KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.6D
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pp.697-705
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2010
The purpose of this research is to clarify the relation between environmental consciousness and railway usage behavior. Author would locate this research on position of basic survey to promote railway use according to Low Carbon Green Growth policy in Korea. In this research, we would perform descriptive analysis using data of research on the actual condition of railway use in 2008, Daegu, and describe its relationship. In addition, we would suggest some idea about policy which can promote railway use. The order of railway choice behavior noticed in clustering of environmental consciousness was cooperative behavior type, middle type and non-cooperative behavior type. It suggests that environmental consciousness has effect on transportation choice behavior. Specially, railway improvement isn't enough to promote railway use. And, it is advisable to carry out the improvement in such a way that it may encourage the nation to move from the current environmental consciousness stage to cooperative behavior. Moreover, we assumed Binary Probit(BP) model using SP data of time or condition of transportation expense compared with passenger car and bus. As the results, modified likelihood ratio of two BP models is favorable variables. And it occurred that mode was transferred from passenger car to railway when it showed higher social environment consciousness and low selfish environment consciousness, because t-statistic which represents selfish environment consciousness showed significance in 95% confidence level. That is, it can be described that environment consciousness affect on the intention of railway use.
KSCE Journal of Civil and Environmental Engineering Research
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v.26
no.1D
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pp.157-167
/
2006
During the first and second NGIS projects by the Korean government, The first one (1995~2000) was limited on constructing geographic information and the second (2001~2005) was focused on circulation and practical use of geoinformation from the result of the first project. In the latter half of 2nd NGIS project, However, the geographic information from the NGIS projects have not been renewed even though there were significant geographical changes. The accurate renewal of geoinformation is a matter of great importance to the next generation industry (e.g. LBS, Ubiquitous, Telematics). In this respect, it is time to update the geographic information in the latter half of the second NGIS project. Therefore, It is not only important to build an accurate geoinformation but also rapid and correct renewal of the geoinformation. NGII (National Geographic Information Institute) has been studying for improvement of digital map that was constructed by the result of the 1st NGIS project. Through the construction of clean digital map, NGII constructed Framework Data to three kinds of formats (NGI, NDA, NRL). Framework Data was contained to other database, and provided the reference system of location or contents for combining geoinformation. Framework Data is consist of Data Set, Data Model and UFID (Unique Feature Identifier). It will be achieved as national infrastructure data. This paper attempts to explore a method of the update to practical framework data with realtime geoinformation on feature's creation, modification and destruction managed by 'Feature management agency' using UFID's process. Furthermore, it suggests a method which can provide important data in order to plan the Framework update with the land change ratio.
Joon-Woo Lee;Yu-Han Han;Jeong-Taek Lee;Jin-Hyuk Park;Geun-Han Kim
Korean Journal of Remote Sensing
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v.39
no.6_3
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pp.1721-1730
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2023
As awareness of the problem of global warming emerges around the world, the role of carbon sinks in settlement is increasingly emphasized to achieve carbon neutrality in urban areas. In order to manage carbon sinks in settlement, it is necessary to identify the current status of carbon sinks. Identifying the status of carbon sinks requires a lot of manpower and time and a corresponding budget. Therefore, in this study, a map predicting the location of trees was created using already established tree location information and Sentinel-2 satellite images targeting Seoul. To this end, after constructing a tree presence/absence dataset, structured data was generated using 16 types of vegetation indices information constructed from satellite images. After learning this by applying the Extreme Gradient Boosting (XGBoost) model, a tree prediction map was created. Afterward, the correlation between independent and dependent variables was investigated in model learning using the Shapely value of Shapley Additive exPlanations(SHAP). A comparative analysis was performed between maps produced for local parts of Seoul and sub-categorized land cover maps. In the case of the tree prediction model produced in this study, it was confirmed that even hard-to-detect street trees around the main street were predicted as trees.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.15
no.4
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pp.192-202
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2010
Submarine groundwater discharge (SGD) has been recognized as a provider for freshwater, nutrients, and dissolved constituents from continents to the oceans and paid more attention with regard to the mass balance of water or dissolved constituents on local and global scales. The submarine discharge of fresh groundwater (fresh SGD) through seepage or springs in coastal ocean may be especially important in aspects of water resource and marine environment managements in the future. Based on the worldwide compilations of observed fresh SGD, our review reveals that fresh SGD occurs in various marine environments along most shoreline of the world and the global estimates of fresh SGD were approximately 0.01-17% of surface runoff. In addition, the input of fresh SGD calculated and investigated in this study were about 50%, 57%, 89%, and 420% of total river discharge in Jeju Island, Yeongil Bay, Masan Bay, and Yeoja Bay, respectively. These inputs from fresh SGD along the shoreline of Korea Peninsula are much higher than those of the whole world, greatly vary with the region. However, since these estimates are based on the water balance method mainly used in coastal ocean, we have to perform continuous monitoring of various parameters, such as precipitation, tide, evapotanspiration and water residence time, which have an impact on the water balance in a lot of areas for evaluating the precise input of fresh SGD. In addition, since the method estimating the input of fresh SGD has brought up many problems, it is required to make an intercomparison between various methods such as hydrogeological assumption, numerical modeling, and seepage meter.
