• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.198-207
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• 2020

Smart City operates with the purpose of solving urban problems. The important thing in smart city operation is that spatial information must be managed at a high level. In addition, it has the characteristics of being managed by one platform. This study presented the core value dimension of smart city based on analysis of various domestic and overseas smart city operation cases. Smart cities are basically operated based on spatial information, and the higher the level of spatial information, the more smart city services can be connected and managed in an integrated manner. The performance dimension of smart city core values presented in the study includes prosperity, personalization, convenience, accuracy, sustainability, safety, environment, integration, etc., and there is a connectivity dimension, a concept that can be managed in an integrated manner. This study will be useful for empirical research on smart city performance dimension design and surveys based on case studies. It will also help field managers who develop, operate, and manage smart cities when quantifying performance dimensions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.275-284
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• 2023

Land monitoring involves systematically understanding changes in land use, leveraging spatial information such as satellite imagery and aerial photographs. Recently, the integration of deep learning technologies, notably object detection and semantic segmentation, into land monitoring has spurred active research. This study developed a web service to facilitate such integrations, allowing users to analyze aerial and drone images using CNN models. The web service architecture comprises AI, WEB/WAS, and DB servers and employs three primary deep learning models: DeepLab V3, YOLO, and Rotated Mask R-CNN. Specifically, YOLO offers rapid detection capabilities, Rotated Mask R-CNN excels in detecting rotated objects, while DeepLab V3 provides pixel-wise image classification. The performance of these models fluctuates depending on the quantity and quality of the training data. Anticipated to be integrated into the LX Corporation's operational network and the Land-XI system, this service is expected to enhance the accuracy and efficiency of land monitoring.

• Journal of the Korea Society of Computer and Information
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• v.20 no.11
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• pp.47-54
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• 2015

In this paper, I examines the spatial representation of the change in the environment of the digital platform, and play the game with a focus on the spatial characteristics of a digital game. First, what is the Spatial characteristic of digital games? This section applies to a digital game "theory of Lefebvre", and the spatial representation of the practice space, divided into representational space were explored. Second, how to express dealing Is there space in the genre of adventure games? The spatial characteristics of the game medium through the Spatial characteristic of the adventure game genre that is most striking examples was analyzed whether the expression in any way. Consequently, the spatial characteristics of the digital game studies of the game as well as think a very large role in the development direction. In addition, this case analysis of the expression is the basis of this digital game that is utilized in many areas, and I am sure many possibilities to find a positive role in the game.

• 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.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.81-89
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• 2014

In Korea, National spatial data infrastructure has implemented in order to integrated manage and share the national spatial information producted by public agencies and local governments. The necessities of systematic quality management are raised, because information, which is generated by different agencies, is integrative managed by national level. In this paper, the establishment of BPR(Business Process Reengineering) for national spatial data infrastructure quality management system. Quality management business is defined as quality management object definition, quality measuring, evaluation and analysis, and quality enhancement process. Next, activities for each process are designed. For the quality management business, business rule(BR) is required for determining error. We derive the BR for six objects(legal-dong, railway boundary, railway centerline, road boundary, road centerline, building) among the basic spatial information. Other information's BR can be generated by using the derivation method described in this paper. Based on the BPR of this paper and derived BR, national spatial data infrastructure quality management system can be implemented in the future.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.85-95
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• 2021

Recently, as data mining and artificial neural network techniques are developed, analyzing large amounts of data is proposed to reduce the dimension of the data. In general, empirical orthogonal function (EOF) used to reduce the dimension in the ocean data and recently, Self-organizing maps (SOM) algorithm have been investigated to apply to the ocean field. In this study, both algorithms used the monthly Sea level anomaly (SLA) data from 1993 to 2018 around the East Asia Coasts. There was dominated by the influence of the Kuroshio Extension and eddy kinetic energy. It was able to find the maximum amount of variance of EOF modes. SOM algorithm summarized the characteristic of spatial distributions and periods in EOF mode 1 and 2. It was useful to find the change of SLA variable through the movement of nodes. Node 1 and 5 appeared in the early 2000s and the early 2010s when the sea level was high. On the other hand, node 2 and 6 appeared in the late 1990s and the late 2000s, when the sea level was relatively low. Therefore, it is considered that the application of the SOM algorithm around the East Asia Coasts is well distinguished. In addition, SOM results processed by SLA data, it is able to apply the other climate data to explain more clearly SLA variation mechanisms.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1479-1481
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• 2003

The aim of this paper was mainly to interpret the real information-missing patch of image by using the kriging interpolation technology of spatial statistics. The TM Image of the Jingouling Forest Farm of Wangqing Forestry Bureau of Northeast China on 1 July 1997 was used as the tested material in this paper. Based on the classification for the TM image, the information pixel-missing patch of image was interpolated by the kriging interpolation technology of spatial statistics theory under the image treatment software-ERDAS and the geographic information system software-Arc/Info. The interpolation results were already passed precise examination. This paper would provide a method and means for interpreting the information-missing patch of image.

• Spatial Information Research
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• v.10 no.3
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• pp.421-438
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• 2002

Abstraction of geographic data within a spatial database context must deal with geometrical simplification, modification or maintenance of the integrity of features, spatial and aspatial data, topology within class, and relationships between classes. This research is to propose a method to abstract a spatial database into a high level database. This study refines operators to carry out the modifications required by the abstraction process in the spatial database. Then, a set of operator sequences (workflows) is suggested to specify operators required to abstract a given feature class and to arrange them in order. Finally, a prototype system is developed, based on rule management with a graphic user interface. When the abstraction process is implemented sequentially we demonstrate that a preferential ordering of operations improves efficiency and reduces loss and distortion in the information.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.83-94
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• 2004

In this study we analyze categorical data by means of spatial statistics and echelon analysis. To do this, we first determine the hierarchical structure of a given contingency table by using echelon dendrogram then, we detect candidates of hotspots given as the top echelon in the dendrogram. Next, we evaluate spatial scan statistics for the zones of significantly high or low rates based on the likelihood ratio. Finally, we detect hotspots of any size and shape based on spatial scan statistics.

• 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.