• Smart Media Journal
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• v.10 no.4
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• pp.35-44
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• 2021

Recently, the new subway project called "Great Train Express" is in progress. During the tunnel excavation in the center of city, vibration and noise are generated, which make an uncomfortable effect on nearby residents. In order to prepare for this situation, the construction company generally establishes a noise and vibration management plan at the site from the construction planning stage through consultation with the residents of nearby areas and establishment of countermeasures for complaints raised. However, despite the establishment of a noise and vibration management plan, civil complaints have not been fundamentally resolved due to occurring noise and vibration during the construction in progress. In order to solve this problems, one of the best solution is to provide noise and vibration simulation technology with a high sense of reality and immersion for residents of nearby areas. Considering the ease and convenience of using the system, we intend to develop a UI(User Interface) necessary for the development of a simulation system that can directly experience the air blast and vibration based on virtual reality. The results of this study are expected to contribute to the development of virtual reality-based air blast and vibration simulations in the future.

• Journal of Korean Society of Transportation
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• v.32 no.1
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• pp.27-38
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• 2014

Recently, urban and transportation planning for Transit Oriented Development(TOD) has become a major issue. For the effective policy implementation of TOD, it is important to understand the travel behavior of residents in housing areas. In this study, we compared the travel behaviors of residents by housing types based on 'the 2010 Household Travel Survey Data' focusing on metropolitan areas. By building an estimation model for subway trip frequency by housing types, it was identified that the factors influencing subway trips and ultimately suggested implications to increase the use of the subway. The highest share of bus mode was for detached house residents with 22.8%, whereas the share of subway mode was highest by efficiency apartment residents with 17.5%. Walking distance to the subway from efficiency apartment and row house were verified as 661meters and 749meters. As the residents of each housing type have more cars and bicycles, their subway trips were decreased. It was also found that subway trips were increased when the population density of residence was high with good accessibility to subway stations and poor accessibility to bus service. In this study, the statistical findings to differentiate the planning factors of public transportation by housing types were also provided. The results of this study would be used for urban design considering the travel behaviors of residents by housing types and can also be utilized for promoting the patronage of public transportation. Some limitations and a future research agenda have also been discussed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.11-27
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• 2017

The road network system of major domestic urban areas such as city of Seoul was rapidly developed and regionally expanded. In addition, many kinds of life-lines such as electrical cables, telephone cables, water&sewerage lines, heat&cold conduits and gas lines were needed in order for urban residents to live comfortably. Therefore, most of the life-lines were individually buried in underground and individually managed. The utility tunnel is defined as the urban planning facilities for commonly installing life-lines in the National Land Planning Act. Expectation effectiveness of urban utility tunnels is reducing repeated excavation of roads, improvement of urban landscape; road pavement durability; driving performance and traffic flow. It can also be expected that ensuring disaster safety for earthquakes and sinkholes, smart-grind and electric vehicle supply, rapid response to changes in future living environment and etc. Therefore, necessity of urban utility tunnels has recently increased. However, all of the constructed utility tunnels are cut-and-cover tunnels domestically, which is included in development of new-town areas. Since urban areas can not accommodate all buried life-lines, it is necessary to study the feasibility assessment system for utility tunnel by urban patterns and capacity optimization for urban utility tunnels. In this study, we break away from the new-town utility tunnels and suggest a quantitative assessment model based on the evaluation index for urban areas. In addition, we also develop a program that can implement a quantitative evaluation system by subdividing the feasibility assessment system of urban patterns. Ultimately, this study can contribute to be activated the urban utility tunnel.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.20-29
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• 2006

