• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.393-403
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• 2021

Recently, there is becoming larger interest in the public practice centers equipped with advanced manufacturing equipment of industries that is difficult to have in all vocational high schools for strengthening practical education and technical education tailored to the Fourth Industrial Revolution in vocational high schools. In this study, using spatial optimization approaches, we explored the optimal location sets of the public practice centers of vocational high schools in Seoul for an illustration. For the proposed optimial location methods, P-median Problem (PMP) and Maximal Coverage Location (MCLP) were used because, when the public practice centers located in priority of large vocational high schools based on the number of students, it showed that the result is not minimizing the travel distance and maximizing the demand of the vocational high school students. This study found that the PMP can find the optimal location sets that minimize the travel distance of whole students. In addition, all students can be captured through locating five public practice centers by MCLP. It should be noted that the optimal locations of this study are limited in Seoul. However, the frame of this methodology applied in this study can be utilized to locate the public practice centers in other regions based on the spatial decision making.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.249-261
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• 2020

Coastal monitoring using multiple platforms/sensors is a very important tools for accurately understanding the changes in offshore marine environment and disaster with high temporal and spatial resolutions. However, integrated observation studies using multiple platforms and sensors are insufficient, and none of them have been evaluated for efficiency and limitation of convergence. In this study, we aimed to suggest an integrated observation method with multi-remote sensing platform and sensors, and to diagnose the utility and limitation. Integrated in situ surveys were conducted using Rhodamine WT fluorescent dye to simulate various marine disasters. In September 2019, the distribution and movement of RWT dye patches were detected using satellite (Kompsat-2/3/3A, Landsat-8 OLI, Sentinel-3 OLCI and GOCI), unmanned aircraft (Mavic 2 pro and Inspire 2), and manned aircraft platforms after injecting fluorescent dye into the waters of the South Sea-Yeosu Sea. The initial patch size of the RWT dye was 2,600 ㎡ and spread to 62,000 ㎡ about 138 minutes later. The RWT patches gradually moved southwestward from the point where they were first released,similar to the pattern of tidal current flowing southwest as the tides gradually decreased. Unmanned Aerial Vehicles (UAVs) image showed highest resolution in terms of spatial and time resolution, but the coverage area was the narrowest. In the case of satellite images, the coverage area was wide, but there were some limitations compared to other platforms in terms of operability due to the long cycle of revisiting. For Sentinel-3 OLCI and GOCI, the spectral resolution and signal-to-noise ratio (SNR) were the highest, but small fluorescent dye detection was limited in terms of spatial resolution. In the case of hyperspectral sensor mounted on manned aircraft, the spectral resolution was the highest, but this was also somewhat limited in terms of operability. From this simulation approach, multi-platform integrated observation was able to confirm that time,space and spectral resolution could be significantly improved. In the future, if this study results are linked to coastal numerical models, it will be possible to predict the transport and diffusion of contaminants, and it is expected that it can contribute to improving model accuracy by using them as input and verification data of the numerical models.

• Korean Journal of Environment and Ecology
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• v.32 no.6
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• pp.686-697
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• 2018

Due to the advance in remote sensing technology, it has become easier to more frequently obtain high resolution imagery to detect delicate changes in an extensive area, particularly including forest which is not readily sub-classified. Time-series analysis on high resolution images requires to collect extensive amount of ground truth data. In this study, the potential of land coverage mapas ground truth data was tested in classifying high-resolution imagery. The study site was Wonju-si at Gangwon-do, South Korea, having a mix of urban and natural areas. KOMPSAT-3A imagery taken on March 2015 and land coverage map published in 2017 were used as source data. Two pixel-based classification algorithms, Support Vector Machine (SVM) and Random Forest (RF), were selected for the analysis. Forest only classification was compared with that of the whole study area except wetland. Confusion matrixes from the classification presented that overall accuracies for both the targets were higher in RF algorithm than in SVM. While the overall accuracy in the forest only analysis by RF algorithm was higher by 18.3% than SVM, in the case of the whole region analysis, the difference was relatively smaller by 5.5%. For the SVM algorithm, adding the Majority analysis process indicated a marginal improvement of about 1% than the normal SVM analysis. It was found that the RF algorithm was more effective to identify the broad-leaved forest within the forest, but for the other classes the SVM algorithm was more effective. As the two pixel-based classification algorithms were tested here, it is expected that future classification will improve the overall accuracy and the reliability by introducing a time-series analysis and an object-based algorithm. It is considered that this approach will contribute to improving a large-scale land planning by providing an effective land classification method on higher spatial and temporal scales.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.12
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• pp.1292-1299
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• 2014

