• Korean Journal of Heritage: History & Science
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• v.56 no.4
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• pp.132-158
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• 2023

The five-story and seven-story stone pagodas at Cheongnyangsaji temple site in Gongju are located under the Sambulbong peak of Gyeryongsan mountain, and are known to have been built of the middle in Goryeo dynasty. As the two pagodas in which two types of Baekje stone pagoda coexist in one era, their historical and academic value are recognized. The seven-story pagoda was overturned by robbery in 1944, and as a result, the five-story pagoda was tilted. Although the two pagodas were restored in 1961, structural instability was continuously raised. In this study, measurement data accumulated from May 2021 to March 2022, and seasonal characteristics were reviewed, and the micro behavior of pagodas were analyzed according to temperature and precipitation during the same period. As a result, the micro thermoelastic behavior was repeated according to the daily temperature change in all sensors, and both the slope and the displacement showed microscale behavior. In the inclinometer, moisture containing the surface and inside of the stones repeated expansion and contraction due to temperature change, showing the micro movements. In particular, the upper part of the five-story pagoda moved up to 3.89° to the northwest, and the seven-story pagoda tilted up to 0.078° to the northeast. The maximum displacements were recorded as 0.127 and 0.149 mm in the five-story and the seven-story pagoda, respectively. These values tended to return to the original position at the end of the measurement, but did not recover completely, indicating a state requiring precise monitoring. The result obtained through the study can be used as basic data for the stable conservation of the two stone pagodas. Based on the behavioral characteristics considering various environmental factors should be analyzed, and the preventive conservation through the maintenance of measurement system built this time should be continued.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.869-881
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• 2023

Purpose: This study aims to come up with improvement measures to improve the effectiveness of child safety measures. Method: The current status of child safety accidents was investigated and implications were deduced by analyzing major child safety measures by government department in the past. In addition, a perception survey was conducted on 1,000 people including children, guardians, and children's facility workers who are subject to child safety policies. Result: Regarding the safety of children's living space(environment), 35.3% of guardians answered that more than 1/3 of them were not safe. Both guardians(95.3%) and children's facility workers(89%) answered that there was the highest risk of 'traffic accidents', and the second risk factor was parents(carelessness of workers at children's facilities) and children's facility workers(careless of guardians at home). Looking at the risks by place, "road and sidewalk" was the most dangerous place and for child safety, guardians(64.3%) and workers (78.3%) both said that the role of "parent" is the most important. For improvements to prevent child safety accidents, the response rate of "strengthening safety management of road traffic facilities" is the most necessary with 75.8% for guardians and 65% for child use facilities. Conclusion: The reinforcement measures to strengthen the effectiveness of child safety measures are as follows. First, in order to ensure the continuity of child safety measures, it should be operated effectively so that those subject to the establishment of the Comprehensive Plan for Child Safety, which took effect in August 2022, can feel it. Second, in order to improve the sensitivity of children's policy targets, promotion measures that take into account the characteristics of each child safety field should be continuously strengthened. Third, it is necessary to expand safety infrastructure for each field to secure child safety. Fourth, it is necessary to strengthen safety education that can ensure safety for children themselves and to come up with detailed measures to make safety education for parents(guardians) mandatory.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1341-1352
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• 2023

The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1309-1320
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• 2023

The technological development and popularization of mobile devices have developed so that users can check their location anywhere and use the Internet. However, in the case of indoors, the Internet can be used smoothly, but the global positioning system (GPS) function is difficult to use. There is an increasing need to provide real-time location information in shaded areas where GPS is not received, such as department stores, museums, conference halls, schools, and tunnels, which are indoor public places. Accordingly, research on the recent indoor positioning technology based on light detection and ranging (LiDAR) equipment is increasing to build a landmark database. Focusing on the accessibility of building a landmark database, this study attempted to develop a technique for estimating the user's location by using a single image taken of a landmark based on a mobile device and the landmark database information constructed in advance. First, a landmark database was constructed. In order to estimate the user's location only with the mobile image photographing the landmark, it is essential to detect the landmark from the mobile image, and to acquire the ground coordinates of the points with fixed characteristics from the detected landmark. In the second step, by applying the bag of words (BoW) image search technology, the landmark photographed by the mobile image among the landmark database was searched up to a similar 4th place. In the third step, one of the four candidate landmarks searched through the scale invariant feature transform (SIFT) feature point extraction technique and Homography random sample consensus(RANSAC) was selected, and at this time, filtering was performed once more based on the number of matching points through threshold setting. In the fourth step, the landmark image was projected onto the mobile image through the Homography matrix between the corresponding landmark and the mobile image to detect the area of the landmark and the corner. Finally, the user's location was estimated through the location estimation technique. As a result of analyzing the performance of the technology, the landmark search performance was measured to be about 86%. As a result of comparing the location estimation result with the user's actual ground coordinate, it was confirmed that it had a horizontal location accuracy of about 0.56 m, and it was confirmed that the user's location could be estimated with a mobile image by constructing a landmark database without separate expensive equipment.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1321-1330
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• 2023