Modeling urban climate caused by land use conversion is critical for human welfare and sustainable development, but has hampered because detailed information on urban characteristics is hard to obtain. With the advantage of satellite observations and the new statistical boundary system, this paper measures the economic and environmental effects of green area loss due to land use conversion in urban areas. To perform this purpose, data were collected from the various sources basic statistical unit data from the National Statistical Office, digital maps from the National Geographic Information Institute, satellite images, and field surveys when necessary. All data (maps and attributes) are built into the geographic information system (GIS). This paper also utilizes Landsat TM 5 imagery of Daegu city to derive vegetation index and to measure average surface temperature. The satellite data were examined using standard image processing software, ERDAS IMAGINE, and the results of the digital processing were presented with ARCVIEW(v.3.3). SAS package was used to perform statistical analyses. This study presents that there exists a strong relationship between land use change and climatic change as well as land price change. Based on results of the analysis, this paper suggests that planners should implement effective tools and policies of urban growth management to detect environmental quality and to make right decisions on policies concerning smart urban growth.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.45-58
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• 2024

Drought risk is expected to increase as the frequency, intensity, and duration of droughts increase due to climate change. Drought risk is related to not only hydro-meteorological factors, but also water supply and demand. Recently, along with climate change, socioeconomic factors have also been recognized to increase drought risk. Therefore, it is necessary to outlook the drought risk considering various conditions for coping with future extreme droughts in a timely manner. In addition, considering various drought scenarios help reduce the uncertainty in future drought outlook. In this study, drought scenarios considering climate change scenarios, population, and water demand were created to outlook drought risk for 160 administrative districts in Korea, then new levels of drought risk were assigned based on the results of drought risk outlook to suggest drought management measures. The results showed that the drought risk will increase in the future in 2020, 2025, and 2030, compared to past. Especially the drought risk is likely twice as high in 2030 under the baseline and high scenarios. Applying the drought outlook results from this study to the new methodology for setting the risk levels shows that most regions are in Response (V) in 2020 and 2030 for baseline and high scenarios.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.21-32
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• 2023

The Environmental Impact Assessment (EIA) plays a pivotal role in predicting the potential environmental impacts of proposed developments and planning appropriate mitigation measures to minimize effects on species. However, as concerns over biodiversity loss rise, there's ongoing debate about the efficacy of these mitigation plans. In this study, we utilized data from EIAs and post-environmental impact surveys to understand the trends in biodiversity during construction and operation phases. By examining 30 urban development projects, we categorized species richness indices of mammals, birds, amphibians, and reptiles into pre-construction, during construction, and post-construction operational stages. The biodiversity trends were analyzed based on the rate of change in these indices. The results revealed three distinct biodiversity change patterns: (A) An initial increase in biodiversity indices post-development, followed by a gradual decline over time; (B) a sustained increase in biodiversity as a result of mitigation measures; and (C) a continuous decline in biodiversity post-development. Furthermore, all species exhibited a higher rate of biodiversity decline during the construction phase compared to the operational phase, with mammals showing the most significant rate of change. Notably, the biodiversity change rate during operation was generally lower than during construction. In particular, mammals seemed to be most influenced by mitigation measures, displaying the smallest rate of change. This study provides empirical evidence on the efficacy of mitigation measures and deliberates on ways to enhance their effectiveness in minimizing the adverse impacts of urban development on biodiversity. These findings can serve as foundational data for addressing terrestrial biodiversity reduction.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.23-37
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• 2018

In recent years, it is very difficult to construct and expand new infrastructures in a city center because of long-term low growth and lack of space due to urban overcrowding. So, there is a need to study a variety of Retrofitting techniques and urban applications that can lead to sustainable development while efficiently utilizing existing facilities. 'Retrofit' means a sustainable urban retrofitting as a directed alteration of the structures, formations and systems of existing facilities to improve energy, water and waste efficiencies. In this study, we applied a hierarchical network design technique that can reflect the structural hierarchy of a city to study how to retrofit public transportation routes in Seoul. The hierarchical network design means dividing the hierarchy according to the functions of hubs and connecting different hierarchies to form a hierarchical network. As a result of comparing the application results of various retrofitting scenarios of public transport, the differences of daily PKT and PHT by about 2.6~3.2% less than before the improvement address that the convenience of passengers is increased. Therefore, it is expected that if the route planning is established according to the proposed method, it will increase the number of passengers and the operational efficiency by the improved convenience of public transit passengers.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.151-164
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• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• 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.