Weather radar systems can provide weather information of the ground, sea, and air in extensive spatial coverage in near real time. However, it becomes problematic when ground clutter signal exists around precipitation because strong signals of ground can cause a false precipitation report. A large percentage of land coverage of Korea consists of mountainous regions where ground clutter needs to be mitigated for more accurate prediction. Thus, it is considered necessary to introduce a new suitable ground clutter removal technique specifically adequate for Korea. In this paper, the C-Map(Clutter Map) method using raw radar signals is proposed for removing ground clutter using a terrain-adaptive clutter map. A clutter map is generated using raw radar signals(I/Q) of clear days, then it is subtracted from received radar signals in frequency domain. The proposed method is applied to the radar data acquired from Sobaeksan rain radar and the result shows that the clutter rejection ratio is about 91.17 %.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.1
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• pp.88-103
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• 2019

This paper aims to identify planting design for the renewal of Okgu Park, located in Siheung, Gyeonggi-do. I designate planting concept fit spatial functions and also suggest planting designs that are proper for a growth environment. The spatial functions of the research site are divided on the basis of the park facilities, its surroundings, and usage. To understand the planting concept, this paper looks into the distribution of plant species and the precise planting structure. To understand the planting concept and the current usage of shade space in the park, I examine the distribution of plant species and the precise planting structure. There are 48 kinds of plants, with Zoysia japonica area (28.84%), Prunus yedoensis (8.0%), Pinus thunbergii (6.73%) and Zelkova serrata (6.38%) taking up the majority. 27 places were chosen for researching the precise planting structure. The research shows that the average green coverage ratio is 38.14% and the average green capacity coefficient is $0.72m^3/m^2$. The growth defective rate of trees in the shade areas is estimated by averaging the classified growth conditions of individual trees per block of shade areas. Areas with an inferior environment for growth and low spatial usage in Okgu Park are selected as subjects for planting design. After comparing the spatial functions with planting concepts and analyzing the growth of plants, I identify $36,236m^2$ areas with inferior growth condition. I also examine structures and the surrounding areas to find areas that require urgent planting improvement, specifically identifying landscape space and shade space around the fountain and the buffer space nearby the North gate. I rearrange spatial functions in the selected areas to devise a planting design considering the existing vegetation, layer structure, and its usage. I set the planting concept and direction to improve the landscape of the selected areas through implementing a planting design so the park users can be satisfied with each space.

• Journal of the Korean association of regional geographers
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• v.15 no.3
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• pp.421-433
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• 2009

The impervious ratio was frequently employed as a fundamental attribute will be used as a proxy of the total environmental burden in the urban area since it may contribute as much or more on a cumulative basis to the overall environmental condition. This research proposes a comparative evaluation framework in a more objective and Quantitative way for an impervious ratio in the university campus, using the Google Earth. Two university campuses (Kyungpook National University: KNU, Hong Kong University: HKUJ were selected as survey objectives in order to evaluate the potential of Google Earth in monitoring impervious conditions in the campus. The 61cm resolution of Quickbird data combined with digital map realistically identified the major type of impervious surface such as road, building and parking lots in the study area by large scale spatial precision. The impervious zones with persistently high road density and parking space were specifically identified over the KNU campus while the HKC campus was intensively covered by tree, resulting in almost twice (31%). as compared to KNU (18.4%), The methods of characterizing impervious surface used in this study are easily replicable using data that are primarily publicly available, and therefore the collection of impervious coverage data via Google Earth is, therefore, proposed as a practical alternative.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11C
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• pp.673-681
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• 2011

