• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.78-86
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• 2004

Recently GPS and mobile GIS technologies based on LBS(location based service) have played an important role as DSS(decision supporting system) for domestic forest fire extinguishment policies. In this study forest fire extinguishments information management system based on mobile GIS technique was designed to seize the exact location on wireless network so that it helps to guide the safe and efficient extinguishments affairs and provide the extinguishments environment toward ground fighting teams and the central forest government in real time. Moreover, possibly to operate this system, the foundation technologies by the name of '.gci' such as the spatial data compression method, the spatial data transmission method over wireless network and the spatial analysis interface on PDA should be mainly considered. Especially, in this study the spatial data compression method having high compression rate from 51% to 62% for each polygon, line, and point data, without the loss of data was developed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.42-49
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• 1996

In this paper, we propose a satellite multispectral image data compression method using classified vector quantization. This method classifies each pixel vector considering band characteristics of multispectral images. For each class, we perform both intraband and interband vector quantization to romove spatial and spectral redundancy, respectively. And residual vector quantization for error images is performed to reduce error of interband vector quantization. Thus, this method improves compression efficiency because of removing both intraband(spatial) and interband (spectral) redundancy in multispectral images, effectively. Experiments on landsat TM multispectral image show that compression efficiency of proposed method is better than that of conventional method.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.133-142
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• 2009

Recently, with the advance of wireless internet and the frequent use of mobile devices, demand for LBS(Location Based Service) is increasing, and research is required on spatial indexes for the storage and maintenance of spatial data to provide efficient LBS in mobile device environments. In addition, the use of flash memory as an auxiliary storage device is increasing in order to store large spatial data in a mobile terminal with small storage space. However, the application of existing spatial indexes to flash-memory lowers index performance due to the frequent updates of nodes. To solve this problem, research is being conducted on flash-memory based spatial indexes, but the efficiency of such spatial indexes is lowered by low utilization of buffer and flash-memory space. Accordingly, in order to solve problems in existing flash-memory based spatial indexes, this paper proposed FR-Tree (Flash-Memory based R-Tree) that uses the node compression technique and the delayed write operation technique. The node compression technique of FR-Tree increased the utilization of flash-memory space by compressing MBR(Minimum Bounding Rectangle) of spatial data using relative coordinates and MBR size. And, the delayed write operation technique reduced the number of write operations in flash memory by storing spatial data in the buffer temporarily and reflecting them in flash memory at once instead of reflecting the insert, update and delete of spatial data in flash-memory for each operation. Especially, the utilization of buffer space was enhanced by preventing the redundant storage of the same spatial data in the buffer. Finally, we perform ed various performance evaluations and proved the superiority of FR-Tree to the existing spatial indexes.

• Spatial Information Research
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• v.10 no.1
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• pp.61-76
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• 2002

Mobile map services using PDA are prevailing because of the rapid developments of techniques of the internet and handhold devices recently. While the volume of spatial data is tremendous and the spatial operations are time-intensive, the PDA has small size memory and a low performance processor. Therefore, the spatial index for PDA should be small size and efficiently filter out the candidate objects of spatial operation as well. This paper proposes a spatial index far PDA called MHF(Multilevel Hashing File). The MHF has simple structure for storage efficiency and uses a hashing technique, which is direct search method, for search efficiency. This paper also designs a compression technique for MBR. which occupies almost 80% of index data in the two dimensional case. We call it HMBR. Although the HMBR technique reduces the MB\ulcorner size to almost a third, it shows good filtering efficiency because of no information loss by quantization in case of small objects that occupy a major portion. Our experimental tests show that the proposed MHF index using HMBR technique is appropriate for PDA in terms of the size of index, the Number of MBR comparisons, the filtering efficiency and the execution time of spatial operations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.13-20
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• 2009

