Park, Kwang-Lai;Kang, Bang-Hun;Choi, Jae-Woong;Kim, Chang-Hwan
Korean Journal of Soil Science and Fertilizer
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v.43
no.6
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pp.1040-1046
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2010
This research is composed of a series of survey of existing plants species by classifying biotope type of agro-ecosystem of Guksoo village area of Yangpyeong County, to collect and analyze basic data of vegetation analysis for indicators development of agro-ecosystem habitat quality. From the observation area, we found total 141 kinds of tracheophytes (53 Family 114 Genus 124 Species 16 Variety 1 Breed) and they are 3.36% of total Korean tracheophytes (4,191 kinds). Among those 141 tracheophytes, there are 23 kinds of naturalized plants (11 Family 20 Genus 20 Species 2 Variety) and they are 8.61% of total Korean naturalized plants (267 kinds). Among those 141 tracheophytes, they include 0.71% of pteridophyte, 0.71% of gymnosperm, 98.58% of angiosperm. So, most of them are angiosperm. When we classify them according to plant life form characteristics, dormant/diapause type plants include 45 species (31.91%) of annual plant (Th), 19 species (13.48%) of Th (w), 17species (12.06%) of hemicryptophyte (H). Regarding propagation type, as for the Radicoid form, there are 99 species (70.21%) of crumb structure plant, 13 species (9.22%) of $R_4$, 12 species (8.51%) of $R_{2.3}$ are the crumb structure does not make any connection on the ground or under ground. As for the Disseminule form of propagation type, there are 62 species (43.97%) of Gravity dispersal type $D_4$), 23 species (16.31%) of Wind dispersal type ($D_1$), 21 species (14.89%) of $D_{1.4}$. According to this survey of plant distribution rate by plant life form characteristics, we may acquire many knowledge about species composition of sociability, cluster's reaction against environmental elements, space usage and possible species competition in community. It may be very useful basic data for habitat preservation to keep and promote biological diversity.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.16
no.4
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pp.195-209
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2021
According to the 2019-2020 social media usage survey conducted by the Seoul e-commerce center, 5 out of 10 consumers have experienced shopping through social media. The cost of traditional advertising media has been reduced and advertising spending on social media has risen by 74%, indicating that social media is becoming a more important marketing element. While the number of users of social media has increased and corporate marketing activities have increased accordingly, research has been conducted in various aspects of marketing such as user motivation for social media, satisfaction, and purchase intention. There was no subdivided study on the differences in the social media usage frequency of consumers in actual purchasing behavior. This study attempted to identify differences in consumer characteristics by cluster in the agrifood purchase situation by grouping them by type according to the frequency of use of social media for consumers who purchase agri-food online. Product involvement, product need, and online purchase channel Consumer characteristics such as demographic distribution, perceived risk, and eating and lifestyle in each cluster were checked for the three agrifood purchase situations including choice, and types for each cluster were presented. To this end, questionnaire data on the frequency of social media use and online agrifood purchase behavior were collected from 245 consumers, and the validity of the measurement variables was secured through factor analysis and reliability analysis. As a result of cluster analysis according to the frequency of social media use, it was divided into three clusters. The first cluster was a group that mainly used open social media, and the second cluster was a group that used both open and closed social media and online shopping malls; The third cluster was a group with low online media usage overall, and the characteristics of each cluster appeared. Through regression analysis, the effect on product involvement, product need, and purchase channel selection when purchasing agri-food online through each of the three clusters was confirmed through regression analysis. As a result of the regression analysis, the characteristic of cluster 1 in the situation of purchasing agri-food online is a male in his 30s living in a rural area who has no reluctance to purchase agri-food on social media or online shopping malls. The characteristics of cluster 2 are mainly consumers who are interested in purchasing health food, and the consumer characteristics are represented. In the case of cluster 3, when purchasing products online, they purchase after considering quality and price a lot, and the consumer characteristics are represented as people who are more confident in purchasing offline than online. Through this study, it is judged that by identifying the differences in consumer characteristics that appear in the agri-food purchase situation according to the frequency of social media use, it can be helpful in strategic judgments in marketing practice on social media customer targeting and customer segmentation.