This study derived production-production multipliers using a regional input-output table and estimated the induced effect of aggregates through the non-metallic minerals sector and the concrete products sector. In deriving the induced effect of aggregates, it is difficult to use the regional input-output table due to the sector classification problem. This study analyzed the non-metallic mineral sector, including aggregates, as aggregates sector, and the concrete products sector, which uses most of the aggregate production. By analyzing this, we attempted to alleviate difficulties caused by sector classification restrictions. In the process of estimating the induced effect, it was assumed that there was a decrease in aggregate production, and in the process of analyzing the concrete products sector, the effect of the decrease in concrete product production due to the decrease in aggregate production, that is, the decrease in production of one unit of aggregate was 0.8511 in the concrete product sector. The analysis was conducted on the premise of a decrease in unit production. Inducing effects within and between regions were calculated for the 17 metropolitan cities and provinces classified by the regional input-output table. The employment effect was also calculated, assuming a 10% production decrease to show differences according to the size of the aggregate and concrete product sectors in each region.
The Journal of the Convergence on Culture Technology
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v.10
no.4
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pp.693-700
/
2024
As of the end of March 2022, the total area of domestic industrial complexes is 606 km2, which is only about 0.6% of the total land area. However, as of 2018, the annual energy consumption of domestic industrial complexes is 110,866.1 thousand TOE, accounting for 53.5% of the country's total energy consumption and 83.1% of the entire industrial sector energy consumption. In addition, industrial complexes have a significant impact on the environment, accounting for 45.1% of the country's total greenhouse gas emissions and 76.8% of industrial sector greenhouse gas emissions. Under this background, in this study, in order to contribute to the energy efficiency of industrial complexes, a prediction study on energy demand and supply for an industrial complex in Korea using machine learning was conducted. In addition, a simulator UI screen was designed to more efficiently convey information on energy demand/supply prediction results and energy consumption status. Among the machine learning algorithms, Multi-Layer Perceptron (MLP) was used, and Bayesian Optimization was applied as an optimization technique for the prediction model. The energy prediction model for the industrial complex built in this study showed a prediction accuracy of 87.90% for compressed air demand and 99.54% for the flow rate available for the public air compressor.
Noise and air pollution, which accompany the development of industry and the increase of population, contribute to the deterioration of urban environment. The air pollution level of Seoul has gradually increased and the city residents are suffering from a high pollution of noise. If no measures were taken against pollution, the amount of emission of pollutant into air would be 36.7 thousand tons per year per square kilometer in 1975, three times more than that of 1970, and it would be the same level as that of United States in 1968. The main sources of air pollution in Seoul are the exhaust has from vehicles and the combustion of bunker-C oil for heating purpose. Thus, it is urgent that an exhaust gas cleaner should be instaled to every car and the fuel substituted by less sulfur-contained-oil to prevent the pollution. Transportation noise (vehicular noise and train noise) is the main component of urban noise problem. The average noise level in downtown area is about 75㏈ with maximum of 85㏈ and the vehicular homing was checked 100㏈ up and down. Therefore, the reduction of the number of bus-stop the strict regulation of homing in downtown area and a better maintenance of car should be an effective measures against noise pollution in urban areas. Within the distance of 200 metres from railroad, the train noise exceeds the limit specified by the pollution control law in Korea. Especially, the level of noise and steam-whistle of train as measured by the ISO evaluation can adversely affect the community activities of residents. To prevent environmental destruction, many developed countries have taken more positive action against worsening pollution and such an action is now urgently required in this country.