Normalized Difference Vegetation Index (NDVI) is the most widely used remote sensing data in the agricultural field and is currently provided by most optical satellites. In particular, as high-resolution optical satellite images become available, the selection of optimal optical satellite images according to agricultural applications has become a very important issue. In this study, we aim to define the most optimal optical satellite image when monitoring NDVI in rice fields in Korea and derive the resolution-related requirements necessary for this. For this purpose, we compared and analyzed the spatial distribution and time series patterns of the Dangjin rice paddy in Korea from 2019 to 2022 using NDVI images from MOD13, Landsat-8, Sentinel-2A/B, and PlanetScope satellites, which are widely used around the world. Each data is provided with a spatial resolution of 3 m to 250 m and various periods, and the area of the spectral band used to calculate NDVI also has slight differences. As a result of the analysis, Landsat-8 showed the lowest NDVI value and had very low spatial variation. In comparison, the MOD13 NDVI image showed similar spatial distribution and time series patterns as the PlanetScope data but was affected by the area surrounding the rice field due to low spatial resolution. Sentinel-2A/B showed relatively low NDVI values due to the wide near-infrared band area, and this feature was especially noticeable in the early stages of growth. PlanetScope's NDVI provides detailed spatial variation and stable time series patterns, but considering its high purchase price, it is considered to be more useful in small field areas than in spatially uniform rice paddy. Accordingly, for rice field areas, 250 m MOD13 NDVI or 10 m Sentinel-2A/B are considered to be the most efficient, but high-resolution satellite images can be used to estimate detailed physical quantities of individual crops.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1553-1563
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• 2023

The Geostationary Ocean Color Imager-II (GOCI-II) is a satellite designed for ocean color observation, covering the Northeast Asian region and the entire disk of the Earth. It commenced operations in 2020, succeeding its predecessor, GOCI, which had been active for the previous decade. In this study, we aimed to enhance the atmospheric correction algorithm, a critical step in producing satellite-based ocean color data, by performing cross-calibration on the GOCI-II near-infrared (NIR) band using the GOCI NIR band. To achieve this, we conducted a cross-calibration study on the top-of-atmosphere (TOA) radiance of the NIR band and derived a vicarious calibration gain for two NIR bands (745 and 865 nm). As a result of applying this gain, the offset of two sensors decreased and the ratio approached 1. It shows that consistency of two sensors was improved. Also, the Rayleigh-corrected reflectance at 745 nm and 865 nm increased by 5.62% and 9.52%, respectively. This alteration had implications for the ratio of Rayleigh-corrected reflectance at these wavelengths, potentially impacting the atmospheric correction results across all spectral bands, particularly during the aerosol reflectance correction process within the atmospheric correction algorithm. Due to the limited overlapping operational period of GOCI and GOCI-II satellites, we only used data from March 2021. Nevertheless, we anticipate further enhancements through ongoing cross-calibration research with other satellites in the future. Additionally, it is essential to apply the vicarious calibration gain derived for the NIR band in this study to perform vicarious calibration for the visible channels and assess its impact on the accuracy of the ocean color products.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1635-1650
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• 2023

