• Journal of Korean Society on Water Environment
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• v.31 no.2
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• pp.120-133
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• 2015

Due to increasing impervious surfaces resulting from urbanization and industrialization which are directly linked to urban inundation and non-point pollutants runoff, there is a need to manage them systematically. A management over urban impervious surfaces calls for pervious/impervious maps, which enable viewing the distribution of impervious surfaces. Nevertheless, relevant data are absent as now. In this respect, despite the diversity of proposed methods, pilot implementation and accuracy verification have never been conducted. Therefore, this study is aimed to produce a pilot pervious/impervious map based on previously proposed methods and to elucidate its pros and cons with a view to proposing a method for producing a GIS-based optimal pervious/impervious map. Following previously proposed methods, a pervious/impervious map of Bupyeong-gu, Incheon was produced. Then, a method of producing optimal pervious/impervious maps applicable to urban areas was proposed through the comparison of pros and cons of relevant spatial data. As a result, the map had been confirmed 99.2% of classification accuracy. Based on the present findings, future studies should establish a standardized method for producing. Also, this method should be used to produce pervious/impervious maps of other regions so that it can be applied to managing impervious surfaces in major urban areas nationwide.

• Journal of Environmental Science International
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• v.15 no.8
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• pp.745-757
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• 2006

We focus on the improvement of accuracy of sea surface wind over complex coastal area doling the warm season. Local Analysis Prediction System (LAPS) was used to improve the initial values in Mesoscale Meteorological model (MM5). During the clear summer days with weak wind speed, sea surface wind simulated with LAPS was compared with the case without LAPS. The results of modeling with LAPS has a good agreement mesoscale circulation such as mountain and valley winds on land and in case of modeling without LAPS, wind speed overestimated over the sea in the daytime. And the results of simulation with LAPS indicated similar wind speed values to observational data over the sea under influence of data assimilation using BUOY, QuikSCAT, and AMEBAS. The present study suggests that MM5 modelling with LAPS showed more improved results than that of without LAPS to simulate sea surface wind over the complex coastal area.

• Korean Journal of Computational Design and Engineering
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• v.19 no.4
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• pp.347-355
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• 2014

IFC converters and viewers, applicable in the construction field, are being actively developed while, in the civil engineering field, IFC schemata are being developed. To prove the IFC schema grammatically, the existing ISO 10303 30s' pre-processors and post-processors may be used. However, to visually prove the IFC model, the existing commercial 3D modeling software should be converted into the IFC schema of civil engineering field, and a viewer is needed to view it. Thus, this study developed a IFC converter and viewer prototype system to apply BIM in the road field. To express the road line, LandXML was analyzed, and IFC suitable for expressing shapes in the road field was designed. Also, an IFC suitable for bridges with focus on representative bridge structures such as abuts, piers and decks was designed. Further, a converter was developed using AutoCAD's Civil3D and Revit's 3rdp party tools, and software was also developed designed to combine each converted IFC model into one IFC. In addition, a viewer designed to view IFC in the road field was developed to prove the converted IFC. Eight major verification and examination items were selected and used in testing the converted model, and it was confirmed that the viewer normally viewed the IFC schema in the road field. The proposed IFC converter is expected to be used as a visual IFC verification tool in the road field.

• Aerospace Engineering and Technology
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• v.10 no.2
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• pp.154-162
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• 2011

The KOrea Multi-Purpose Satellite-3 (KOMPSAT-3) provides 0.7 m Ground Sample Distance (GSD) panchromatic image and 2.8 m GSD multi-spectral image data for various applications. The KOMPSAT-3 system data will be applied in the field of earth observations, covering land, sea, coastal zones, and Geographic Information Systems (GIS). In order to keep the swath width of 15km at nadir view of KOMPSAT-3, CCD consist of approximately 24,020 pixels excluding 20 dark pixels at both sides and has overlap region. Because there are no CCD-line sensors with a pixel size of $7{\mu}m$, the field of view is separated into 2 parts and imaged on 2 detectors, each with 12,080 pixels. Therefore, 2 detectors have different geometric characteristic. This paper provides image simulation for geometric characteristics analysis of overlapping area of KOMPSAT-3 using KOMPSAT-2 image data.

