• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.55-63
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• 2021

The purpose of this study was to investigate the structural relationship between the use motives of the Internet of Things (IoT), which was presented as a technology strategy priority for university students, on usage attitudes, usability performance and life satisfaction. From April 1 to April 30, 2021, a non-face-to-face survey was conducted targeting university students living in Gwangju Metropolitan City and Jeollanam-do, and the study was conducted in a total of 213 copies. The collected questionnaires were analyzed using IBM's SPSS 21.0 and AMOS 21.0 programs. The research results are as follows. First, the motivation for using IoT was found to have an effect on usage attitude, and it was found to have an effect on life satisfaction and also on usage performance. Second, it was found that the attitude of using the Internet of Things had an effect on the usability performance. However, it was found that there was no effect on life satisfaction. Third, it was found that the use of IoT has an effect on the life satisfaction of college students. Fourth, it was found that the indirect effect on the attitude of use had an indirect effect on the relationship between the motivation for use and the performance of use. However, it was found that there was no indirect effect on the relationship between use motivation and life satisfaction. Fifth, the indirect effect on the usability performance was found to have an indirect effect on the relationship between use motivation and life satisfaction, Also, it was found that there was an indirect effect on the relationship between usage attitude and life satisfaction. Sixth, in the relationship between use motivation and life satisfaction, there was no double indirect effect via use attitude and utilization performance. Based on these results, the motivation for using the Internet of Things for college students and a solution to the information gap were proposed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.1-7
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• 2022

The purpose of this study is to discuss the impact of unmanned aerial vehicle service and how to activate it. The discussion on the impact of the introduction of the unmanned aerial vehicle service was examined in terms of economic, environmental, and social acceptance, and a plan to revitalize the industry was presented. In terms of economic impact, if transportation services are increased using unmanned aerial vehicles in the future, road-based transportation cargo may decrease and road movement speed may increase due to reduced road congestion. This can have a positive effect on the increase in the value of land or real estate assets, and it also provides an impact on smart city design. In terms of environmental impact, unmanned aerial vehicles (UAVs) generally move through electricity, so they emit less exhaust gas compared to other existing devices, such as vehicles and railroads, and thus have less environmental impact. However, noise can have a negative impact on the habitat in the presence of wild animals along their migration routes. In terms of social acceptability of unmanned aerial vehicles (UAV) technology, areas that are declining due to the emergence of new services may appear, and at the same time, organizations that create profits may appear, causing conflicts between industries. Therefore, it is essential to form a social consensus on the acceptance of emerging industries. The government should come up with various countermeasures to minimize the negative impact that reflects the characteristics of the unmanned aerial vehicle use service. Just as various systems such as road signs were introduced so that vehicles can be operated on the ground to secure air routes in the mid- to long-term for revitalization of unmanned-based industries, development and establishment of services that should be introduced and applied prior to constructing air routes I need this. In addition, the design and implementation of information collection and operation plans for unmanned air traffic management in Korea and a plan to secure a control system for each region should also be made. This study can contribute to providing ideas for mid- to long-term research on new areas with the development of the unmanned aerial vehicle industry.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.3
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• pp.19-34
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• 2022

This study was conducted to provide basic data that can be used when establishing Net Zero policies and implementation plans for non-urban settlements by quantitatively analyzing the Net Zero contribution to green infrastructure in rural areas corresponding to non-urban settlements. The main purpose is to first, systematize green infrastructure in rural areas, secondly derive basic units for each element of green infrastructure, and thirdly quantify and present the impact on Net Zero in Korea using these. In this study, CVR(Content Validity Ration) analysis was performed to verify the adequacy of green infrastructure elements in rural areas derived through research and analysis of previous studies, is as follows. First, Hubs of Green infrastructure in rural area include village forests, wetlands, farm land, and smart farms with a CVR value of .500 or higher. And Links of Green infrastructure in rural area include streams, village green areas, and LID (rainwater recycling). Second, the basic unit for each green infrastructure element was presented by classifying it into minimum, maximum, and median values using the results of previous studies so that it could be used for spatial planning and design for Net Zero. Third, when Green infrastructure in rural areas is applied to non-urban settlements in Korea, it is analyzed that it has the effect of indirectly reducing CO₂ by at least 70.76 million tons and up to 141.16 million tons. This is 3.4 to 6.7 times the amount of CO₂ emission from the agricultural sector in 2019, and it can be seen that the contribution to Net Zero is very high. It is expected to greatly contribute to the transformation of the ecosystem. This study quantitatively presented the carbon-neutral contribution to settlements located in non-urban areas, and by deriving the carbon reduction unit for each element of green infrastructure in rural areas, it can be used in spatial planning and design for carbon-neutral at the village level. It has significance as a basic research. In particular, the basic unit of carbon reduction for each green infrastructure factors will be usable for Net Zero policy at the village level, presenting a quantitative target when establishing a plan, and checking whether or not it has been achieved. In addition, based on this, it will be possible to expand and apply Net Zero at regional and city units such as cities, counties, and districts.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.737-748
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• 2022

