• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.587-598
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• 2021

This study aims to develop a multi-camera based MMS (Mobile Mapping System) technology for building a HD (High Definition) map for autonomous driving and for quick update. To replace expensive lidar sensors and reduce long processing times, we intend to develop a low-cost and efficient MMS by applying multiple cameras and real-time data pre-processing. To this end, multi-camera storage technology development, multi-camera time synchronization technology development, and MMS prototype development were performed. We developed a storage module for real-time JPG compression of high-speed images acquired from multiple cameras, and developed an event signal and GNSS (Global Navigation Satellite System) time server-based synchronization method to record the exposure time multiple images taken in real time. And based on the requirements of each sector, MMS was designed and prototypes were produced. Finally, to verify the performance of the manufactured multi-camera-based MMS, data were acquired from an actual 1,000 km road and quantitative evaluation was performed. As a result of the evaluation, the time synchronization performance was less than 1/1000 second, and the position accuracy of the point cloud obtained through SFM (Structure from Motion) image processing was around 5 cm. Through the evaluation results, it was found that the multi-camera based MMS technology developed in this study showed the performance that satisfies the criteria for building a HD map.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.1-11
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• 2017

The main source of water pollution in Doam Lake is turbid incoming water from upland fields in the upper watershed. The large scale, elevation, and slope of this region means that it is inaccessible, and it is difficult to collect information and update data. Field survey results show that there is a difference between classification of upland fields and grasslands in the cadastral data and land-cover map. In this study, MODIS NDVI was calculated from May 2000 to September 2015 in order to improve classification accuracy of upland fields.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.152-159
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• 2014

Recently. utilization of remote sensing exploration and cloud computing has been extended to efficient measurement, store, and update of bathymetry map data according to cloud computing technology. In the field of real ocean, water depth measurements and measurement data management, distribution, and display equipment for the development and dissemination have generated a lot of time and cost. To improve these problems, through real-time three-dimensional display system at this location, we can determine the importance of measurement activities, and reduce the time and cost of measurement activities. Data measured from marine probe vessels and remote sensing exploration equipments and other various channels can be handled and managed. In this paper, we propose a realtime three-dimensional display system through the depth measurements from remote sensing exploration. The proposed real-time three-dimensional display system can be effectively applied in the field of measurement of the topographical survey of the land as well as bathymetry of the sea.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.83-91
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• 2012

Crown density, which is defined as the proportion of the forest floor concealed by tree crown, is important and useful information in various fields. Previous methods of measuring crown density have estimated crown density by interpreting aerial photographs or through a ground survey. These are time-consuming, labor-intensive, expensive and inconsistent approaches, as they involve a great deal of subjectivity and rely on the experience of the interpreter. In this study, the crown density of a forest in Korea was estimated using KOMPSAT-2 high-resolution satellite images. Using the image segmentation technique and stand information of the digital forest map, the forest area was divided into zones. The crown density for each segment was determined using the discriminant analysis method and the forest ratio method. The results showed that the accuracy of the discriminant analysis method was about 60%, while the accuracy of the forest ratio method was about 85%. The probability of extraction of candidate to update was verified by comparing the result with the digital forest map.

• Journal of the Korean Geographical Society
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• v.44 no.6
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• pp.706-722
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• 2009

This study aims to find the ways to correct and fix the errors in transcription by analyzing Romanization of Korean geographical names in foreign countries. The gazetteers from many countries, place name databases, and map-providing websites are the main source of research. Common error types found in this study are variant name posting, subordinated marking, double posting, spelling errors, and location errors. In fact, transcription of geographical names exhibits more diverse forms and types. The counter measures to fix these errors are as follows, firstly, consistent efforts with regular monitoring to fix errors are essential. Secondly, the one and only standardized Romanization principle is urgent. Thirdly, prompt update and publication in case of place name and/or boundary change is necessary. Fourthly, efforts to register unregistered geographical names are necessary. Lastly, the establishment of central agency solely for the management of geographical names is required.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.3
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• pp.223-230
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• 2007

