• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.183-191
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• 2020

In this study, in order to obtain basic data on the development of a new hanbok skirt pattern for developing a customizing system, a new hanbok brand skirt pattern was compared and analyzed. After analyzing the patterns of six new hanbok brands, virtual simulation was performed to evaluate the appearance, clothing pressure, and airgap. As a result of analyzing the waist skirt patterns of commercial new hanbok brands A, B, C, D, E, and F, it was found that they were produced in different dimensions despite the free size skirt of the same design. The pattern of new hanbok waist skirt was composed of a flat pattern like the traditional hanbok. As a result of appearance evaluation, it was evaluated that there were significant differences between the patterns of the six brands in all the evaluation items on the front, side, and back. In the appearance evaluation, it was evaluated that the waist skirt of the B brand was excellent. As a result of examining the color distribution and airgap, it was evaluated that the airgap was large in most parts due to the characteristics of the waist skirt worn around the waist, and the garment pressure was low. In this paper, we propose a basic data for standardizing dimensions and patterns according to activation New Hanbok. It is thought that a unified pattern development based on the B brand pattern should be made.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.2027-2034
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• 2021

Using multi-temporal KOMPSAT-3/3A high-resolution satellite images, the Normalized Difference Vegetation Index (NDVI) for the area around the Fukushima daiichi nuclear power plant was determined, and the pattern of vegetation changes was analyzed. To calculate the NDVI, surface reflectance from the KOMPSAT-3/3A satellite image was used. Satellite images from four years were used, and the zones where the images overlap was designated as the area of interest (AOI) for the study, and by setting a profile passing through highly vegetated area as a data analysis method, the changes by year were examined. In addition, random points were extracted within the AOI and displayed as a box plot to quantitatively indicate change of NDVI distribution pattern. The main results of this study showed that the NDVI in 2014 was low within AOI in the vicinity of the nuclear power plant, but vegetated area continued to expand until 2021. These results were also confirmed in the change monitoring results shown in a profile or box plot. In disaster areas where access is restricted, such as the Fukushima nuclear power plant area, where it is difficult to collect field data, obtaining land cover classification products with high accuracy using satellite images is challenging, so it is appropriate to analyze them using primary outputs such as vegetation indices obtained from high-resolution satellite imagery. It is necessary to establish an international cooperation system for jointly utilizing satellite images. Meanwhile, to periodically monitor environmental changes in neighboring countries that may affect the Korean peninsula, it is necessary to establish utilization models and systems using high-resolution satellite images.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.667-673
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• 2021

Purpose: The aim of this study is to analyze the trend for the dispatch of the 119 rescue teams to remove the beehive according to the distribution of temperature and time in Busan metropolitan city for 5 years from 2015. Method: From January 2015 to December 2019, 11 fire stations in Busan were dispatched and the source data of rescue and emergency activities were collected. The number of beehive removal dispatches was determined by the Busan Metropolitan Fire Station's jurisdiction over the past five years, and the temperature meteorological factors and honeycomb removal dispatches were analyzed in frequency and percentage. Result: The frequency of dispatch began to increase at an monthly average temperature of more than 20℃ and was higher at 23℃ to 29℃ than other temperature range. The highest frequency of dispatch was 7,900 cases in 2017. In particular, we found that the start timing of the honeycomb removal is getting faster as the year goes by. Gijang-gun had the largest frequency of dispatch, and Haeundae-gu, Geumjeong-gu, and Nam-gu were found to have a higher that. Conclusion: We found that the start timing of the honeycomb removal is getting faster as the year goes by and temperature changes. The results of this study are considered to be useful in future studies of wasps in urban areas.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1215-1227
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• 2021

