• Korean Journal of Remote Sensing
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• v.12 no.1
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• pp.1-16
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• 1996

Korea Aerospace Research Institute(KARI) is developing a Korea Multi-Purpose Satellite I(KOMPSAT-I) which accommodates Electro-Optical Camera(EOC), Ocean Color Imager(OCI), Space Physics Sensor(SPS) for cartography, ocean color monitoring, and space environment monitoring respectively. The satellite has the weight of about 500 kg and is operated on the sun synchronized orbit with the altitude of 685km, the orbit period of 98 minutes, and the orbit revisit time of 28days. The satellite will be launched in the third quarter of 1999 and its lifetime is more than 3 years. EOC has cartography mission to provide images for the production of scale maps, including digital elevation models, of Korea from a remote earth view in the KOMPSAT orbit. EOC collects panchromatic imagery with the ground sample distance(GSD) of 6.6m and the swath width of 15km at nadir through the visible spectral band of 510-730 nm. EOC scans the ground track of 800km per orbit by push-broom and body pointed method. OCI mission is worldwide ocean color monitoring for the study of biological oceanography. OCI is a multispectral imager generating 6 color ocean images with and <1km GSD by whisk-broom scanning method. OCI is designed to provide on-orbit spectral band selectability in the spectral range from 400nm to 900nm. The color images are collected through 6 primary spectral bands centered at 443, 490, 510, 555, 670, 865nm or 6 spectral bands selected in the spectral range via ground commands after launch. SPS consists of High Energy Particle Detector(HEPD) and Ionosphere Measurement Sensor(IMS). HEPD has mission to characterize the low altitude high energy particle environment and to study the effects of radiation environment on microelectronics. IMS measures densities and temperature of electrons in the ionosphere and monitors the ionospheric irregularities in KOMPSAT orbit.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.132-144
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• 2018

3D Geo-spatial information models have been widely used in the field of Civil Engineering, Medical, Computer Graphics, Urban Management and many other. Especially, in surveying and geo-spatial field, the demand for high quality 3D geospatial information and indoor spatial information is so highly increasing. However, it is so difficult to provide a low-cost and high efficiency service to the field which demand the highest quality of 3D model, because pre-constructed spatial data are composed of different formats and storage structures according to the application purpose of each institutes. In fact, the techniques to construct a high applicable 3D geo-spatial model is very expensive to collect and analyze geo-spatial data, but most demanders of 3D geo-spatial model never want to pay the high-cost to that. This study, therefore, suggest the effective way to construct 3D geo-spatial model with low-cost of construction. In general, the effective way to reduce the cost of constructing 3D geo-spatial model as presented in previous studies is to combine the raw data obtained from point cloud observatory and UAV imagery, however this method has some limitation of usage from difficulties to approve the use of raw data because of those have been managed separately by various institutes. To solve this problem, we developed the linking & management system for unifying a high-Resolution raw geo-spatial data based on the point cloud DB and apply this system to extract the basic database from 3D geo-spatial mode for the road database registration. As a result of this study, it can be provided six contents of main entries for road registration by applying the developed system based on the point cloud DB.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.497-502
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• 2018

An analog to digital converter(: ADC) has been designed to extract video signals of marine X-band radar and convert to digital signals in order to produce rainfall information. X-band weather radars are suitable for high temporal-spatial resolution observations of rainfall over local ranges but they are very expensive and require professional management. The marine radars with 10-2 cost facilitate data collection and management as well as economic benefits. To validate the usefulness of the developed ADC, comparative observations were made with weather radar for short term precipitation cases. The rainfall distribution of marine radar observations are consistent with that of weather radar within a radius of 15 km. This demonstrates the usability of marine radar for rainfall observations.

• Spatial Information Research
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• v.6 no.2
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• pp.233-245
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• 1998

This study focused on developing a comprehensive strategy to revise 1:1,000 digital topographic maps for Seoul metropolitan area in terms of both organizational and technical aspects. First of all, we analyze the elements of' the revision strategy in the organization domain and produce four alternatives. Of these alternatives, we suggest a best alternative which appears to be practically sound. Secondly, we review four possible map updating methodologies, paper map digitization, a partial topographic map revision method, a method utilizing scanned aerial photographs, and a method using digital orthophotos. Through a detailed technical analysis and cost analysis of each method, we suggest a reasonable map updating method. Finally, we provide a guideline for distributing 1:1,000 digital topographic maps based on the digital map distribution policy National Geography Institute.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.41-50
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• 2008

Recent progress in state-of-the-art geospatial information technologies such as digital mapping, LiDAR(Light Detection And Ranging), and high-resolution satellite imagery provides various data sources fer Digital Elevation Model(DEM). DEMs are major source to extract elements of the hydrological terrain property that are necessary for efficient watershed management. Especially, watersheds extracted from DEM are important geospatial database to identify physical boundaries that are utilized in water resource management plan including water environmental survey, pollutant investigation, polluted/wasteload/pollution load allocation estimation, and water quality modeling. Most of the previous studies related with watershed extraction using DEM are mainly focused on the hydrological elements analysis and preprocessing without considering grid size of the DEMs. This study aims to analyze accuracy of the watersheds extracted from DEMs with various grid sizes generated by LiDAR data and digital map, and appropriate preprocessing methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.451-456
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• 2018