As the centralization of city, underground facilities is increasing and being more important. Although the importance of underground facilities map has been emphasized, there were many accidents related underground facilities. The inaccuracy of existing data and the carelessness of management caused many accidents. It is very important to update and to have high quality accuracy of underground facilities maps. But the underground facilities maps are mapped and updated by each institutes. So it is difficult to verify the accuracy of the data. In this study, Field Test is performed to analyze the horizontal accuracy of existing maps using Electromegnetic Induction Method, Total Station and GPS. Surveying of underground facilities in Seoul was performed for 6 institutes of underground facilities during 3 years. The aim of this study is to verify the horizontal accuracy of data and to improve the accuracy of underground facility maps. As the result of analysis, the horizontal accuracy of 6 underground facilities management institutes is 73 cm(2004), 78 cm(2005) and 75 cm(2006).

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.243-248
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• 2003

An incremental kernel principal component analysis (IKPCA) is proposed for the nonlinear feature extraction from the data. The problem of batch kernel principal component analysis (KPCA) is that the computation becomes prohibitive when the data set is large. Another problem is that, in order to update the eigenvectors with another data, the whole eigenspace should be recomputed. IKPCA overcomes these problems by incrementally computing eigenspace model and empirical kernel map The IKPCA is more efficient in memory requirement than a batch KPCA and can be easily improved by re-learning the data. In our experiments we show that IKPCA is comparable in performance to a batch KPCA for the feature extraction and classification problem on nonlinear data set.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.506-506
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• 2002

S. Korean Government has accelerating its efforts to enhance the quality of the drinking water. The Ministry of Environment has declared the law of securing water-pollutant buffering zone to minimize the inflow of the point and nonpoint sources into the drinking water sources. As a first phase of installing nationa-wide water-pollutant buffering zone, approximately 300km buffering zone has been delineated along the South and North Han river, the major drinking water sources for the capital area of S. Korea, which has the population of more than 12 millions. The buffering zone has the width of 1,000 meter for the special protection area, and 500 meter for the remaining area from both ends of the river. The major works have been done in three stages. Firstly, the boundaries lines of the buffering zone was delineated on the digital topographic maps. Secondly, the maps were overlayed with the cadastral maps to identify individual land parcels, the street address of the major pollutant discharging facilities, and all different types of pollutants including livestocks. Thirdly, the field work has been done as a verification. Once the buffering zone was generated, all the information for the buffering gone were created or imported from other government agencies including official land price, details of the major manufacturing facilities discharging considerable amount of pollutants, major motels and resorts, not to mention of restaurants, etc. Also, major livestock houses were located to identify the path of the pollutant inflow to the drinking water source. Further works need to be continued such as purchasing private lands within the buffering zone and change the land use in the efforts to decrease the pollutant amount and to provide more environmentally friendly space. Also, high resolution satellite imagery should be utilized in the near future as a cost-effective data source to update all the landuse activities within buffering zone.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.436-443
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• 2009

There have been rapid increases to the demands for modeling diverse and complex spatial phenomena and utilizing spatial data through the computer across all the aspects of society. As a result, the importance and utilization of remote sensing and GIS's(geographic information systems) have also increased. It can produce digital data of enormous accuracy and value by incorporating remote sensing images into GIS analysis technology and make various thematic maps by classifying and analyzing land cover. Once such a map is made for the target area, it can easily do modeling and constant monitoring based on the map, revise the database with ease, and thus efficiently update geo-spatial information. Under the goal of analyzing changes to land cover along the road by combining the remote sensing and GIS technology, this study classified land cover from the images of two periods, detected changes to the six classes over ten years, and obtained statistics about the study area's quantitative area changes in order to provide basic decision making data for urban planning and development. By analyzing land use along the road, one can set up plans for the area along the road and the downtown to supplement each other.