and supporting the worker in charge of cooperation', and 'participating and sharing of organization members'. The success factors in need of improvements from businesses are 'deciding goals and performance strategies', 'developing mutual understanding and checking possibility of cooperation with potential partners', and 'evaluating cooperation activities and their outcomes and providing feedback' and 'adjusting contents of agreements and deciding whether to maintain cooperation'. Therefore, efforts from each partner to improve those factors and support from related organizations are necessary.

• Korean Journal of Breeding Science
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• v.43 no.5
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• pp.430-441
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• 2011

Maize is divided into two types based on the starch composition of the endosperm in the seed, normal maize(or non-waxy maize) and waxy maize. In this study, genetic diversity and population structure were investigated among 80 waxy maize and normal inbred lines(40 waxy maize inbred lines and 40 normal maize inbred lines) using 50 SSR markers. A total of 242 alleles were identified at all the loci with an average of 4.84 and a range between 2 and 9 alleles per locus. The gene diversity values varied from 0.420 to 0.854 with an average of 0.654. The PIC values varied from 0.332 to 0.838 with an average of 0.602. To evaluate the population structure, STRUCTURE 2.2 program was employed to confirm genetic structure. The 80 waxy and normal maize inbred lines were separated with based on the membership probability threshold 0.8, and divided into groups I, II and admixed group. The 13 waxy maize inbred lines were assigned to group I. The 45 maize inbred lines including 7 waxy maize inbred lines and 38 normal maize inbred lines were assigned to group II. The 22 maize inbred lines with 20 waxy maize inbred lines and 2 normal maize inbred lines were contained in the admixed group. The cluster tree generated using the described SSR markers recognized three major groups at 31.7% genetic similarity. Group I included 40 waxy maize inbred lines and 11 normal maize inbred lines, and Group II included 27 normal maize inbred lines. Group III consist of only 2 normal maize inbred lines. The present study has demonstrated the utility of SSR analysis for the study of genetic diversity and the population structure among waxy and normal maize inbred lines. The information obtained from the present studies would be very useful for designing efficient maize breeding programs in Maize Experiment Station, Kangwon Agricultural Research and Extension Services.