• Journal of Navigation and Port Research
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• v.33 no.1
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• pp.35-41
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• 2009

A waypoint tracking algorithm(WTA) is designed for Unmanned Surface Vehicle(USV) in which water-jet system is installed for propulsion To control the heading of USV for waypoint tracking, the steering nozzle of water-jet need, to be controlled. Firstly, target heading is calculated by using the position information of waypoints input from the land control center. Secondly, the command for the steering nozzle of water-jet is calculated in real time by using the heading and the rate-of-turn( ROT) from magnetic compass, In this study, in order to consider the drift angle due to external disturbance such as wind and wave, the course of ground( COG) can be used instead of heading at higher speed than a certain value, To test the performance of newly-designed WTA, the tests were carried out in actual sea area near Gwang-an bridge of Busan. In this paper, the sea trial test results from WTA are analyzed and compared with those from manual control and those from commercial controller.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1286-1294
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• 2011

This paper reviews the future directions and perspectives on the soil environmental researches in the 21 century. Previously, the principal emphasis of soil environmental researches had put on the enhancement of food and fiber productions. Beside the basic function of soil, however, the societal needs on soil resources in the 21st century have demands for several environmental and social challenges, occurring regionally or globally. Typical global issues with which soil science should deal include food security with increasing agronomic production to meet the exploding world population growth, adaptation and mitigation of climate change, increase of the carbon sequestration, supply of the biomass and bioenergy, securing the water resource and quality, protection of environmental pollution, enhancing the biodiversity and ecosystem health, and developing the sustainable farming/cropping system that improve the use efficiency of water and agricultural resources. These challenges can be solved through the sustainable crop production intensification (SCPI) or plant welfare concept in which soil plays a key role in solving the abovementioned global issues. Through implementation of either concept, soil science can fulfill the goal of the modern agriculture which is the sustainable production of crops while maintaining or enhancing the ecosystem function, quality and health. Therefore, directions of the future soil environmental researches should lie on valuing soil as an ecosystem services, translating research across both temporal and spatial scales, sharing and using data already available for other purposes, incorporating existing and new technologies from other disciplines, collaborating across discipline, and translating soil research into information for stakeholders and end users. Through the outcomes of these approaches, soil can enhance the productivity from the same confined land, increase profitability, conserve natural resource, reduce the negative impact on environment, enhance human nutrition and health, and enhance natural capital and the flow of ecosystem services. Soil is the central dogma, final frontier and new engine for the era of sustainability development in the $21^{st}$ century and thus soil environmental researches should be carried according to this main theme.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.1
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• pp.53-61
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• 2021

The quantified analysis of damages to wastewater treatment plants by natural disasters is essential to maintain the stability of wastewater treatment systems. However, studies on the quantified analysis of natural disaster effects on wastewater treatment systems are very rare. In this study, a total disaster index (DI) was developed to quantify the various damages to wastewater treatment systems from natural disasters using two statistical methods (i.e., AHP: analytic hierarchy process and PCA: principal component analysis). Typhoons, heavy rain, and earthquakes are considered as three major natural disasters for the development of the DI. A total of 15 input variables from public open-source data (e.g., statistical yearbook of wastewater treatment system, meteorological data and financial status in local governments) were used for the development of a DI for 199 wastewater treatment plants in Korea. The total DI was calculated from the weighted sum of the disaster indices of the three natural disasters (i.e., TI for typhoon, RI for heavy rain, and EI for earthquake). The three disaster indices of each natural disaster were determined from four components, such as possibility of occurrence and expected damages. The relative weights of the four components to calculate the disaster indices (TI, RI and EI) for each of the three natural disasters were also determined from AHP. PCA was used to determine the relative weights of the input variables to calculate the four components. The relative weights of TI, RI and EI to calculate total DI were determined as 0.547, 0.306, and 0.147 respectively.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.73-82
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• 2022