Park, Jueon;Kim, Taeheon;Lee, Changhui;Han, Youkyung
Korean Journal of Remote Sensing
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v.37
no.5_1
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pp.1135-1147
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2021
In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.
Sung, Taejun;Kim, Young Jun;Choi, Hyunyoung;Im, Jungho
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.
As part of the next-generation Compact Advanced Satellite 500 (CAS500) project, CAS500-4 is scheduled to be launched in 2025 focusing on the remote sensing of agriculture and forestry. To obtain quantitative information on vegetation from satellite images, it is necessary to acquire surface reflectance through atmospheric correction. Thus, it is essential to develop an atmospheric correction method suitable for CAS500-4. Since the absorption and scattering characteristics in the atmosphere vary depending on the wavelength, it is needed to analyze the sensitivity of atmospheric correction parameters such as aerosol optical depth (AOD) and water vapor (WV) considering the wavelengths of CAS500-4. In addition, as CAS500-4 has only five channels (blue, green, red, red edge, and near-infrared), making it difficult to directly calculate key parameters for atmospheric correction, external parameter data should be used. Therefore, thisstudy performed a sensitivity analysis of the key parameters (AOD, WV, and O3) using the simulated images based on Sentinel-2 satellite data, which has similar wavelength specifications to CAS500-4, and examined the possibility of using the products of GEO-KOMPSAT-2A (GK2A) as atmospheric parameters. The sensitivity analysisshowed that AOD wasthe most important parameter with greater sensitivity in visible channels than in the near-infrared region. In particular, since AOD change of 20% causes about a 100% error rate in the blue channel surface reflectance in forests, a highly reliable AOD is needed to obtain accurate surface reflectance. The atmospherically corrected surface reflectance based on the GK2A AOD and WV was compared with the Sentinel-2 L2A reflectance data through the separability index of the known land cover pixels. The result showed that two corrected surface reflectance had similar Seperability index (SI) values, the atmospheric corrected surface reflectance based on the GK2A AOD showed higher SI than the Sentinel-2 L2A reflectance data in short-wavelength channels. Thus, it is judged that the parameters provided by GK2A can be fully utilized for atmospheric correction of the CAS500-4. The research findings will provide a basis for atmospheric correction of the CAS500-4 in the future.
Kim, Young-Chul;Chae, Hyun-Hee;Park, You-Cheol;Lee, Seon-Mi;Nam, Gi-Heum
Korean Journal of Environment and Ecology
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v.35
no.5
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pp.438-479
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2021
Basic information such as flora and their distribution are the key factors to consider for preserving plant diversity on a regional level. The number of plant species identified through a survey is closely related to the survey area and the number of habitats distributed within the survey area. In this study, we surveyed the flora of Mt. Maryong-san (PH) and Mt. Daeso-san (YH) located in Uljin-gun, Gyeongsangbuk-do, six and nine times, respectively. We planned to include a variety of habitats in the survey routes. As a result, we identified a total of 594 taxa composing of 112 families, 349 genera, 548 species, 10 subspecies, 34 varieties, and 2 formulas in the Mt. Maryong-san (PH) area and a total of 434 taxa composing of 89 families, 270 genera, 400 species, 9 subspecies, and 25 varieties in the Mt. Daeso-san (YH) area. Of the plants observed in the 21 habitats, the plants distributed in the transition zone around the valley and the dry grassland accounted for the highest proportion. The traditional graveyards located on the coast also served as the major habitat for the distribution of some plant species. In the two graveyards, 19 taxa of endemic plant species were surveyed. Moreover, the identified floristic target species included 1 taxon for grade V, 11 taxa for grade IV, and 24 taxa for grade III. A total of 77 taxa of naturalized plants were identified, and four of them were invasive alien plants as designated by the Ministry of Environment. The differences in the plants distributed in the area of Mt. Maryong-san (PH) and Mt. Daeso-san (YH) were mainly due to the difference in the size of each habitat distributed within the survey area. Moreover, it was judged that the entire vicinity of Mt. Daeso-san (YH) was not connected to the surrounding mountains and was an isolated area surrounded by farmland and residential areas.
