• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.53-58
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• 2020

The purpose of this study is to build a database of Spatial information Bigdata of cities using satellite images and spatial information, and to examine the correlations with the surface temperature. Using architectural structure and usage in building information, DEM and Slope topographical information for constructed with 300 × 300 mesh grids for Busan. The satellite image is used to prepare the Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Bare Soil Index (BI), and Land Surface Temperature (LST). In addition, the building area in the grid was calculated and the building ratio was constructed to build the urban environment DB. In architectural structure, positive correlation was found in masonry and concrete structures. On the terrain, negative correlations were observed between DEM and slope. NDBI and BI were positively correlated, and NDVI was negatively correlated. The higher the Building ratio, the higher the surface temperature. It was found that the urban environment DB could be used as a basic data for urban environment analysis, and it was possible to quantitatively grasp the impact on the architecture and urban environment by adding local meteorological factors. This result is expected to be used as basic data for future urban environment planning and disaster prevention data construction.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.115-126
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• 2009

Recent development in wireless communication and mobile positioning technologies makes Location-Based Services (LBSs) popular. However, because, in the LBSs, users request a query to database servers by using their exact locations, the location information of the users can be misused by adversaries. Therefore, a mechanism for users' privacy protection is required for the safe use of LBSs by mobile users. For this, we, in this paper, propose a efficient cloaking region creation scheme using Hilbert curves in distributed grid environment, so as to protect users' privacy in LBSs. The proposed scheme generates a minimum cloaking region by analyzing the characteristic of a Hilbert curve and computing the Hilbert curve values of neighboring cells based on it, so that we may create a cloaking region to satisfy K-anonymity. In addition, to reduce network communication cost, we make use of a distributed hash table structure, called Chord. Finally, we show from our performance analysis that the proposed scheme outperforms the existing grid-based cloaking method.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.13-21
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• 2011

In mobile environment supporting mobility technologies, user requirements have been increased with respect to utilization of location information. In particular, moving object DBMS has consistently posed in order to efficiently maintain traffic information related to location of vehicle which tents to tremendously change over time. Despite the fact that these sorts of researches must be taken into consideration, empirical studies on moving object in terms of map database for lbs service, spatial attribute of which is continuously changed over time, have rarely performed. Therefore, aim of this paper is to suggest efficient spatial index scheme, which is capable of supporting query processing algorithm and location of moving object over time, by developing new empirical model. As a result, we can come to the conclusion that moving object model based on multi-fixed grid index makes it possible to cut down on the number of entity for retrieving. What's more, this model enables hierarchical data to be accessed through efficient spatial filtering on large-scale lbs data and constraints in accordance with level in order to display map.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.9-17
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• 2006

Moving objects database systems manage a set of moving objects which changes its locations and directions continuously. The traditional spatial indexing scheme is not suitable for the moving objects because it aimed to manage static spatial data. Because the location of moving object changes continuously, there is problem that expense that the existent spatial index structure reconstructs index dynamically is overladen. In this paper, we analyzed the insertion/deletion costs for processing the movement of objects. The results of our extensive experiments show that the Dynamic Hashing Index outperforms the original R-tree and the fixed grid typically by a big margin.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.231-242
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• 2007

The existing pattern mining methods[1,2,3,4,5,6,11,12,13] do not use location generalization method on the set of location history data of moving object, but even so they simply do extract only frequent patterns which have no spatio-temporal constraint in moving patterns on specific space. Therefore, it is difficult for those methods to apply to frequent pattern mining which has spatio-temporal constraint such as optimal moving or scheduling paths among the specific points. And also, those methods are required more large memory space due to using pattern tree on memory for reducing repeated scan database. Therefore, more effective pattern mining technique is required for solving these problems. In this paper, in order to develop more effective pattern mining technique, we propose new location generalization method that converts data of detailed level into meaningful spatial information for reducing the processing time for pattern mining of a massive history data set of moving object and space saving. The proposed method can lead the efficient spatial moving pattern mining of moving object using by creating moving sequences through generalizing the location attributes of moving object into 2D spatial area based on $R^*$-Tree and Area Grid Hash Table(AGHT) in preprocessing stage of pattern mining.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.206-221
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• 2019

Source localization in three-dimensional (3-D) wireless sensor networks (WSNs) is becoming a major research focus. Due to the complicated air-ground environments in 3-D positioning, many of the traditional localization methods, such as received signal strength (RSS) may have relatively poor accuracy performance. Benefit from prior learning mechanisms, fingerprinting-based localization methods are less sensitive to complex conditions and can provide relatively accurate localization performance. However, fingerprinting-based methods require training data at each grid point for constructing the fingerprint database, the overhead of which is very high, particularly for 3-D localization. Also, some of measured data may be unavailable due to the interference of a complicated environment. In this paper, we propose an efficient kernel based 3-D localization algorithm via tensor completion. We first exploit the spatial correlation of the RSS data and demonstrate the low rank property of the RSS data matrix. Based on this, a new training scheme is proposed that uses tensor completion to recover the missing data of the fingerprint database. Finally, we propose a kernel based learning technique in the matching phase to improve the sensitivity and accuracy in the final source position estimation. Simulation results show that our new method can effectively eliminate the impairment caused by incomplete sensing data to improve the localization performance.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.60-65
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• 2004