UAVs (Unmanned Aerial Vehicles) are widely used for maintenance and monitoring of facilities. It is necessary to acquire a high-resolution image for evaluating the appearance state of the facility in safety inspection. In addition, it is essential to acquire the video data in order to acquire data over a wide area rapidly. In general, since video data does not include position information, it is difficult to analyze the actual size of the inspection object quantitatively. In this study, we evaluated the utilization of 3D point cloud data of bridges using a matching between video frames and reference photos. The drones were used to acquire video and photographs. And exterior orientations of the video frames were generated through feature point matching with reference photos. Experimental results showed that the accuracy of the video frame data is similar to that of the reference photos. Furthermore, the point cloud data generated by using video frames represented the shape and size of bridges with usable accuracy. If the stability of the product is verified through the matching test of various conditions in the future, it is expected that the video-based facility modeling and inspection will be effectively conducted.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.436-440
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• 2008

Complete consideration on condition and surrounding environment shall be performed to select proper location for complex planning or establishment of facility with special purpose. Especially, in case of living space for human, lighting, ventilation, efficiency in land use, etc. are important elements. Diverse 3D analysis through 3D topography modeling and virtual simulation is necessary for this. Now, it can be processed with relatively inexpensive cost since high resolution satellite image essential in topography modeling is provided with domestic technology through Arirang No. 2 satellite (KOMPSAT2). In this study, several candidate sites is selected for complex planning with special purpose and analysis on proper location was performed using the 3D topography modeling and land information. For this, land analysis, land price calculation, slope analysis and aspect analysis have been carried out. As a result of arranging the evaluation index for each candidate site and attempting the quantitative evaluation, proper location could be selected efficiently and reasonably.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1757-1766
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• 2021

The green coverage ratio is the ratio of the land area to green coverage area, and it is used as a practical urban greening index. The green coverage ratio is calculated based on the land cover map, but low spatial resolution and inconsistent production cycle of land cover map make it difficult to calculate the correct green coverage area and analyze the precise green coverage. Therefore, this study proposes a new method to calculate green coverage area using aerial images and deep neural networks. Green coverage ratio can be quickly calculated using manned aerial images acquired by local governments, but precise analysis is difficult because components of image such as acquisition date, resolution, and sensors cannot be selected and modified. This limitation can be supplemented by using an unmanned aerial vehicle that can mount various sensors and acquire high-resolution images due to low-altitude flight. In this study, we proposed a method to calculate green coverage ratio from manned or unmanned aerial images, and experimentally verified the proposed method. Aerial images enable precise analysis by high resolution and relatively constant cycles, and deep learning can automatically detect green coverage area in aerial images. Local governments acquire manned aerial images for various purposes every year and we can utilize them to calculate green coverage ratio quickly. However, acquired manned aerial images may be difficult to accurately analyze because details such as acquisition date, resolution, and sensors cannot be selected. These limitations can be supplemented by using unmanned aerial vehicles that can mount various sensors and acquire high-resolution images due to low-altitude flight. Accordingly, the green coverage ratio was calculated from the two aerial images, and as a result, it could be calculated with high accuracy from all green types. However, the green coverage ratio calculated from manned aerial images had limitations in complex environments. The unmanned aerial images used to compensate for this were able to calculate a high accuracy of green coverage ratio even in complex environments, and more precise green area detection was possible through additional band images. In the future, it is expected that the rust rate can be calculated effectively by using the newly acquired unmanned aerial imagery supplementary to the existing manned aerial imagery.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.101-104
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• 2010

Purpose: Raynaud scan is divided to flow, blood pool and local-delay image. Usually, we evaluate comparison through blood pool and local-delay image. We will evaluate about usability when comparative observe blood image and local-delay image in Raynaud scan that used $^{201}Tl$ as making flow image to one sheet of images. Materials and Methods: We have selected 29 Raynaud phenomenon patients aged 14~68 years who visited department of vascular surgery between Feb. 2008 and Aug. 2009. An intravenous injection $^{201}Tl$ of 111 MBq (3 mCi) to opposite side diagonal line limbs above an internal auditing department. Equipment used Philips gamma camera forte A-Z, and collimator used LEHR. Matrix size set up to each $64{\times}64$, $128{\times}128$, $256{\times}256$ and zoom factor used to full field. Protocol of dynamic is 2 second to 155 frames. Blood pool and delay count to 300 second. We set up ROI by a foundation to data acquired in PEGASYS processing program. Each results were analyzed with the SPSS 12.0 statistical software. Results: Each averages of count ratio (Rt / Lt) to have been given at composite image, a blood pool image, delay images analyzed at Raynaud phenomenon patients is $1.25{\pm}0.39$, $1.20{\pm}0.33$, $1.11{\pm}0.17$. The sample analysis results of blood pool image and delay image contented itself with p<0.029. Also, there don't have been each difference, and blood pool image, delay image regarding composite image was able to know. Conclusion: We were able to give help for comparison to evaluate a blood pool image and a local delay image at the Raynaud scan which used $^{201}Tl$ while making a flow image to one sheet image. Identification to be visual too was possible. If you are proceeded a researcher that there was further depth, you are more appropriate for, and you may get useful information.