• Journal of Korean Society of Transportation
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• v.7 no.1
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• pp.57-70
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• 1989

The purpose of study is to analyze the spatial population distribution and accessibility of network in urban areas. This study examines the forty-six political subdivision cities in Korea at the end of 1983, except the four metrpolitans (Seoul, Pusan, Daeku and Incheon). Evaluation indexes are classified the spatial pupulation distribution and accessibility of network. To analyze the cities, 10 indexes and the statistical techniques such as descriptive analysis, correlation analysis, factor analysis and cluster analysis were used. According to the results of cluster analysis, 15 cities (Ulsasn, Suwon, Bucheon, Chungju and etc.) are classified dispersed cities and another 15 cities (Kwangju, Daejun, Sungnam, Mokpo and etc.) are classified concentrated cities.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.19-30
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• 2008

Recently, the query processing algorithm in the field of spatial network database(SNDB) has been attracted by many Interests. But, there is little research on route-based queries. Since the moving objects move only in spatial networks, the efficient route-based query processing algorithms, like in-route nearest neighbor(IRNN), are essential for Location-based Service(LBS) and Telematics application. However, the existing IRNN query processing algorithm has a problem that it does not consider traffic jams in the road network. In this thesis, we propose an IRNN query processing algorithm which considers space restriction. Finally, we show that space-constrained IRNN query processing algorithm is efficient compared with the existing IRNN algorithm.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.202-208
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• 2014

Wireless network information services allow end systems to discover heterogeneous networks and spectrum available for secondary use at or near their current location, helping them to cope with increasing traffic and finite spectrum resources. We propose a unified architecture that allows end systems to find nearby base stations that are using either licensed, shared or unlicensed spectrum across multiple network operators. Our study evaluates the performance and scalability of spatial databases storing base station coverage area geometries. The measurement results indicate that the current spatial databases perform well even when the number of coverage areas is very large. A single logical spatial database would likely be able to satisfy the query load for a large national cellular network. We also observe that coarse geographic divisions can significantly improve query performance.

• Journal of Korea Planning Association
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• v.54 no.2
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• pp.76-83
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• 2019

This study aims to empirically identify the effect of spatial accessibility, based on travel, on housing prices in the Korean capital region. More specifically, it has two research purposes: First, investigating the effect of comprehensive spatial accessibility, based on road network and actual trips from origin to destination, on average apartment price (Korean Won per square meter) at the level of Eup, Myeon and Dong; Second, identifying better accessibility index between Hansen's and Kalogirou and Foley's ones. The former represents a road-based travel time decay function with destination trips, while the latter is a function with origin trips as well as destination ones. The study employs spatial economic models considering spatial auto-correlative relationship as an appropriate methodology with such control independent indicators as population density, road density, educational environment and distances from CBDs. Analysis results demonstrate that spatial accessibility, based on road network and actual trips from origin to destination, has a statistically significant impacts on housing price in the region. Our empirical evidence proves that the Hansen index is more appropriate than the other in estimating housing price impacts.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1259-1276
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• 2017

As technologies related to sensor network are currently emerging and the use of GeoSensor is increasing along with the development of Internet of Things (IoT) technology, spatial query processing systems to efficiently process spatial sensor data are being actively studied. However, existing spatial query processing systems do not support a spatial-temporal data type and a spatial-temporal operator for processing spatialtemporal sensor data. Therefore, they are inadequate for processing spatial-temporal sensor data like GeoSensor. Accordingly, this paper developed a spatial-temporal query processing system, for efficient spatial-temporal query processing of spatial-temporal sensor data in a sensor network. Lastly, this paper verified the utility of System through a scenario, and proved that this system's performance is better than existing systems through performance assessment of performance time and memory usage.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.207-212
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• 2021

Clustering Unlabeled Spatial-datasets to convert them to Labeled Spatial-datasets is a challenging task specially for geographical information systems. In this research study we investigated the NYC Taxi Limousine Commission dataset and discover that all of the spatial-temporal trajectory are unlabeled Spatial-datasets, which is in this case it is not suitable for any data mining tasks, such as classification and regression. Therefore, it is necessary to convert unlabeled Spatial-datasets into labeled Spatial-datasets. In this research study we are going to use the Clustering Technique to do this task for all the Trajectory datasets. A key difficulty for applying machine learning classification algorithms for many applications is that they require a lot of labeled datasets. Labeling a Big-data in many cases is a costly process. In this paper, we show the effectiveness of utilizing a Clustering Technique for labeling spatial data that leads to a high-accuracy classifier.

