• Journal of KIISE:Information Networking
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• v.37 no.5
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• pp.363-373
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• 2010

The existing QoS mechanisms for video streaming are short of the consideration for various user environments and the characteristic of streaming applying programs. In order to overwhelm this problem, studies on the video streaming protocols exploiting scalable video coding (SVC), which provide spatial, temporal, and qualitative scalability in video coding, are progressing actively. However, these protocols also have the problem to deepen network congestion situation, and to lower fairness between other traffics, as they are not equipped with congestion control mechanisms. SVC based streaming protocols also have the problem to overlook the property of videos encoded in SVC, as the protocols transmit the streaming simply by extracting the bitstream which has the maximum bit rate within available bandwidth of a network. To solve these problems, this study suggests TCP-friendly network adaptive SVC streaming(T-NASS) protocol which considers both network status and SVC bitstream property. T-NASS protocol extracts the optimal SVC bitstream by calculating TCP-friendly transmission rate, and by perceiving the network status on the basis of packet loss rate and explicit congestion notification(ECN). Through the performance estimation using an ns-2 network simulator, this study identified T-NASS protocol extracts the optimal bitstream as it uses TCP-friendly transmission property and perceives the network status, and also identified the video image quality transmitted through T-NASS protocol is improved.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.5-16
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• 2022

Based on the general formula for the area error of a polygon and rectangular parcel, the constant term 0.026² × M (scale denominator) of the area error calculation formula prescribed by the Enforcement Decree was analyzed. As a result, it is found that the formula appropriately reflects the characteristics of the graphical surveying as a typical rectangular parcel model, but quantitatively allows a relatively large area error. In addition, it is found that, even if the area is the same, 50% more area error than a square parcel could be calculated depending on the shape of the parcel, and that the allowable area error should be different when dividing a parcel. Based on the analysis, furthermore, this study shows a solution that can solve the problems at once from the point of cadastral surveying. These are, the problem of reflecting the accuracy of the surveying, the problem of reflecting the size and shape of the parcel, and the problem whether a single area error formula can be used without having to distinguish between graphical and numerical surveyings. The new formula that solves these problems will bring about improvements in many related factors and promote the development of digital cadastral system.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.2
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• pp.23-34
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• 2012

As the quality of life grows, the role of cultural facilities in urban areas is becoming more important. However, due to various reasons, the location of these facilities shows the geographical imbalance between urban regions. Even though provision of road network can improve this kind of urban problem, in many countries, the provision of urban infrastructure plays a role which is magnifies the cultural gap between regions and socio-economic classes. The findings of this study are as follows. First of all, the inequality of accessibility to cultural facilities is shown over the period. Cross-sectional data shows that the higher the income of a region, the higher the accessibility index(AI) of the zone to cultural facilities at any time. Next, the provision of road network contributes the improvement of AI of high income region. Finally the provision of new facilities has a tendency that these kind of facilities are located to make AI of high income zone better. It means that the decision making by city government intensifies the geographical inequality. This result would be very useful in the decision making process for determining the number and the location of cultural facilities and other similar urban infrastructure as well. Also it will be helpful for the selection of optimal location which considered not only physical distances but also social equalities.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.50-60
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• 2014

The purpose of this study is to identify characteristics and improvements of the climate change vulnerability analysis methods to build a safe city from disasters. For this, an empirical analysis on sea level rise disasters was performed focusing on Heaundae-gu in Busan. For the analysis, Census output areas and Dongs were set as analysis unit and their disaster vulnerability was analyzed. Improvements were reviewed through the comparison and review of analysis process and results. According to analysis results, Modifiable Areal Unit Problem(MAUP) which gives different results according to aggregate unit occurs. Improvements were induced by analysis process, and it was found that in spatial unit setting stage that becomes the base of analysis, analysis unit adjustment, score computation method adjustment, and clearer analysis method for each disaster type would be needed. In analysis execution stage, it was thought that weighting according to variables, diversification of variables, and exclusion of subjective analysis selection method would be needed. It is expected that accurate the total disaster vulnerability analysis will be the base for the improvement of efficiency in urban resilience responding to future weather changes.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.24-33
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• 2018

DSM and orthoimage, which are representative results of UAV photogrammetry, are high-quality spatial information data and are widely used in various fields of spatial information industry in recent years. However, the UAV photogrammetry has a problem that the quality of the output of the UAV deteriorates due to the altitude of the UAV, the camera calibration, the weather conditions at the time of shooting, the performance of the GPS / IMU and the number of the ground reference points. The purpose of this study is to analyze the location accuracy of unmanned aerial photogrammetry according to the change of the number if ground control points. Experiments were made with fixed wing, and the shooting altitude was set at 130m and 260m. The number of ground reference points used was 9, 8, 5, and 4, respectively. Ten checkpoints were used. XY RMSE for orthoimage and Z RMSE for DSM were compared and analyzed. In addition, the resolution of the orthoimage was determined to affect the judgment of the operator in the verification of the planimetric position accuracy, and the visual resolution was analyzed using the Siemens star target. As a result of the analysis, the variation of the vertical position accuracy is larger than the variation of the planimetric position accuracy when the number of the ground reference points are different. Also The higher the flying height, the greater the effect of change of ground control points on position accuracy.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.137-143
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• 2013