Recently there is growing interest in LBS requiring real-time services and the spatial main memory DBMS for efficient Telematics services. In order to optimize existing disk-based spatial indexes of the spatial main memory DBMS in the main memory, spatial index structures have been proposed, which minimize failures in cache access by reducing the entry size. However, because the reduction of entry size requires compression based on the MBR of the parent node or the removal of redundant MBR, the cost of MBR reconstruction increases in index update and the efficiency of search is lowered in index search. Thus, to reduce the cost of MBR reconstruction, this paper proposed the RSMB (relative-sized MBR)compression technique, which applies the base point of compression differently in case of broad distribution and narrow distribution. In case of broad distribution, compression is made based on the left-bottom point of the extended MBR of the parent node, and in case of narrow distribution, the whole MBR is divided into cells of the same size and compression is made based on the left-bottom point of each cell. In addition, MBR was compressed using a relative coordinate and size to reduce the cost of search in index search. Lastly, we evaluated the performance of the proposed RSMBR compression technique using real data, and proved its superiority.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.418-429
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• 2013

This paper presents a GIS vector map data compression scheme based on hybrid polyline simplification method and SEC(spatial energy compaction). The proposed method extracts all layers which contain polylines in the GIS vector map and compress all polylines in extracted layers by the hybrid polyline simplification and SEC based on MAE(minimum area error) for each segment in the line. The proposed simplification and SEC increase the compression ratio while preserving the shape quality. We analyze the visual aspects and compression efficiency between the original GIS vector map and the compressed map. From experimental results, we verify that our method has the higher compression efficiency and visual quality than conventional methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.3
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• pp.15-26
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• 2012

Recently, due to applicability increase of vector data based digital map for geographic information and evolution of geographic measurement techniques, large volumed GIS(geographic information service) services having high resolution and large volumed data are flowing actively. This paper proposed an efficient vector map compression technique using the SEC(spatial energy compaction) based on classified bins for the vector map having 1cm detail and hugh range. We encoded polygon and polyline that are the main objects to express geographic information in the vector map. First, we classified 3 types of bins and allocated the number of bits for each bin using adjacencies among the objects. and then about each classified bin, energy compaction and or pre-defined VLC(variable length coding) were performed according to characteristics of classified bins. Finally, for same target map, while a vector simplification algorithm had about 13%, compression ratio in 1m resolution we confirmed our method having more than 80% encoding efficiencies about original vector map in the 1cm resolution. Also it has not only higher compression ratio but also faster computing speed than present SEC based compression algorithm through experimental results. Moreover, our algorithm presented much more high performances about accuracy and computing power than vector approximation algorithm on same data volume sizes.

• Journal of KIISE
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• v.42 no.2
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• pp.162-168
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• 2015

Image data is mostly stored in compressed form because of its huge size. Therefore, a series of cumbersome procedures is required to apply a transformation to image data: decompression, extraction of spatial data, transformation and recompression. In this paper, we employ DCT(Discrete Cosine Transform) coefficients to change the spatial presentation of images. DCT is commonly used in still image compression standards such as JPEG and moving picture compression standards such as MPEG-2, MPEG-4, and H.264. In this paper, we derived mathematically the relationship between the geometry transformation in the spatial domain and coefficient changes in the DCT domain and verified it with images in the JPEG file format. Because of the efficiency of transformation in the frequency domain, our findings can be utilized for light-weight partial image encryption for privacy data protection or entertainment contents protection.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.13-23
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• 2007

Recently there is growing Interest in LBS(Location Based Service) requiring real-time services and the spatial main memory DBMS for efficient Telematics services. In order to optimize existing disk-based multi-dimensional Indexes of the spatial main memory DBMS in the main memory, multi-dimensional index structures have been proposed, which minimize failures in cache access by reducing the entry size. However, because the reduction of entry size requires compression based on the MBR of the parent node or the removal of redundant MBR, the cost of MBR reconstruction increases in index update and the efficiency of search is lowered in index search. Thus, to reduce the cost of MBR reconstruction, this paper proposed the RSMBR(Relative-Sized MBR) compression technique, which applies the base point of compression differently in case of broad distribution and narrow distribution. In case of broad distribution, compression is made based on the left-bottom point of the extended MBR of the parent node, and in case of narrow distribution, the whole MBR is divided into cells of the same size and compression is made based on the left-bottom point of each cell. In addition, MBR was compressed using a relative coordinate and size to reduce the cost of search in index search. Lastly, we evaluated the performance of the proposed RSMBR compression technique using real data, and proved its superiority.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.753-754
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• 2008

LiDAR data are acknowledged as very useful method to represent 3-D geographical information. In this paper aquad tree has been utilized to represent the 3-D spatial information. Compression algorithm is implemented based on a given threshold. The efficiency of compress is very high with large threshold values.