최근 무선/이동 통신 기술과 GPS 기술의 발달은 휴대폰을 소지하고 이동하는 사람이나 GPS 수신기를 탑재한 차량과 같은 이동객체의 위치 정보와 관련된 서비스의 제공을 가능하게 하였다. 이러한 환경에서 연속적으로 변경되는 이동객체의 위치 정보는 데이터베이스에 빈번한 갱신 연산을 요구하게 되고, 이는 전체 시스템의 성능을 저하시키는 원인이 된다. 이러한 문제를 해결하기 위하여 R-Tree와 같은 공간색인 구조를 확장하여 갱신 효율을 높이기 위한 연구가 진행되어 왔지만, 시스템의 전체 성능은 오히려 저하되는 문제를 가져왔다. 이 논문에서는 이동객체의 질의 처리 성능뿐만 아니라 객체의 빈번한 위치 갱신을 효율적으로 처리할 수 있는 방법으로 고정 그리드와 R-Tree를 혼합한 형태의 색인 기법을 제안한다. 제안된 색인 기법은 R-Tree에서 색인의 재조직화로 인해 갱신 성능이 저하되는 문제를 해결하기 위하여 셀 기반 색인 기법인 고정 그리드를 이용하여 이동객체의 위치 정보를 저장하고, 고정 그리드에서 객체의 편중 분포로 인한 오버플로 문제를 처리하기 위하여 오버플로가 발생한 각각의 셀들을 R-Tree로 관리한다. 또한, 객체의 밀도가 낮은 셀들을 하나의 버켓으로 공유하여 관리함으로써 저장 공간을 효율적으로 활용한다. 제안된 방법을 다양한 평가 요소를 통해 실험한 결과, 기존의 R-Tree보다 뛰어난 갱신 성능을 보였으며, 질의 처리에 대해서도 성능이 향상되었음을 보였다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.31-33
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• 2001

고비용의 공간 연산을 수행해야 하는 공간 질의 처리는 여과-정제의 2단계 처리가 일반적이다. 그러나, 2단계 색인 방법은 여과율이 좋지 못한 단점이 있으므로, 최근 다단계 여과 과정이 많이 연구되고 있다. 다단계 여과 과정은 1차 여과된 객체에 대하여 더욱 정밀한 필터를 적용함으로써 후부 객체 수를 줄이는 방법으로 접근하고 있으나, 여러 번의 여과 단계를 거치므로 수행 시간이 길어지고 추가 정보유지로 인한 저장 공간 낭비 등의 단점이 있다. 본 논문에서는 전체 공간 영역을 격자로 분할하고, 객체를 격자 위에 구성하는 2단계의 공간 색인 방법을 제안한다. 제안된 색인 방법은 Dead Space의 크기를 줄이고, 한 번의 여과 과정으로 높은 여과율을 갖는다.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.2
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• pp.75-87
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• 2013

This study developed a GIS-based suitability assessment model of coastal zoning system that is needed in the substantial classification of coastal zoning system according to the establishment of law about coastal zoning system. First, this study investigated several kinds of regulations, GIS database and application system related coastal area. Also, grid data model was selected as the GIS analytical model for calculating items of suitability assessment of coastal zoning system. And Grid-based analytical method was suggested for calculating items composing of sea and spatial location characteristics including physical one. Critical values of items were presented using standards that were suggested in coastal regulations and land suitability assessment. Especially, this study presented a calculation method of continuous pattern as fuzzy set function for reflecting the characteristics of GIS data. And this study classified the suitability grade using Z-score and developed model designating coastal zone as conservation management priority, utilization management priority, and planning management priority. This study is judged that very efficient business performance is possible if we consider the spatial coverage of study area and GIS database when the suitability assessment model of coastal zoning system that is suggested in this study, is applied to business works.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.63-73
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• 2010

A comprehensive mapping project for agroclimatic zoning in South Korea will end by April 2010, which has required 4 years, a billion won (ca. 0.9 million US dollars) and 22 experts from 7 institutions to complete it. The map database from this project may be categorized into primary, secondary and analytical products. The primary products are called "high definition" digital climate maps (HD-DCMs) and available through the state of the art techniques in geospatial climatology. For example, daily minimum temperature surfaces were prepared by combining the climatic normals (1971-2000 and 1981-2008) of synoptic observations with the simulated thermodynamic nature of cold air by using the raster GIS and microwave temperature profiling which can quantify effects of cold air drainage on local temperature. The spatial resolution of the gridded climate data is 30m for temperature and solar irradiance, and 270m for precipitation. The secondary products are climatic indices produced by statistical analysis of the primary products and includes extremes, sums, and probabilities of climatic events relevant to farming activities at a given grid cell. The analytical products were prepared by driving agronomic models with the HD-DCMs and dates of full bloom, the risk of freezing damage, and the fruit quality are among the examples. Because the spatial resolution of local climate information for agronomic practices exceeds the current weather service scale, HD-DCMs and the value-added products are expected to supplement the insufficient spatial resolution of official climatology. In this lecture, state of the art techniques embedded in the products, how to combine the techniques with the existing geospatial information, and agroclimatic zoning for major crops and fruits in South Korea will be provided.