• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.217-223
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• 2014

With precise sensor position, attitude element, and imaging resolution, a simulated geospatial image can be generated. In this study, a satellite image is simulated using SPOT ortho-image and global elevation data, and the geometric similarity between original and simulated images is analyzed. Using a SPOT panchromatic image and high-density elevation data from a 1/5K digital topographic map data an ortho-image with 10-meter resolution was produced. The simulated image was then generated by exterior orientation parameters and global elevation data (SRTM1, GDEM2). Experimental results showed that (1) the agreement of the image simulation between pixel location from the SRTM1/GDEM2 and high-resolution elevation data is above 99% within one pixel; (2) SRTM1 is closer than GDEM2 to high-resolution elevation data; (3) the location of error occurrence is caused by the elevation difference of topographical objects between high-density elevation data generated from the Digital Terrain Model (DTM) and Digital Surface Model (DSM)-based global elevation data. Error occurrences were typically found at river boundaries, in urban areas, and in forests. In conclusion, this study showed that global elevation data are of practical use in generating simulated images with 10-meter resolution.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.453-462
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• 2008

The objective of this paper is to compare the prediction performances of different landslide hazard maps based on topographic data stemming from different sources of elevation. The geostatistical framework of kriging, which can properly integrate spatial data with different accuracy, is applied for generating more reliable elevation estimates from both sparse elevation spot heights and exhaustive ASTER-based elevation values. A case study from Boeun, Korea illustrates that the integration of elevation and slope maps derived from different data yielded different prediction performances for landslide hazard mapping. The landslide hazard map constructed by using the elevation and the associated slope maps based on geostatistical integration of spot heights and ASTER-based elevation resulted in the best prediction performance. Landslide hazard mapping using elevation and slope maps derived from the interpolation of only sparse spot heights showed the worst prediction performance.

• Journal of information and communication convergence engineering
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• v.7 no.1
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• pp.41-45
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• 2009

In mobile GIS environments, a client needs to receive the isogram data with a topographical map from a server, if the mobile client wants to display map with elevation information. Because the elevation data size is normally quite large, the client will suffer some problems to receive the elevation data from server. The main reason is a resource limitation of the mobile devices. To overcome these problems, this paper proposes new data structures and algorithms. They are designed for efficient transmission of contour data to a client. Because of the contour data are generated as a vector style from elevation information stored at a server, the proposed algorithms are focused to minimize the transmission data volume and time.

• Journal of IKEEE
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• v.13 no.2
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• pp.181-185
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• 2009

In this paper, we are concerned with a 3D line segment extraction method by area-based stereo matching technique. The main idea is based on line fitting of elevation data on 2D line coordinates of ortho-image. Elevation data and ortho-image can be obtained by well-known area-based stereo matching technique. In order to use elevation in line fitting, the elevation itself should be reliable. To measure the reliability of elevation, in this paper, we employ the concept of self-consistency. We test the effectiveness of the proposed method with a quantitative accuracy analysis using synthetic images generated from Avenches data set of Ascona aerial images. Experimental results indicate that our method generates 3D line segments almost 7.5 times more accurate than raw elevations obtained by area-based method.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.259-261
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• 2008

GIS-based spatial data integration tasks have used exhaustive thematic maps generated from sparsely sampled data or satellite-based exhaustive data. Due to a simplification of reality and error in mapping procedures, such spatial data are usually imperfect and of different accuracy. The objective of this study is to carry out a sensitivity analysis in connection with input topographic data for landslide hazard mapping. Two different types of elevation estimates, elevation spot heights and a DEM from ASTER stereo images are considered. The geostatistical framework of kriging is applied for generating more reliable elevation estimates from both sparse elevation spot heights and exhaustive ASTER-based elevation values. The effects of different accuracy arising from different terrain-related maps on the prediction performance of landslide hazard are illustrated from a case study of Boeun, Korea.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.441-448
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• 2011

Lately, digital restitution was became common using digital aerial photos. Therefore, we can obtain three-dimensional data. As a plotting-maker is checked by naked eye, plotting original data is very useful for making reliable three-dimensional data including contour and elevation point layers. In this study, we want to make precise and accurate digital elevation model using plotting original data. Contour and elevation point layers was extracted in digital map and break line was extracted in plotting original data. And then, compared both of results. For comparison, we selected slight slope and complex topography area like a residence area, mountain and agricultural land. We extracted break line deleting layer until obtaining ideal digital elevation model. As the results, We could extract contour, elevation points, eight road and two boundary layers using break lines. And We could obtain precise elevation model. Editing break lines, the distortion of digital elevation model could be minimized in the complex and sharp slope area.

