• Journal of The Korea Institute of Healthcare Architecture
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• v.26 no.1
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• pp.51-62
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• 2020

Purpose: The Intensive Care Unit (ICU) is an important inpatient care area where critical patients are treated intensively with advanced medical technology. The level of care of ICU and the modernization of related facilities is an important indicator of health care quality. At the present time, when the Regional public hospitals are frequently expanding, the rational planning of the ICU has become an important part of the medical institutions treating the ICU. The purpose of this study is to present basic data with net area which can be used in the architectural planning of the ICU. Methods: The investigation and analysis of the ICUs were conducted on 26 medical facilities, based on theoretical analysis through relevant guidelines, articles, and documents, and on the basis of the actual space composition and net area analysis through the architectural drawings. Results: This study provides basic data such as zone division, spatial composition, relationship between main activities and zones, composition of facilities in the zone and area ratio within each zone. Implications: The results of this paper are expected to be effective reference materials for future research for rational spatial organization and efficient operation of the Intensive Care Unit in regional public hospitals.

• Journal of Korean Association for Spatial Structures
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• v.23 no.4
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• pp.27-34
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• 2023

In this study, the seismic response characteristics of the three analysis model with or without TMD were investigated to find out the effective dome shape. The three analysis models are rib type, lattice type and geodesic type dome structure composed of space frame. The maximum vertical and horizontal displacements were evaluated at 1/4 point of the span by applying the resonance harmonic load and historical earthquake loads (El Centro, Kobe, Northridge earthquakes). The study of the effective TMD installation position for the dome structure shows that seismic response control was effective when eight TMDs were installed in all types of analysis model. The investigation of the efficiency of TMD according to dome shape presents that lattice dome and geodesic dome show excellent control performance, while rib dome shows different control performance depending on the historical seismic loads. Therefore, lattice and geodesic types are desirable for seismic response reduction using TMD compared to rib type.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.4
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• pp.165-175
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• 2005

Geographic Information System(GIS) is useful to preserve cultural heritage and land use management using both spatial information management technique and spatial analysis function in cultural heritage management. The purpose of this study is to build a database of pottery and kiln sites in South Korea, to analyze site locations and finally to make prediction model. The locations of 1,200 sites are put into GIS database. Such factor elevation, slope angle, aspect, horizontal/vertical distance from the nearest water are analyzed. Each factor was statistically analyzed on GIS and represented to rank 1-5. Pottery/kiln can be predicted by the spatial analysis function in overlay methods. As a result of this study, preliminary application of prediction model shows that the high potential area is between the slope and alluvial plain. Field survey in the Sungbuk-dong in Daejeon city supports the preliminary result. More data can make improve efficient prediction model in unknown areas.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.343-346
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• 2019

This letter describes a development of satellite-based forest withering index for detection of fire burn area and its application to the Goseong-Sokcho and Gangneung-Donghae wildfires in April 4, 2019. Withered forest has very different spectral characteristics from healthy forest. In particular, a false color composite of R-NIR-G represents such difference very clearly. Using Sentinel-2 images with the forest withering index, we derived the area burned by the wildfires: approximately 701.16 ha for Goseong-Sokcho and approximately 710.60 ha for Gangneung-Donghae, although official record will be announced by the Korean government later.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1231-1244
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• 2022

The frequency of exposure of field crops to stress situations is increasing due to abnormal weather conditions. In South Korea, large-scale diseases in representative paddy rice cultivation area were happened. There are limits to field investigation on the crop damage due to large-scale. Satellite-based remote sensing techniques are useful for monitoring crops in cities and counties, but the sensitivity of vegetation index measured from satellite under abnormal growth of crop should be evaluated. The goal is to evaluate satellite-based normalized difference vegetation index (NDVI) retrieved from different spatial scales using drone imagery. In this study, Sentinel-2 and Landsat-8 satellites were used and they have spatial resolution of 10 and 30 m. Drone-based NDVI, which was resampled to the scale of satellite data, had correlation of 0.867-0.940 with Sentinel-2 NDVI and of 0.813-0.934 with Landsat-8 NDVI. When the effects of bias were minimized, Sentinel-2 NDVI had a normalized root mean square error of 0.2 to 2.8% less than that of the drone NDVI compared to Landsat-8 NDVI. In addition, Sentinel-2 NDVI had the constant error values regardless of diseases damage. On the other hand, Landsat-8 NDVI had different error values depending on degree of diseases. Considering the large error at the boundary of agricultural field, high spatial resolution data is more effective in monitoring crops.

• Journal of Korean Society of Rural Planning
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• v.27 no.4
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• pp.55-70
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• 2021

In this study, in the field of remote sensing, where the scope of application is rapidly expanding to fields such as land monitoring, disaster prediction, facility safety inspection, and maintenance of cultural properties, monitoring of rural space and surrounding environment using UAV is utilized. It was carried out to verify the possibility, and the following main results were derived. First, the aerial image taken with an unmanned aerial vehicle had a much higher image size and spatial resolution than the aerial image provided by the National Geographic Information Service. It was suitable for analysis due to its high accuracy. Second, the more the number of photographed photos and the more complex the terrain features, the more the point cloud included in the aerial image taken with the UAV was extracted. As the amount of point cloud increases, accurate 3D mapping is possible, For accurate 3D mapping, it is judged that a point cloud acquisition method for difficult-to-photograph parts in the air is required. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. Fourth, the digital elevation model(DEM) produced with aerial image taken with an UAV can visually express the altitude and shape of the topography of the study site, so it can be used as data to predict the effects of topographical changes due to changes in rural space. Therefore, it is possible to utilize various results using the data included in the aerial image taken by the UAV. In this study, the superiority of images acquired by UAV was verified by comparison with existing images, and the effect of 3D mapping on rural space monitoring was visually analyzed. If various types of spatial data such as GIS analysis and topographic map production are collected and utilized using data that can be acquired by unmanned aerial vehicles, it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.420-436
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• 2007