Surface reflectance, as a product of the absolute atmospheric correction process of low-orbit satellite imagery, is the basic data required for accurate vegetation analysis. The Commission on Earth Observation Satellite (CEOS) has conducted research and guidance to produce analysis-ready data (ARD) on surface reflectance products for immediate use by users. However, this trend is still in the early stages of research dealing with ARD for high-resolution multispectral images such as KOMPSAT-3A and CAS-500, as it targets medium- to low-resolution satellite images. This study first summarizes the types of distribution of ARD data according to existing cases. The link between Open Data Cube (ODC), the cloud-based satellite image application platforms, and ARD data was also explained. As a result, we present practical ARD deployment steps for high-resolution satellite images and several types of application models in the conceptual level for high-resolution satellite images deployed in ODC and cloud environments. In addition, data pricing policies, accuracy quality issue, platform applicability, cloud environment issues, and international cooperation regarding the proposed implementation and application model were discussed. International organizations related to Earth observation satellites, such as Group on Earth Observations (GEO) and Committee on Earth Observation Satellites (CEOS), are continuing to develop system technologies and standards for the spread of ARD and ODC, and these achievements are expanding to the private sector. Therefore, a satellite-holder country looking for worldwide markets for satellite images must develop a strategy to respond to this international trend.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.58-72
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• 2021

In July 2021, UNCTAD classified Korea as a developed country. After the Korean War in the 1950s, economic development was promoted despite difficult conditions, resulting in epoch-making national growth. However, in order to respond to the rapidly changing global economy, it is necessary to continuously study the domestic industrial ecosystem and prepare strategies for continuous change and growth. This study analyzed the industrial ecosystem of the automobile industry where it is possible to obtain transaction data between companies by applying complexity spatial network analysis. For data, 295 corporate data(node data) and 607 transaction data (link data) were used. As a result of checking the spatial distribution by geocoding the address of the company, the automobile industry-related companies were concentrated in the Seoul metropolitan area and the Southeastern(Dongnam) region. The node importance was measured through degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality, and the network structure was confirmed by identifying density, distance, community detection, and assortativity and disassortivity. As a result, among the automakers, Hyundai Motor, Kia Motors, and GM Korea were included in the top 15 in 4 indicators of node centrality. In terms of company location, companies located in the Seoul metropolitan area were included in the top 15. In terms of company size, most of the large companies with more than 1,000 employees were included in the top 15 for degree centrality and betweenness centrality. Regarding closeness centrality and eigenvector centrality, most of the companies with 500 or less employees were included in the top 15, except for automakers. In the structure of the network, the density was 0.01390522 and the average distance was 3.422481. As a result of community detection using the fast greedy algorithm, 11 communities were finally derived.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1405-1423
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• 2021

Precipitation is one of the main factors that affect water and energy cycles, and its estimation plays a very important role in securing water resources and timely responding to water disasters. Satellite-based quantitative precipitation estimation (QPE) has the advantage of covering large areas at high spatiotemporal resolution. In this study, machine learning-based rainfall intensity models were developed using Himawari-8 Advanced Himawari Imager (AHI) water vapor channel (6.7 ㎛), infrared channel (10.8 ㎛), and weather radar Column Max (CMAX) composite data based on random forest (RF). The target variables were weather radar reflectivity (dBZ) and rainfall intensity (mm/hr) converted by the Z-R relationship. The results showed that the model which learned CMAX reflectivity produced the Critical Success Index (CSI) of 0.34 and the Mean-Absolute-Error (MAE) of 4.82 mm/hr. When compared to the GeoKompsat-2 and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) rainfall intensity products, the accuracies improved by 21.73% and 10.81% for CSI, and 31.33% and 23.49% for MAE, respectively. The spatial distribution of the estimated rainfall intensity was much more similar to the radar data than the existing products.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.223-233
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• 2021