• International Journal of Advanced Culture Technology
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• v.6 no.3
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• pp.211-215
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• 2018

Ventilator-associated pneumonia (VAP) is a lung infection that develops in patients receiving mechanical ventilation. VAP contributes to about 50% of hospital-acquired pneumonia in ICU settings. One of the recommendation of the Institute of for Healthcare Improvement ventilator bundle is HOB elevation. HOB elevation affects shearing forces and makes higher risk for pressure injury development. Pressure injury (PI) is localized damage to the skin over a bony prominence. PI prevention guidelines recommend that HOB positioning should be lower to reduce risk for PI development which contradicts VAP prevention guidelines for the HOB between 30 and 45 degrees for ICU patients. This presents a care dilemma and tension. The purpose of this study was to perform a secondary data analysis using cumulative electronic health record data in order to determine the association of HOB elevation with VAP and PI in ICU patients. A secondary data analysis was conducted to determine whether HOB elevation is associated with VAP and PI. HOB elevation was not likely to be associated with VAP prevention whereas it was likely to be related to PI development. This is somewhat contrary to popular data and publications. Prospective cohort study is desired to inform us in an evidence-based fashion what actually is optimal HOB elevation for ventilated patients in ICU settings.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.595-600
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• 2013

In order to spatially interpolate the near-surface temperature (Ta) values, satellite and reanalysis methods were used from previous studies. Accuracy of reanalysis Ta was generally better than that of satellite-based Ta, but spatial resolution of reanalysis Ta was large to use at local scale studies. Our purpose is to evaluate accuracy of reanalysis Ta and satellite-based Ta according to elevation from April 2011 to March 2012 in Northeast Asia that includes various topographic features. In this study, we used reanalysis data that is ERA-Interim produced by European Centre for Medium-Range Weather Forecasts (ECMWF), and estimated satellite-based Ta using Digital Elevation Meter (DEM), Normalized Difference Vegetation Index (NDVI), difference between brightness temperature of $11{\mu}m$ and $12{\mu}m$, and Land Surface Temperature (LST) data. The DEM data was used as auxiliary data, and observed Ta at 470 meteorological stations was used in order to evaluate accuracy. We confirmed that the accuracy of satellite-based Ta was less accurate than that of ERA-Interim Ta for total data. Results of analyzing according to elevation that was divided nine cases, ERA-Interim Ta showed higher accurate than satellite-based Ta at the low elevation (less than 500 m). However, satellite-based Ta was more accurate than ERA-Interim Ta at the higher elevation from 500 to 3500 m. Also, the width of the upper and lower quartile appeared largely from 2500 to 3500 m. It is clear from these results that ERA-Interim Ta do not consider elevation because of large spatial resolution. Therefore, satellite-based Ta was more effective than ERA-Interim Ta in the regions that is range from 500 m to 3500 m, and satellite-based Ta was recommended at a region of above 2500 m.

• KIEAE Journal
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• v.8 no.5
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• pp.43-48
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• 2008

This study is about offering quantitatively analytic frame of streetscape, and also about making a way to be standardized and adapt changing landscape. This allows us to manage a form of elevation map after the application to GIS. The form of elevation map is a visible and vertical arrangement method of data recognizable while walking or driving. Applying measurable traits enables us to make a quantitative control over each element of which streetscape consists. After all, it would play a great roll in organizing and maintaining fine streetscape of each city. As the basic ways to make the elevation map, this study proposes the methods of providing quantitative analytic frame of streetscape after applying elevation data, Raster Data and Vector Data, which were investigated on the basis of GIS. In addition, as a simulation for increasing reality, certain streets, where the streetscape is very important, were chosen so that they enable us to utilize quantitatively analytic data of streetscape with analyzing the +degree of opening ratio in the boundary of D/H=2, comparing between wall area and windowpane area, comparing between facade area and sign board area, and calculating both area and ratio which are applied to ecospace.

• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.471-483
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• 2020

Flood prediction is an important issue to prevent damages by flood inundation caused by increasing high-intensity rainfall with climate change. In recent years, machine learning algorithms have been receiving attention in many scientific fields including hydrology, water resources, natural hazards, etc. The performance of a machine learning algorithm was investigated to predict the water elevation of a river in this study. The aim of this study was to develop a new method for securing a large enough lead time for flood defenses by predicting river water elevation using the a long- short-term memory (LSTM) technique. The water elevation data at the Oisong gauging station were selected to evaluate its applicability. The test data were the water elevation data measured by K-water from 15 February 2013 to 26 August 2018, approximately 5 years 6 months, at 1 hour intervals. To investigate the predictability of the data in terms of the data characteristics and the lead time of the prediction data, the data were divided into the same interval data (group-A) and time average data (group-B) set. Next, the predictability was evaluated by constructing a total of 36 cases. Based on the results, group-A had a more stable water elevation prediction skill compared to group-B with a lead time from 1 to 6 h. Thus, the LSTM technique using only measured water elevation data can be used for securing the appropriate lead time for flood defense in a river.