Marine fisheries resources face major anthropogenic threat from unregulated fishing activities; thus require precise detection for protection through marine surveillance. Korea developed an efficient land-based small fishing vessel monitoring system using real-time V-Pass data. However, those data directly do not provide information on fishing activities, thus further efforts are necessary to differentiate their activity status. In Korea, especially in Busan, longlining is practiced by many small fishing vessels to catch several types of fishes that need to be identified for proper monitoring. Therefore, in this study we have improved the existing fishing status classification method by applying Hidden Markov Model (HMM) on V-Pass data in order to further classify their fishing status into three groups, viz. non-fishing, longlining and other types of fishing. Data from 206 fishing vessels at Busan on 05 February, 2021 were used for this purpose. Two tiered HMM was applied that first differentiates non-fishing status from the fishing status, and finally classifies that fishing status into longlining and other types of fishing. Data from 193 and 13 ships were used as training and test datasets, respectively. Using this model 90.45% accuracy in classifying into fishing and non-fishing status and 88.23% overall accuracy in classifying all into three types of fishing statuses were achieved. Thus, this method is recommended for monitoring the activities of small fishing vessels equipped with V-Pass, especially for detecting longlining.

• Journal of the Korean Society of Safety
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• v.37 no.3
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• pp.34-44
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• 2022

This study analyzed the smart construction safety cost included in safety management plans that are approved before construction. Specifically, it refers to the cost incurred in constructing and operating a safety management system using wireless communication and facilities. Based on the obtained statistical results, an activation policy for the inclusion of the smart construction safety cost in building safety management plans was proposed. The smart construction safety cost must be included in the safety management cost; notably, this is mandated by the Construction Technology Promotion Act. However, there are some problems with the inclusion of smart construction safety costs. To analyze the problems encountered when calculating the smart construction safety cost and including it in safety management plans, in this study, statistical analysis was performed using the data of 1,334 safety management plans received at the Construction Safety Management Integrated Information (CSI) from June to August 2021. The results show that only 50.7% of the safety management plans included the smart construction safety cost although the current law mandates 100% inclusion of these costs. Thus, it is apparent that the smart construction safety costs are only included in a low proportion of sites. In addition, the calculated smart construction safety costs were shown to have a small correlation with the construction cost; moreover, they appeared to be distributed at a constant cost level. In this context, it is believed that perfunctory cost calculations were performed at most sites since the effect of the construction cost on the smart construction safety cost was negligible. Therefore, it is necessary to improve the inclusion of smart construction safety costs by strengthening the authorization process of the approval institute of safety management plans. In addition, institutional support, such as guidelines that promote the calculation and inclusion of appropriate smart construction safety costs according to the characteristics of sites, are needed.

• Journal of Information Technology Services
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• v.21 no.3
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• pp.63-72
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• 2022

The extinction crisis of local cities, caused by a population density increase phenomenon in capital regions, directly causes the increase of vacant houses in local cities. According to population and housing census, Gunsan-si has continuously shown increasing trend of vacant houses during 2015 to 2019. In particular, since Gunsan-si is the city which suffers from doughnut effect and industrial decline, problems regrading to vacant house seems to exacerbate. This study aims to provide a foundation of a system which can predict and deal with the building that has high risk of becoming vacant house through implementing a data driven vacant house prediction machine learning model. Methodologically, this study analyzes three types of machine learning model by differing the data components. First model is trained based on building register, individual declared land value, house price and socioeconomic data and second model is trained with the same data as first model but with additional POI(Point of Interest) data. Finally, third model is trained with same data as the second model but with excluding water usage and electricity usage data. As a result, second model shows the best performance based on F1-score. Random Forest, Gradient Boosting Machine, XGBoost and LightGBM which are tree ensemble series, show the best performance as a whole. Additionally, the complexity of the model can be reduced through eliminating independent variables that have correlation coefficient between the variables and vacant house status lower than the 0.1 based on absolute value. Finally, this study suggests XGBoost and LightGBM based machine learning model, which can handle missing values, as final vacant house prediction model.