In this paper, we design multiple antenna relay transmission schemes of low complexity to enhance the spatial diversity in orthogonal frequency division multiplexing (OFDM) systems. The relay scheme underlined, can provide space time block coding (STBC) of OFDM signals in the time domain without IFFT and FFT operations with much reduced complexity. In this paper, we modify the conventional low-complexity STBC-OFDM relaying scheme to be compatible to the existing OFDM systems. In addition, we extend the proposed scheme for multiple antenna relays and provide performance enhancement strategies according to the channel quality information available at the relay. The proposed scheme is shown to improve the diversity and thereby to reduce the outage probability and coded bit error rate. Therefore, the proposed scheme will be promising for service quality improvement or coverage extension based on OFDM like wireless LANs and maritime communications.

• Publications of The Korean Astronomical Society
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• v.27 no.4
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• pp.347-352
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• 2012

Understanding infrared (IR) luminosity is fundamental to understanding the cosmic star formation history and AGN evolution, since their most intense stages are often obscured by dust. Japanese infrared satellite, AKARI, provided unique data sets to probe this both at low and high redshifts. The AKARI performed an all sky survey in 6 IR bands (9, 18, 65, 90, 140, and $160{\mu}m$) with 3-10 times better sensitivity than IRAS, covering the crucial far-IR wavelengths across the peak of the dust emission. Combined with a better spatial resolution, AKARI can measure the total infrared luminosity ($L_{TIR}$) of individual galaxies much more precisely, and thus, the total infrared luminosity density of the local Universe. In the AKARI NEP deep field, we construct restframe $8{\mu}m$, $12{\mu}m$, and total infrared (TIR) luminosity functions (LFs) at 0.15 < z < 2.2 using 4,128 infrared sources. A continuous filter coverage in the mid-IR wavelength (2.4, 3.2, 4.1, 7, 9, 11, 15, 18, and $24{\mu}m$) by the AKARI satellite allows us to estimate restframe $8{\mu}m$ and $12{\mu}m$ luminosities without using a large extrapolation based on a SED fit, which was the largest uncertainty in previous work. By combining these two results, we reveal dust-hidden cosmic star formation history and AGN evolution from z = 0 to z = 2.2, all probed by the AKARI satellite.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1236-1238
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• 2003

The Earth's total magnetic field was extracted from on board TAM (Three Axis Magnetometer) observations of KOMPSAT-1 satellite between June 19th and 21st, 2000. In the pre-processing, the TAM's telemetry data were transformed from ECI (Earth Centered Inertial frame) to ECEF (Earth Centered Earth Fixed frame) and then to spherical coordination, and self-induced magnetic field by satellite bus itself were removed by using an on-orbit magnetometer data correction method. The 2-D wavenumber correlation filtering and quadrant-swapping method were applied to the pre-processed data in order to eliminate dynamic components and track-line noise, respectively. Then, the spherical harmonic coefficients are calculated from KOMPSAT-1 data. To test the validity of the TAM's geomagnetic field, Danish/NASA/French ${\phi}$rsted satellite's magnetic model and IGRF2000 model were used for statistical comparison. The correlation coefficient between ${\phi}$rsted and TAM is 0.97 and IGRF and TAM is 0.96. It was found that the data from on board magnetometer observations for attitude control of Earth-observing satellites can be used to determinate the Earth's total magnetic field and that they can be efficiently used to upgrade the global geomagnetic field coefficients, such as IGRF by providing new information at various altitudes with better temporal and spatial coverage.