• Journal of Korea Water Resources Association
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• v.52 no.8
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• pp.515-529
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• 2019

Geospatial information for river network and watershed boundary have played a fundamental roles in terms of river management, planning and design, hydrological and hydraulic analysis. Irrespective of their importance, the lack of punctual update and improper maintenance in currently available river-related geospatial information systems has revealed inconsistency issues between individual systems and spatial inaccuracy with regard to reflecting dynamically transferring riverine geography. Given that digital elevation models (DEMs) of high spatial resolution enabling to reproduce precise river network are only available adjacent to national rivers, DEMs with poor spatial resolution lead to generate unreliable river network information and thereby reduce their extensible applicabilities. This study first of all evaluated published spatial information available in Korea with respect to their spatial accuracy and consistency, and also provides a methodology and tool to modify existing low resolution of DEMs by means of striation of conventional or digitized river network to replicate input river network in various degree of further delineation. The tool named FSND was designed to be operated in ArcGIS ModelBuilder which ensures to automatically simulate river network striation to DEMs and delineation with different flow accumulation threshold. The FNSD was successfully validated in Seom River basin to identify its replication of given river network manually digitized based on recent aerial photograph in conjunction with a DEM with 30 meter spatial resolution. With the derived accuracy of reproducibility, substantiation of a various order of river network and watershed boundary from the striated DEM posed tangible possibility for highly extending DEMs with low resolution to be capable of producing reliable riverine spatial information subsequently.

• Spatial Information Research
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• v.18 no.5
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• pp.93-105
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• 2010

Spatial neighborhoods are spaces which are relate to target space. A 3D spatial query which is a function for searching spatial neighborhoods is a significant function in spatial analysis. Various methodologies have been proposed in related these studies, this study suggests an adjacent based methodology. The methodology of this paper implements topological data for represent a adjacency via using network based topological data model, then apply modifiable Dijkstra's algorithm to each topological data. Results of ordering analysis about an adjacent space from a target space were visualized and considered ways to take advantage of. Object of this paper is to implement a 3D spatial query for searching a target space with a adjacent relationship in 3D space. And purposes of this study are to 1)generate adjacency based 3D network data via network based topological data model and to 2)implement a 3D spatial query for searching spatial neighborhoods by applying Dijkstra's algorithms to these data.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.556-570
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• 2021

The existing video expression recognition methods mainly focus on the spatial feature extraction of video expression images, but tend to ignore the dynamic features of video sequences. To solve this problem, a multi-mode convolution neural network method is proposed to effectively improve the performance of facial expression recognition in video. Firstly, OpenFace 2.0 is used to detect face images in video, and two deep convolution neural networks are used to extract spatiotemporal expression features. Furthermore, spatial convolution neural network is used to extract the spatial information features of each static expression image, and the dynamic information feature is extracted from the optical flow information of multiple expression images based on temporal convolution neural network. Then, the spatiotemporal features learned by the two deep convolution neural networks are fused by multiplication. Finally, the fused features are input into support vector machine to realize the facial expression classification. Experimental results show that the recognition accuracy of the proposed method can reach 64.57% and 60.89%, respectively on RML and Baum-ls datasets. It is better than that of other contrast methods.

• Journal of the Korean Geographical Society
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• v.43 no.4
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• pp.526-543
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• 2008

Based on the social network analysis(SNA), this study examines the structural and spatial characteristics of the actor networks of the manufacturing industries for the elderly. In the field of economic geography, former researches on network have mainly focused on the network governance. However, this study focused on the social network analysis. Centrality indexes are used to analyze the topological structure of actor networks of firms and organizations. In order to investigate the spatial structure of actor networks, not only the regional distribution of actors but also the correlation between centrality index and distance are analyzed. Network matrixes among actors are transformed to network matrixes among regions using block modeling method to reveal the spatial characteristics of the actor networks. In spite of the importance of the Capital Region, networks in the non-Capital Region like Chungnam and Pusan were showed high network density. This suggested that some kinds of policy project operating in the non-Capital Region had the influence on this network in the initial stage of industry.