Journal of the Korean Association of Geographic Information Studies
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v.12
no.4
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pp.34-47
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2009
Rapid urbanization is causing environmental and ecological damage, development thoughtless for the environment, and social and economical issues. It is important to grasp urban growth situations and characteristics, reflect them, and establish a policy for the solution of issues pursuant to urbanization and the sustainable and efficient development of national land. This research aims to be used as basic data in establishing an urban policy by analyzing the situations and characteristics of urban growth for the past 20 years in our entire country rather than an existing district. For this, some urban districts were sampled using a 1980s and 2000s version of land cover map produced by Ministry of Environment, and then pattern analysis for urban growth by administrative district ranks was conducted using GIS and a statistical technique. As a result, the development zone area after 1980s has increased by 2.5 times as compared to that before 1980s, and especially in the farm villages neighboring the national capital region, it has increased by 21.2 times. Special cities and metropolitan cities were developed at the districts being low in altitude, close to the principal road and the major downtown, high in road ratio, and restricted environmentally, ecologically and legally, and were diverted from mountains, forests and grassland to urban land. On the other hand, farm villages neighboring a large city, farm villages neighboring the national capital region, and local farm villages were developed at the districts being high in altitude, far from the principal road and the major downtown, low in road ratio, and not restricted environmentally, ecologically and legally, and were diverted from farmland to urban land. That is, it can be seen that urban development has been actively realized despite the unfavorable topographical conditions in the suburban districts due to lack of available land and various regulations and policies as urban growth around big cities expands.
Kim, Sang-Wan;Han, Ahrim;Cho, Keunhoo;Kim, Donghan;Park, Sang-Eun
Korean Journal of Remote Sensing
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v.35
no.3
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pp.457-470
/
2019
Automatic Target Recognition (ATR) using Synthetic Aperture Radar (SAR) has been attracted attention in the fields of surveillance, reconnaissance, and national security due to its advantage of all-weather and day-and-night imaging capabilities. However, there have been some difficulties in automatically identifying targets in real situation due to various observational and environmental conditions. In this paper, ATR problems in Extended Operating Conditions (EOC) were investigated. In particular, we considered partial occlusions of the target (10% to 50%) and differences in the depression angle between training ($17^{\circ}$) and test data ($30^{\circ}$ and $45^{\circ}$). To simulate various occlusion conditions, SARBake algorithm was applied to Moving and Stationary Target Acquisition and Recognition (MSTAR) images. The ATR accuracies were evaluated by using the template matching and Adaboost algorithms. Experimental results on the depression angle showed that the target identification rate of the two algorithms decreased by more than 30% from the depression angle of $45^{\circ}$ to $30^{\circ}$. The accuracy of template matching was about 75.88% while Adaboost showed better results with an accuracy of about 86.80%. In the case of partial occlusion, the accuracy of template matching decreased significantly even in the slight occlusion (from 95.77% under no occlusion to 52.69% under 10% occlusion). The Adaboost algorithm showed better performance with an accuracy of 85.16% in no occlusion condition and 68.48% in 10% occlusion condition. Even in the 50% occlusion condition, the Adaboost provided an accuracy of 52.48%, which was much higher than the template matching (less than 30% under 50% occlusion).
Due to recent changes in government policy, officetels have received attention as alternative assets, along with the uplift of office and apartment prices in Seoul. However, the current officetel price indexes use small-size samples and, thus, there is a critique on their accuracy. They rely on valuation prices which lag the market trend and do not properly reflect the volatile nature of the property market, resulting in 'smoothing'. Therefore, the purpose of this paper is to create the officetel price index using transaction data. The data, provided by the Ministry of Land, Infrastructure and Transport from 2005 to 2020, includes sales prices and rental prices - Jeonsei and monthly rent (and their combinations). This study employed a repeat sales model for sales, jeonsei, and monthly rent indexes. It also contributes to improving conversion rates (between deposit and monthly rent) as a supplementary indicator. The main findings are as follows. First, the officetel price index and jeonsei index reached 132.5P and 163.9P, respectively, in Q4 2020 (1Q 2011=100.0P). However, the rent index was approximately below 100.0. Sales prices and jeonsei continued to rise due to high demand while monthly rent was largely unchanged due to vacancy risk. Second, the increase in the officetel sales price was lower than other housing types such as apartments and villas. Third, the employed approach has seen a potential to produce more reliable officetel price indexes reflecting high volatility compared to those indexes produced by other institutions, contributing to resolving 'smoothing'. As seen in the application in Seoul, this approach can enhance accuracy and, therefore, better assist market players to understand the market trend, which is much valuable under great uncertainties such as COVID-19 environments.
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