The high resolution satellite images are used in many fields such as weather observation, remote sensing, military facilities monitoring, cultural properties protection etc. Although satellite images are obtained in same satellite imaging system, the satellite images are degraded depending on the condition of hardware(optical device, satellite operation altitude, image sensor, etc.). Due to the fact that changing the hardware of satellite imaging system is impossible for resolution enhancement of these degraded satellite after launching a satellite, therefore the method of resolution enhancement with satellite images is necessary. In this paper the resolution is enhances by using a Super Resolution(SR) algorithm. The SR algorithm is an algorithm to enhance the resolution of an image by uniting many low resolution images, so an output image has higher resolution than using other interpolation methods. But It is difficult to obtain many images of the same area. Therefore, to solve this problem, we applied SR after by applying the affine and projection transform. As a results, we found that the images applied SR after affine and projection transform have higher resolution than the images only applied SR.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.405-416
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• 2019

Due to the development of information and communication technology, the production and processing speed of data is getting faster. To classify objects using machine learning, which is a field of artificial intelligence, data required for training can be easily collected due to the development of internet and geospatial information technology. In the field of geospatial information, machine learning is also being applied to classify or recognize objects using images and point clouds. In this study, the problem of manually constructing training data using existing digital map version 1.0 was improved, and the technique of classifying roads, buildings and vegetation using image and point clouds were proposed. Through experiments, it was possible to classify roads, buildings, and vegetation that could clearly distinguish colors when using true ortho-image with only RGB (Red, Green, Blue) bands. However, if the colors of the objects to be classified are similar, it was possible to identify the limitations of poor classification of the objects. To improve the limitations, random forest and support vector machine techniques were applied after band fusion of true ortho-image and normalized digital surface model, and roads, buildings, and vegetation were classified with more than 85% accuracy.

• Journal of Korea Spatial Information System Society
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• v.7 no.1 s.13
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• pp.63-76
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• 2005

Recently, the wireless positioning techniques and mobile computing techniques were developed with rapidly to use location data of moving objects. Also, the demand for LBS(Location Based Services) which uses location data of moving objects is increasing rapidly. In order to support various LBS, a system that can store and retrieve location data of moving objects efficiently is required necessarily. The more the number of moving objects is numerous and the more periodical sampling of locations is frequent, the more location data of moving objects become very large. Hence the system should be able to efficiently manage mass location data, support various spatio-temporal queries for LBS, and solve the uncertainty problem of moving objects. Therefore, in this paper, we presented a hash technique, a clustering technique and a trajectory search technique to manage location data of moving objects efficiently And, we have developed a Mass Moving Object Location Data Management System, which is a disk-based system, that can store and retrieve location data of mass moving objects efficiently and support the query for spatio-temporal data and the past location data with uncertainty. By analying the performance of the Mass Moving Object Locations Management system and the SQL-Server, we can find that the performance of our system for storing and retrieving location data of moving objects was about 5% and 300% better than the SQL-Server, repectively.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.44-58
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• 2014

In this study, a standard vector data model was developed for interoperability of river-geospatial information and for verification purpose the applicability of the standard vector model was evaluated using a model to RIMGIS vector data at Changnyeong-Hapcheon & Gangjung-Goryeong irrigation watershed. The standards from ISO and OGC were analyzed and the river geospatial data model standard was established by applying the standards. The ERD was designed based on the analysis information on data characteristics and relationship. The verification of RIMGIS vector data included points, lines and polygon to develope GDM was carried out by comparing with the data by layer. This conducting comparison of basic spatial data and attribute data to each record and spatial information vertex. The error in the process of conversion was 0 %, indicating no problem with model. Our Geospatial Data Model presented in this study provides a new and consistent format for the storage and retrieval of river geospatial data from connected database. It is designed to facilitators integrated analysis of large data sets collected by multiple institutes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.305-313
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• 2019

Recently, spatial information is being constructed actively based on the images obtained by drones. Because occlusion areas occur due to buildings as well as many obstacles, such as trees, pedestrians, and banners in the urban areas, an efficient way to resolve the problem is necessary. Instead of the traditional way, which replaces the occlusion area with other images obtained at different positions, various models based on deep learning were examined and compared. A comparison of a type of feature descriptor, HOG, to the machine learning-based SVM, deep learning-based DNN, CNN, and RNN showed that the CNN is used broadly to detect and classify objects. Until now, many studies have focused on the development and application of models so that it is impossible to select an optimal model. On the other hand, the upgrade of a deep learning-based detection and classification technique is expected because many researchers have attempted to upgrade the accuracy of the model as well as reduce the computation time. In that case, the procedures for generating spatial information will be changed to detect the occlusion area and replace it with simulated images automatically, and the efficiency of time, cost, and workforce will also be improved.