Journal of Korean Home Economics Education Association
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v.33
no.1
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pp.1-16
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2021
The purpose of this study was to investigate the needs of middle school students for the practical reasoning in a distance learning environment, to verify the needs differences based on the learner's personal characteristics, student-teacher interaction, and student-student interaction, and to investigate the relationships among student-teacher interaction, voluntary participation of students, and the students' perception of the extent to which practical reasoning is implemented in distance learning. For this purpose, 1,842 middle school students from seven schools in Gyeonggi, Daejeon, Chungbuk, and Sejong areas were surveyed online to investigate the importance of the practical reasoning questions and the how much practical reasoning is implemented in current distance learning. Among them, 1,095 responses were used for final analysis and descriptive statistics, independent sample t-test, one-way ANOVA, and path analysis were conducted. As a result of the study, first, middle school students acknowledged that the practical reasoning was important with the importance average 3.76. Based on the locus for focus model, the priorities of the needs in home economics class were examined, and the values and importance of the problem, and the ramification of the solution were considered to be of high priority. Second, characteristics of middle school students, student-teacher interaction and student-student interaction were found to have positive influence on needs for practical reasoning, while no difference were found by gender or voluntary participation in distance learning. Third, the voluntary participation of students and the student-teacher interaction in distance learning had a positive (+) significant effect on perceived implementation of practical reasoning, yet negative (-) significant effect on needs for practical reasoning.
Journal of agricultural medicine and community health
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v.46
no.4
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pp.280-294
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2021
Objectives: The purpose of this study is to investigate the effects of social capital characteristics, socio-demographic characteristics, physical condition, and health behavior characteristics on health-related quality of life of the elderly in Korea. Methods: T-test, one-way ANOVA, and regression analysis were performed by applying a complex sample design to 57.787 people aged 65 and over using the 2019 Community Health Survey. Results: First, as a result of complex-sample T-test and ANOVA analysis, it was found that there were differences in health-related quality of life according to social capital characteristics, physical condition & health behavior characteristics, and socio-demographic characteristics. Complex Sample Regression Analysis Results, the explanatory power of the model was 28%. When living in the metropolitan area, living in an apartment building, having a spouse, having a higher household income, economic activity, higher educational attainment, increase sleeping time, walking time, frequent binge drinking, health checkup, networking, trust, and social participation showed higher health-related quality of life. When people were older, their gender was female, higher BMI, number of chronic diseases, and severe stress that showed lower health-related quality of life. Conclusions: It was proved that the factors affecting the health-related quality of life of the elderly are not only physical condition and health behavior factors, but also social capital and socio-demographic characteristics. It was found that the role as a member was important.
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.
Kim, Ju-Heon;Han, Sung-Mi;Song, Hyun-Ouk;Seo, Youn-Kyung;Moon, Young-Suk;Kim, Hong-Tae
Anatomy & Biological Anthropology
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v.31
no.4
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pp.133-142
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2018
3D histology is a imaging system for the 3D structural information of cells or tissues. The synchrotron radiation propagation phase contrast micro-CT has been used in 3D imaging methods. However, the simple phase contrast micro-CT did not give sufficient micro-structural information when the specimen contains soft elements, as is the case with many biomedical tissue samples. The purpose of this study is to develop a new technique to enhance the phase contrast effect for soft tissue imaging. Experiments were performed at the imaging beam lines of Pohang Accelerator Laboratory (PAL). The biomedical tissue samples under frozen state was mounted on a computer-controlled precision stage and rotated in $0.18^{\circ}$ increments through $180^{\circ}$. An X-ray shadow of a specimen was converted into a visual image on the surface of a CdWO4 scintillator that was magnified using a microscopic objective lens(X5 or X20) before being captured with a digital CCD camera. 3-dimensional volume images of the specimen were obtained by applying a filtered back-projection algorithm to the projection images using a software package OCTOPUS. Surface reconstruction and volume segmentation and rendering were performed were performed using Amira software. In this study, We found that synchrotron phase contrast imaging of frozen tissue samples has higher contrast power for soft tissue than that of non-frozen samples. In conclusion, synchrotron radiation propagation phase contrast cryo-microCT imaging offers a promising tool for non-destructive high resolution 3D histology.
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