Due to the lack of flood data, the water engineering practice calculates the design flood using rainfall frequency analysis and rainfall-runoff model. However, the rainfall frequency analysis for arbitrary duration does not reflect the regional characteristics of the duration and amount of storm event. This study proposed a practical method to calculate the design flood in a watershed considering the characteristics of storm event, based on the bivariate rainfall frequency analysis. After extracting independent storm events for the Pyeongchang River basin and the upper Namhangang River basin, we performed the bivariate rainfall frequency analysis to determine the design storm events of various return periods, and calculated the design floods using the HEC-1 model. We compared the design floods based on the bivariate rainfall frequency analysis (DF_BRFA) with those estimated by the flood frequency analysis (DF_FFA), and those estimated by the HEC-1 with the univariate rainfall frequency analysis (DF_URFA). In the case of the Pyeongchang River basin, except for the 100-year flood, the average error of the DF_BRFA was 11.6%, which was the closest to the DF_FFA. In the case of the Namhangang River basin, the average error of the DF_BRFA was about 10%, which was the most similar to the DF_FFA. As the return period increased, the DF_URFA was calculated to be much larger than the DF_FFA, whereas the BRFA produced smaller average error in the design flood than the URFA. When the proposed method is used to calculate design flood in an ungauged watershed, it is expected that the estimated design flood might be close to the actual DF_FFA. Thus, the design of the hydrological structures and water resource plans can be carried out economically and reasonably.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.497-510
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• 2022

Agricultural reservoirs are essential structures for water supplies during dry period in the Korean peninsula, where water resources are temporally unequally distributed. For efficient water management, systematic and effective monitoring of medium-small reservoirs is required. Synthetic Aperture Radar (SAR) provides a way for continuous monitoring of those, with its capability of all-weather observation. This study aims to evaluate the applicability of SAR in monitoring medium-small reservoirs using Sentinel-1 (10 m resolution) and Capella X-SAR (1 m resolution), at Chari (CR), Galjeon (GJ), Dwitgol (DG) reservoirs located in Ulsan, Korea. Water detected results applying Z fuzzy function-based threshold (Z-thresh) and Chan-vese (CV), an object detection-based segmentation algorithm, are quantitatively evaluated using UAV-detected water boundary (UWB). Accuracy metrics from Z-thresh were 0.87, 0.89, 0.77 (at CR, GJ, DG, respectively) using Sentinel-1 and 0.78, 0.72, 0.81 using Capella, and improvements were observed when CV was applied (Sentinel-1: 0.94, 0.89, 0.84, Capella: 0.92, 0.89, 0.93). Boundaries of the waterbody detected from Capella agreed relatively well with UWB; however, false- and un-detections occurred from speckle noises, due to its high resolution. When masked with optical sensor-based supplementary images, improvements up to 13% were observed. More effective water resource management is expected to be possible with continuous monitoring of available water quantity, when more accurate and precise SAR-based water detection technique is developed.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.28-43
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• 2022

This study classified UAV image-based physical spatial types for parks in urban areas of Changwon City and analyzed thermal comfort characteristics according to physical spatial types by comparing them with ENVI-met thermal comfort results. Physical spatial types were classified into four types according to UAV-based NDVI and SVF characteristics. As a result of ENVI-met thermal comfort, the T_MRT difference between the tree-dense area and other areas was up to 30℃ or more, and it was 19. 6℃ at 16:00, which was the largest during the afternoon. As a result of analyzing UAV-based physical spatial types and thermal comfort characteristics by time period, it was confirmed that the physical spatial types with high NDVI and high SVF showed a similar to thermal comfort change patterns by time when using UAV, and the physical spatial types with dense trees and artificial structures showed a low correlation to thermal comfort change patterns by time when using UAV. In conclusion, the possibility of identifying the distribution of thermal comfort based on UAV images was confirmed for the spatial type consisting of open and vegetation, and the area adjacent to the trees was found to be more thermally pleasant than the open area. Therefore, in the urban planning stage, it is necessary to create an open space in consideration of natural covering materials such as grass and trees, and when using artificial covering materials, it is judged that spatial planning should be done considering the proximity to trees and buildings. In the future, it is judged that it will be possible to quickly and accurately identify urban climate phenomena and establish urban planning considering thermal comfort through ground LIDAR and In-situ measurement-based UAV image correction.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.543-551
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• 2023

Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.631-639
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• 2023

Flash drought (FD), characterized by the rapid onset and intensification, can significantly impact ecosystems and induce immediate water stress. A more comprehensive understanding of the causes and characteristics of FD events is required to enhance drought monitoring. Therefore, we investigated the FD events took place over the Korean peninsula using Global Land Data Assimilation System (GLDAS) data from 2012 to 2022. We first detected FD events using the stress-based method (Standardized Evaporative Stress Ratio, SESR), and analyzed the frequency and duration of FDs. The FD events were classified into three cases based on the variations in Actual Evapotranspiration (AET) and potential Evapotranspiration (PET), and spatially analyzed. Results revealed that there are regional disparities in frequency and duration of FDs, with a mean frequency of 6.4 and duration of 31 days. When classified into Case 1 (normal condition), Case 2 (AET-driven), and Case 3 (PET-driven), we found that Case 2 FDs emerged approximately 1.5 times more frequently than those driven by PET (Case 3) across the Korean peninsula. Case 2 FDs were found to be induced under water-limited conditions, and led both AET and PET to be decreased. Conversely, Case 3 FDs occurred under energy-limited conditions, with increase in both. Case 2 FDs predominantly affected the northwestern and central-southern agricultural regions, while Case 3 occurred in the eastern region, characterized by forested land cover. These findings offers insights into our understanding of FDs over the Korean peninsula, considering climate factors, land cover, and water availability.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.53-73
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• 2023

Although it is mandatory to wear a seat belt that can minimize human injury when traffic accident occurs, the number of traffic accident casualties not wearing seat belts still accounts for a significant proportion.The seat belt wearing detection system for all seats is a system that identifies whether all seat passengers wear a seat belt and encourages their usage, also it can be a useful technical countermeasure. Firstly, this study established the viability of system implementation by assessing the factors influencing the severity of injuries in traffic accidents through the development of an ordered probit model. Analysis results showed that the use of seat belts has statistically significant effects on the severity of traffic accidents, reducing the probability of death or serious injury by 0.054 times in the event of a traffic accident. Secondly, a meta-analysis was conducted based on prior research related to seat belts and injuries in traffic accidents to estimate the expected reduction in accident severity upon the implementation of the system.The analysis of the effect of accident severity reduction revealed that wearing seat belts would lead to a 63.3% decrease in fatal accidents, with the front seats showing a reduction of 75.7% and the rear seats showing a reduction of 58.1% in fatal accidents. Lastly, Using the results of the meta-analysis and traffic accident statistics, the expected decrease in the number of traffic accident casualties with the implementation of the system was derived to analyze the traffic safety effects of the proposed detection system. The analysis demonstrated that with an increase in the adoption rate of the system, the number of casualties in accidents where seat belts were not worn decreased. Specifically, at a system adoption rate of 60%, it is anticipated that the number of fatalities would decrease by more than three times compared to the current scenario. Based on the analysis results, operational strategies for the system were proposed to increase seat belt usage rates and reduce accident severity.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.949-965
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• 2023

In this study, we propose a method to monitor the surface area of agricultural reservoirs in South Korea using Sentinel-1 synthetic aperture radar images and the deep learning model, Swin Transformer. Utilizing the Google Earth Engine platform, datasets from 2017 to 2021 were constructed for seven agricultural reservoirs, categorized into 700 K-ton, 900 K-ton, and 1.5 M-ton capacities. For four of the reservoirs, a total of 1,283 images were used for model training through shuffling and 5-fold cross-validation techniques. Upon evaluation, the Swin Transformer Large model, configured with a window size of 12, demonstrated superior semantic segmentation performance, showing an average accuracy of 99.54% and a mean intersection over union (mIoU) of 95.15% for all folds. When the best-performing model was applied to the datasets of the remaining three reservoirsfor validation, it achieved an accuracy of over 99% and mIoU of over 94% for all reservoirs. These results indicate that the Swin Transformer model can effectively monitor the surface area of agricultural reservoirs in South Korea.