Systematic and continuous monitoring and management of the energy consumption of buildings are important for estimating building energy efficiency, and ultimately aim to cope with climate change and establish effective policies for environment, and energy supply and demand policies. Globally, buildings consume 36% of total energy and account for 39% of carbon dioxide emissions. The purpose of this study is to generate three-dimensional thermo-spatial building models with photogrammetric technique using drone TIR (Thermal Infrared) images to measure the temperature emitted from a building, that is essential for the building energy rating system. The aerial triangulation was performed with both optical and TIR images taken from the sensor mounted on the drone, and the accuracy of the models was analyzed. In addition, the thermo-spatial models of temperature distribution of the buildings in three-dimension were visualized. Although shape of the objects 3D building modeling is relatively inaccurate as the spatial and radiometric resolution of the TIR images are lower than that of optical images, TIR imagery could be used effectively to measure the thermal energy of the buildings based on spatial information. This paper could be meaningful to present extension of photogrammetry to various application. The energy consumption could be quantitatively estimated using the temperature emitted from the individual buildings that eventually would be uses as essential information for building energy efficiency rating system.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1837-1847
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• 2021

This study investigated wind corridors for the entire Suwon-city area using a geographic information system and a computational fluid dynamics model. We conducted numerical simulations for 16 inflow wind directions using the average wind speeds measured at the Suwon automated synoptic observation system (ASOS) for recent ten years. We analyzed the westerly (dominant wind direction) and easterly cases (not dominant but strong wind speed) in detail and investigated the characteristics of a wind speed distribution averaged using the frequencies of 16 wind directions as weighting factors. The characteristics of the wind corridors in Suwon city can be summarized as; (1) In the northern part of Suwon, complicated flows were formed by the high mountainous terrain, and strong (weak) winds and updrafts (downdrafts) were simulated on the windward (leeward) mountain slope. (2) On the leeward mountain slope, a wind corridor was formed along a valley, and relatively strong airflow flowed into the residential area. (3) The strong winds were simulated in a wide and flat area in the west and south part of Suwon city. (4) Due to the friction and flow blocking by buildings, wind speeds decreased, and airflows became complicated in the downtown area. (5) Wind corridors in residential areas were formed along wide roads and areas with few obstacles, such as rivers, lakes, and reservoirs.

• Journal of Korean Library and Information Science Society
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• v.50 no.1
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• pp.61-84
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• 2019

This study is an analysis of Mengshan heshang analects. Mengshan heshang lived in Song(?) and Yuan(?) Dynasty and he was a Buddhist monk of Linji Chan(???). His works handed on Buddhist monks of Goryeo in the late Goryeo Dynasty. And he influenced Buddism in the early Joseon Dynasty. In Joseon Dynasty Mengshan heshang Sermons abstract was confirmed existence of 39 editions and Mengshan heshang Liudao Pushuo was confirmed existence of 24 editions. All 63 editions show that Sermons abstract and Liudao Pushuo are his representitive analects. All editions were printed in early Joseon Dynasty. At that time Mengshan heshang analects was distributed in Joseon Dynasty. Mengshan heshang analects was distributed in all over the nation as well as in Royal Family of Joseon. Also Mengshan heshang analects was published many times in the Mt. Jiri area. The names of almost engravers found on the publications of many temples. Some engravers actively participated in publishing Buddhist scriptures in particular area. His ideas were received in the late Goryeo Dynasty and the early Joseon Dynasty actively and his many works appears like this.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.1-14
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• 2019

In rural areas, composting is a source of non-point pollutants. However, as the quantitative distribution and loading have not been estimated, it is difficult to determine the effect of composting on stream water quality. In this study, composting datum acquired by unmanned aerial vehicle(UAV) was verified by using terrestrial LiDAR, and the management status and load change of the composting was investigated by UAV with manual control flight, thereby obtaining the basic data to determine the effect on the water system. As a result of the comparative accuracy assessment based on terrestrial LiDAR, the difference in the digital surface model(DSM) was within 0.21m and the accuracy of the volume was 93.24%. We expect that the accuracy is sufficient to calculate and utilize the composting load acquired by UAV. Thus, the management status of composting can be investigated by UAV. As the total load change of composting were determined to be $1,172.16m^3$, $1,461.66m^3$, and $1,350.53m^3$, respectively, the load change of composting could be confirmed. We expect that the results of this study can contribute to efficient management of non-point source pollution by UAV.