Under global warming, the steadily increasing sea surface temperature (SST) severely impacts marine ecosystems,such as the productivity decrease and change in marine species distribution. Recently, the catch of Todarodes Pacificus, one of South Korea's primary marine resources, has dramatically decreased. In this study, we analyze the marine environment that affects the formation of fishing grounds of Todarodes Pacificus and develop seasonal habitat suitability index (HSI) models based on various satellite data including Geostationary Ocean Color Imager (GOCI) data to continuously manage fisheries resources over Korean exclusive economic zone. About 83% of catches are found within the range of SST of 14.11-26.16℃,sea level height of 0.56-0.82 m, chlorophyll-a concentration of 0.31-1.52 mg m^-3, and primary production of 580.96-1574.13 mg C m^-2 day^-1. The seasonal HSI models are developed using the Arithmetic Mean Model, which showed the best performance. Comparing the developed HSI value with the 2019 catch data, it is confirmed that the HSI model is valid because the fishing grounds are formed in different sea regions by season (East Sea in winter and Yellow Sea in summer) and the high HSI (> 0.6) concurrences to areas with the high catch. In addition, we identified the significant increasing trend in SST over study regions, which is highly related to the formation of fishing grounds of Todarodes Pacificus. We can expect the fishing grounds will be changed by accelerating ocean warming in the future. Continuous HSI monitoring is necessary to manage fisheries' spatial and temporal distribution.

• Journal of Venture Innovation
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• v.4 no.3
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• pp.1-15
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• 2021

Due to long-term social distancing due to the spread of COVID-19, business trends of restaurant companies are being implemented in accordance with the changed environment such as packaging and subscription. However, even in this environment, upscale restaurants are generating high profits by trying to differentiate themselves from existing restaurants by providing high-quality services with the best facilities. Therefore, this study describes how customers' experience of upscale restaurant service influences behavioral loyalty. That is, the purpose of this study is to determine the effect of service experience on cognitive satisfaction and emotional attachment, and to examine the causal role of cognitive satisfaction and emotional attachment by confirming the relationship between these constructs and relationship commitment and behavioral loyalty. To verify this, data were collected through face-to-face interviews with 300 consumers who recently used a upscale restaurant. Of the collected data, 275 copies(91.6%) were used for the final analysis, and inaccurate or erroneous data among 25 response sheets were excluded. In this study, the validity and reliability of the data were checked and the research hypothesis was verified by using SPSS 21.0 and AMOS 20 statistical package. Frequency analysis was performed to confirm the demographic characteristics of the respondent. Structural equation model analysis(SEM) was used to confirm the fit of the research model and to verify the research hypothesis. As a result of the research hypothesis analysis, it was found that service experience had a positive effect on cognitive satisfaction, and cognitive satisfaction had a positive effect on emotional attachment, relationship commitment, and behavioral loyalty. Also, it was found that emotional attachment had a positive effect on relationship commitment and behavioral loyalty, and relationship commitment had a positive effect on behavioral loyalty. However, service experience did not affect emotional attachment. With this study, marketers and managers of upscale restaurants such as hotel restaurants need to accurately select their target audience, understand their service needs, and then present the appropriate service to them. In addition, they should not only induce cognitive satisfaction by providing excellent service to their customers, but also identify moments of truth and present appropriate services so that satisfied customers can strengthen their emotional attachment. In addition, it is necessary to strengthen the relationship with their firms by forming friendly relationships with customers who have high emotional attachment, and also to induce relationship commitment so that such customers have a strong sense of belonging and attachment to their firms.

• Journal of Venture Innovation
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• v.4 no.2
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• pp.29-42
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• 2021

The stress on finding a job is also increasing in a situation where the difficulty in finding a job is aggravating due to the COVID-19 pandemic. In this study, the major satisfaction of college students was subdivided into subject satisfaction and relationship satisfaction, and the relationship between these and job-seeking stress was investigated. In addition, We tried to find out whether there is a difference in the influence relationship between these majors according to their current major, that is, whether they majored in a science, engineering major or a social science major. The population for the study was the students currently enrolled in the 4th grade, and the research sample was obtained from students of H and N universities in the metropolitan area. A total of 220 people were analyzed, 110 people from science and engineering and 110 from social sciences. For analysis, SPSS 24.0 and Process Macro 5.0 were used. The empirical analysis results are as follows. First, subject satisfaction had a negative (-) effect on job-seeking stress. Second, relationship satisfaction also had a significant negative (-) effect on job-seeking stress. Third, there was a significant difference between science, engineering students and social science students in the effect of subject satisfaction on job-seking stress. Fourth, in the effect of relationship satisfaction on job-seeking stress, there was also a significant difference between science, engineering students and social science students. Therefore, the higher the satisfaction with the major you are majoring in, the lower the job-seeking stress, and the extent of this decrease is social science students were larger than science, engineering students. It is necessary to be cautious in generalizing the results of this study, which was made in the context of the COVID-19 pandemic. Based on the empirical analysis results, the academic and practical implications of this study are presented.