The choice of an effective indexing method is crucial to guarantee the performance of the spatial join operator which is heavily used in geographical information systems. The $R^*$-tree based method is renowned as one of the most representative indexing methods. In this paper, we propose an efficient spatial join technique based on the DOT(Double Transformation) index, and compare it with the spatial Join technique based on the $R^*$-tree index. The DOT index transforms the MBR of an spatial object into a single numeric value using a space filling curve, and builds the $B^+$-tree from a set of numeric values transformed as such. The DOT index is possible to be employed as a primary index for spatial objects. The proposed spatial join technique exploits the regularities in the moving patterns of space filling curves to divide a query region into a set of maximal sub-regions within which space filling curves traverse without interruption. Such division reduces the number of spatial transformations required to perform the spatial join and thus improves the performance of join processing. The experiments with the data sets of various distributions and sizes revealed that the proposed join technique is up to three times faster than the spatial join method based on the $R^*$-tree index.

• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.889-902
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• 2020

This study was performed in Seolmacheon basin to evaluate the adequacy of GLDAS (Global Land Data Assimilation System) and GLEAM (Global Land Evaporation Amsterdam Model) evapotranspiration data. The verification data necessary for the evaluation of adequacy were calculated after processing the latent heat flux data produced in the Seolmacheon basin with the Koflux program. In order to gap-fill the empty period, alternative evapotranspiration was calculated in three ways: FAO-PM (Food and Agriculture Organization-Penman Monteith), MDV (Mean Diurnal Variation) and Kalman Filter. This study selected Kalman Filter method as the data gap-filling method because it showed the best Bias and RMSE among the three methods. The amount of GLDAS spatial evapotranspiration was calculated as Noah (version 2.1) with a time interval of 3 hours and a spatial resolution of 0.25°. The amount of GLEAM spatial evapotranspiration was calculated using GLEAM (version 3.1a). This study evaluated the spatial evapotranspiration of GLDAS and GLEAM as the evapotranspiration based on eddy covariance. As a result of evaluation, GLDAS spatial evapotranspiration showed better results than GLEAM. Accordingly, in this study, the GLDAS method was proposed as a method for calculating the amount of spatial evapotranspiration in the Seolmacheon basin.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.57-70
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• 2018

The advancement and the spread of information and communication technology (ICT) changes the way we live and act. Computer and ICT devices become smaller and invisible, and they are now virtually everywhere in the world. Many socio-economic activities are now subject to the use of computer and ICT devices although we don't really recognize it. Various socio economic activities supported by digital devices leave digital records, and a myriad of these records becomes what we call'big data'. Big data differ from conventional data we have collected and managed in that it holds more detailed information of socio-economic activities. Thus, they offer not only new insight for our society and but also new opportunity for policy analysis. However, the use of big data requires development of new methods and tools as well as consideration of institutional issues such as privacy. The goals of this research are twofold. Firstly, it aims to understand the opportunities and challenges of using big data for planning support. Big data indeed is a big sum of microscopic and dynamic data, and this challenges conventional analytical methods and planning support tools. Secondly, it seeks to suggest ways of visualizing such spatial big data for planning support. In this regards, this study attempts to develop a dynamic visualization model and conducts an experimental case study with mobile phone big data for the Jeju island. Since the off-the-shelf commercial software for the analysis of spatial big data is not yet commonly available, the roles of open source software and computer programming are important. This research presents a pilot model of dynamic visualization for spatial big data, as well as results from them. Then, the study concludes with future studies and implications to promote the use of spatial big data in urban planning field.

• Journal of Wetlands Research
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• v.17 no.4
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• pp.370-379
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• 2015

In recent, the natural disaster like localized heavy rainfall due to the climate change is increasing. Therefore, it is important issue that the precise observation of rainfall and accurate spatial distribution of the rainfall for fast recovery of damaged region. Thus, researches on the use of the radar rainfall data have been performed. But there is a limitation in the estimation of spatial distribution of rainfall using rain gauge. Accordingly, this study uses the Kriging method which is a spatial interpolation method, to measure the rainfall field in Namgang river dam basin. The purpose of this study is to apply KED(Kriging with External Drift) with OK(Ordinary Kriging) and CK(Co-Kriging), generally used in Korea, to estimate rainfall field and compare each method for evaluate the applicability of each method. As a result of the quantitative assessment, the OK method using the raingauge only has 0.978 of correlation coefficient, 0.915 of slope best-fit line, and 0.957 of $R^2$ and shows an excellent result that MAE, RMSE, MSSE, and MRE are the closest to zero. Then KED and CK are in order of their good results. But the quantitative assessment alone has limitations in the evaluation of the methods for the precise estimation of the spatial distribution of rainfall. Thus, it is considered that there is a need to application of more sophisticated methods which can quantify the spatial distribution and this can be used to compare the similarity of rainfall field.