• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.423-436
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• 2017

This paper presents a deep learning-based road segmentation framework from very high-resolution orthophotos. The proposed method uses Deep Convolutional Autoencoders for end-to-end mapping of orthophotos to road segmentations. In addition, a set of post-processing steps were applied to make the model outputs GIS-ready data that could be useful for various applications. The optimization of the model's parameters is explained which was conducted via grid search method. The model was trained and implemented in Keras, a high-level deep learning framework run on top of Tensorflow. The results show that the proposed model with the best-obtained hyperparameters could segment road objects from orthophotos at an average accuracy of 88.5%. The results of optimization revealed that the best optimization algorithm and activation function for the studied task are Stochastic Gradient Descent (SGD) and Exponential Linear Unit (ELU), respectively. In addition, the best numbers of convolutional filters were found to be 8 for the first and second layers and 128 for the third and fourth layers of the proposed network architecture. Moreover, the analysis on the time complexity of the model showed that the model could be trained in 4 hours and 50 minutes on 1024 high-resolution images of size $106{\times}106pixels$, and segment road objects from similar size and resolution images in around 14 minutes. The results show that the deep learning models such as Convolutional Autoencoders could be a best alternative to traditional machine learning models for road segmentation from aerial photographs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.1
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• pp.117-129
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• 1997

In recent years, the 1 : 5,000 scale Digital National Basemap(DNB) has been generated under National Geo-graphic Information System(NGIS) Project. The DNB database generated will be the backdrop data for thematic maps, underground facilities maps and so on. The DNB database will be distributed to the government and private sectors in near future so that it should meet the requirements as the basic data. In order to assure the quality of DNB database, the establishment of quality assurance process to database was in great need. In this study, we were mainly concerned with improving the quality of digital national basemap database in geomatric aspect as well as the processing time due to the amount of digital data generated. As a results of this study, the quality assuance process of DNB database is established and automatic quality assurance program is developed. Also, the program developed in this study is contributed to quality assurance of DNB database as well as economic aspects.

• Proceedings of the KSRS Conference
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• v.1
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• pp.52-55
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• 2006

It's used to be said that tsunami is a rare event. The recurrence time of tsunami in Sumatra area is approximately 230 years as CalTech Research Group‘s study from paleocoral. However, the tsunami occurred in Indian Ocean on 26 December 2004, 28 March 2005 and 17 July 2006, because the earthquakes still release the energy. To cope with the tsunami disaster, we have to put the much effort on better disaster preparedness. The Tsunami Reduction Of Impacts through three Key Actions (TROIKA) was suggested by Eddie N. Bernard, the director of NOAA/PMEL (Pacific Marine Environmental Laboratory). They are Hazard Assessment, Mitigation and Warning Guidance. The satellite remote sensing has potential on these actions. The medium and high resolution satellite data were used to assess the degree of damage at the six-damaged provinces on the Andaman seacoast of Thailand. Fast and reliable interpretation of the damage by remote sensing method can be used for inundation mapping, rehabilitation and housing plans for the victims. For tsunami mitigation, the satellite data can be used with GIS to construct the evacuation map (evacuation route and refuge site) and coastal zone management. It is also helpful for educational program for local residents and school systems. Tsunami is a kind of ocean wave, therefore any satellite sensors such as SAR, Altimeter, MODIS, Landsat, SPOT, IKONOS can detect the tsunami wave in 2004. The satellite images have shown the characteristics of tsunami wave approaching the coast. For warning, satellite data has potential for early warning to detect the tsunami wave in deep ocean, if there are enough satellite constellation to monitor and detect the first tsunami wave like the pressure gauge, seismograph and tide gauge with the DART buoy can do. Moreover, the new methods should be developed to analyse the satellite data more faster for early warning procedure.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.123-127
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• 2020

In order to obtain the overall fire line information of medium and large forest fires at night, the ground control system was developed to determine whether forest fires occurred through real-time video clips and to calculate the location of the forest fires determined using the location of drones, angle information of video cameras, and altitude information on the map to reduce the time required for regular video matches obtained after the completion of the mission. To verify the reliability of the developed function, the error distance of the aiming position information of the flight altitude star and the image camera was measured, and the location information within the reliable range was displayed on the map. As the function developed in this paper allows real-time identification of multiple locations of forest fires, it is expected that overall fire line information for the establishment of forest fire extinguishing measures will be obtained more quickly.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.7-16
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• 2008

There are unique aspects of truck vehicle movements compared with the personal travel in trip chaining. This paper reports an analysis on the truck vehicle trip chaining which intercity/metropolitan/intraregional trips are classified. Data collected from the travel dairy survey is used the truck trip-chaining analysis. The pattern of trip chaining classes is classified by the GIS mapping based on orgin-destination trip information. The physical index and efficiency index for each trip diary is used to the truck vehicle activity. Truck trips lengths and time differs from its truck type, service type and travel patterns. It is shown that the efficiency of the truck trip chaining depends on vehicle types and its delivery patterns. There are many other topics for research on trip chaining modeling such as the classification of trip chain, time use and mode choice by trip chaining.

• Spatial Information Research
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• v.9 no.1
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• pp.1-13
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• 2001

Nowadays, SAR Interferometry is actively being studied as a new technique in topographic mapping using satellite imagery. It extracts height values using phase information derived by two SAR imageries covering same areas. Unlike when using SPOT imagery, it is not affected by atmospheric conditions and time. So to speak, we can say that SAR Interferometry is flexible in imagery acquisitions and can get height data economically over wide area. So, it is expected that SAR Interferometry will be widely using in GIS applications. But, in some area occurring geometric distortion, height data are misjudged or not extracted depending on phase unwrapping algorithms. IN the case of ERS tandem data, the accuracy of height data was worst in mountain area. It is the because of the short incidence angle resulted in layover effect. Of the phase unwrapping algorithms, path-following was better in height accuracy but could not get data in layover area. In this area, we could get height data using Height Sensitivity. In concludion, we could get DEM that maintained the accuracy of path-following method and have overall data across imagery.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5225-5231
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• 2015

Background: One of the most prevalent cancers in whole world is skin cancer and its prevalence is growing. The present research sought to estimate relative risk of morbidity and mortality due to skin cancer. Materials and Methods: In this cross-sectional study. The required data were gathered from the registered cancer reports of Cancer Control Office in the Center for Non Communicable Disease of the Iranian Ministry of Health (MOH). The data were extracted at province level in the time span of 2008-10. WINBUGS software was used to analyze the data and to identify high risk regions. ArcGIS10 was utilized to map the distribution of skin cancer and to demonstrate high risk provinces by using classic and fully Bayesian models taking into account spatial correlations of adjacent regions separately for men and women. Results: Relative risk of morbidity for women in Yazd and for men in Kurdistan and relative risk of mortality for women in Bushehr and for men in Kohgiluyeh were found to be the highest. Bayesian model due to regarding adjacent regions correlation, have precise estimation in comparing to classical model. More frequent epidemiological studies to enact skin cancer prevention programs. Conclusions: High risk regions in Iran include central and highland regions. Therefore it is suggested that health decision makers enact public education, using anti UV creams and sunglasses for those parts as a short preventing program.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.12 no.2
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• pp.187-197
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• 1994

The purpose of this study is to develop a PC-based water supply facilities information system. This system will be a major stepping-stone for developing Geographic Information Systems(GIS) in Korea, which is constructed by integrating the technologies related to Automated Mapping(AM) systems and Facilities Management(FM) system. And the results of this study are as follows: (1) After the user needs assessment, it was decided that information management of the water supply facilities including distribution pipes, valves, and leaking management are the most urgent tasks. So, the system was developed focusing on these tasks. (2) After the system design and development, the water supply facilities information system consists of graphic database management system, attribute database management system, internal interface that links graphic data and attribute data, and graphic user interface for user-friendliness. (3) The graphic data and the attribute data including distribution pipes, leading-pipes, valves, and parcels at the study area, Non-Hyun Dong Kang-Nam Gu in Seoul, were used in this system, and the water supply facilities database was established. It was applied to test these facilities, and proved that the system developed in this study is efficient to manage information within the scope of this study. (4) The function using the parcel identification number was efficient to locate the address concerned.

• Korean Journal of Geomatics
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• v.2 no.2
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• pp.123-130
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• 2002

LiDAR (Light Detection And Ranging) system has a profound impact on geoinformatics. The laser mapping system is now recognized as being a viable system to produce the digital surface model rapidly and efficiently. Indeed the number of its applications and users has grown at a surprising rate in recent years. Interest is now focused on the reconstruction of buildings in urban areas from LiDAR data. Although with present technology objects can be extracted and reconstructed automatically using LiDAR data, the quality issue of the results is still major concern in terms of geometric accuracy. It would be enormously beneficial to the geoinformatics industry if geometrically accurate modeling of topographic surface including man-made objects could be produced automatically. The objectives of this study are to reconstruct buildings using airborne LiDAR data and to evaluate accuracy of the result. In these regards, firstly systematic errors involved with ALS (Airborne Laser Scanning) system are introduced. Secondly, the overall LiDAR data quality was estimated based on the ground check points, then classifying the laser points was performed. In this study, buildings were reconstructed from the classified as building laser point clouds. The most likely planar surfaces were estimated by the least-square method using the laser points classified as being planes. Intersecting lines of the planes were then computed and these were defined as the building boundaries. Finally, quality of the reconstructed building was evaluated.

• Asian Journal of Atmospheric Environment
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• v.2 no.1
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• pp.34-46
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• 2008

Emissions inputs for use in air quality modeling of Korea were generated with the emissions inventory data from the National Institute of Environmental Research (NIER), maintained under the Clean Air Policy Support System (CAPSS) database. Source Classification Codes (SCC) in the Korea emissions inventory were adapted to use with the U.S. EPA's Sparse Matrix Operator Kernel Emissions (SMOKE) by finding the best-matching SMOKE default SCCs for the chemical speciation and temporal allocation. A set of 19 surrogate spatial allocation factors for South Korea were developed utilizing the Multi-scale Integrated Modeling System (MIMS) Spatial Allocator and Korean GIS databases. The mobile and area source emissions data, after temporal allocation, show typical sinusoidal diurnal variations with high peaks during daytime, while point source emissions show weak diurnal variations. The model-ready emissions are speciated for the carbon bond version 4 (CB-4) chemical mechanism. Volatile organic carbon (VOC) emissions from painting related industries in area source category significantly contribute to TOL (Toluene) and XYL (Xylene) emissions. ETH (Ethylene) emissions are largely contributed from point industrial incineration facilities and various mobile sources. On the other hand, a large portion of OLE (Olefin) emissions are speciated from mobile sources in addition to those contributed by the polypropylene industry in point source. It was found that FORM (Formaldehyde) is mostly emitted from petroleum industry and heavy duty diesel vehicles. Chemical speciation of PM2.5 emissions shows that PEC (primary fine elemental carbon) and POA (primary fine organic aerosol) are the most abundant species from diesel and gasoline vehicles. To reduce uncertainties in processing the Korea emission inventory due to the mapping of Korean SCCs to those of U.S., it would be practical to develop and use domestic source profiles for the top 10 SCCs for area and point sources and top 5 SCCs for on-road mobile sources when VOC emissions from the sources are more than 90% of the total.