• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.213-217
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• 1998

This study overviews existing evaluation methods of classification accuracy using confusion matrix proposed by Cohen in 1960's, and proposes ISDd(Index of Spatial Distribution by distance) and ISDs(Index of Spatial Distribution by scatteredness) for the evaluation of spatial distribution of satellite image classification errors, which has not been tried yet. Index of spatial distribution offers the basis of decision on adoption/rejection of classification results at sub-image level by evaluation of distribution, such as status of local aggregation of misclassified pixels. So, users can understand the spatial distribution of misclassified pixels and, can have the basis of judgement of suitability and reliability of classification results.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.89-95
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• 2009

This paper proposes a tag indexing scheme for RFID tag using spatial index. The tag being used for the inventory management and the tag's location is determined by the position of readers. Therefore, the reader recognizes the tag, which is attached products and thereby their positions can be traced down. In this paper, we propose hTag-tree( Hybrid Tag index) which manages RFID tag attached products. hTag-tree is a new index, which is based on tag's attributes with fast searching, and this tag index manages RFID tags using reader's location. This tag index accesses rapidly to tags for insertion, deletion and updating in dynamic environment. This can minimize the number of node accesses in tag searching comparing to previous techniques. Also, by the extension of MER in present tag index, it is helpful to stop the lowering of capacity which can be caused by parent node approach. The proposed index experiment deals with the comparison of tag index. Fixed Interval R-tree, and present spatial index, R-tree comparison. As a result, the amount of searching time is significantly shortened through hTag-tree node access in data search. This shows that the use of proposed index improves the capacity of effective management of a large amount of RFID tag.

• Korean Journal of Remote Sensing
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• v.30 no.3
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• pp.375-381
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• 2014

Soil moisture is an essential satellite-driven variable for understanding hydrologic, pedologic and geomorphic processes. The European Space Agency (ESA) has endorsed soil moisture as one of Climate Change Initiates (CCI) and had merged multi-satellites over 30 years. The $0.25^{\circ}$ coarse resolution soil moisture satellite data showed correlations with variables of a water stress index, Temperature-Vegetation Dryness Index (TVDI), from a stepwise regression analysis. The ancillary data from TVDI, Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) from MODIS were inputted to a multi-regression analysis for estimating the surface soil moisture. The estimated soil moisture was validated with in-situ soil moisture data from April, 2012 to March, 2013 at Andong observation sites in South Korea. The soil moisture estimated using satellite-based LST and NDVI showed a good agreement with the observed ground data that this approach is plausible to define spatial distribution of surface soil moisture.

• Journal of Korean Society for Geospatial Information Science
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• v.3 no.2 s.6
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• pp.137-149
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• 1995

A spatial index is necessary to support an efficient search in a geographical information system (GIS) that is important in these days. In this paper, we design and implement a geographical data manager, called GOOD (Geo-object Oriented Data Manager) 2.0, by extending GOOD 1.0 with a spatial index processing module. That is, R-tree and R*-tree are used as a spatial index in this paper to make an efficient search possible. In addition, this paper conducts a performance evaluation to measure the improvement in search efficiency and analyzes the results of the performance evaluation. When the performance evaluation is carried out, we consider various environment factors to allow an GIS administrator to use the results as a basic data in selecting an appropriate spatial index.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.3
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• pp.116-126
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• 2003

In this study, we research about the relationships of human longevity and environments, inducted the significant factors of longevity from the statistical analysis, and represented spatial distribution of longevity using geographic information system. The factors confining human longevity can be categorized by geography/geology, climate/weather, economy, and social welfare. After analyzing statistical data, dependent variable which means the longevity index is defined by the ratio of population more than 85 years old among population more than 65 years old. The results of analysis show that longevity are related with waterworks ratio, temperature, local tax ratio, and latitude. In this study we discussed about the spatial characteristics which are represented by variance of the longevity index and described a spatial relationship between the longevity index and significant factors which are chosen by statistical analysis. In the further study, in order to sustain the longevity of a region, it is necessary for the effective rural planning to propagate a longevity of rural areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.29-40
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• 2021

Risk factors that threaten public safety such as crime, fire, and traffic accidents have spatial characteristics. Since each region has different dangerous environments, it is necessary to analyze the spatial pattern of risk factors for each sector such as traffic accident, fire, crime, and living safety. The purpose of this study is to analyze the spatial distribution pattern of local safety level index, which act as an index that rates the safety level of each sector (traffic accident, fire, crime, living safety, suicide, and infectious disease) for basic local governments across the nation. The following analysis tools were used to analyze the spatial autocorrelation of local safety level index : Global Moran's I, Local Moran's I, and Getis-Ord's G⁎i. The result of the analysis shows that the distribution of safety level on traffic accidents, fire, and suicide tends to be more clustered spatially compared to the safety level on crime, living safety, and infectious disease. As a result of analyzing significant spatial correlations between different regions, it was found that the Seoul metropolitan areas are relatively safe compared to other cities based on the integrated index of local safety. In addition, hot spot analysis using statistical values from Getis-Ord's G⁎i derived three hot spots(Samchuck, Cheongsong-gun, and Gimje) in which safety-vulnerable areas are clustered and 15 cold spots which are clusters of areas with high safety levels. These research findings can be used as basic data when the government is making policies to improve the safety level by identifying the spatial distribution and the spatial pattern in areas with vulnerable safety levels.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.263-274
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• 2016

The exceptional development of electronic device technology, the miniaturization of mobile devices, and the development of telecommunication technology has made it possible to monitor human biometric data anywhere and anytime by using different types of wearable or embedded sensors. In daily life, mobile devices can collect wireless body area network (WBAN) data, and the co-collected location data is also important for disease analysis. In order to efficiently analyze WBAN data, including location information and support medical analysis services, we propose a geohash-based spatial index method for a location-aware WBAN data monitoring system on the NoSQL database system, which uses an R-tree-based global tree to organize the real-time location data of a patient and a B-tree-based local tree to manage historical data. This type of spatial index method is a support cloud-based location-aware WBAN data monitoring system. In order to evaluate the proposed method, we built a system that can support a JavaScript Object Notation (JSON) and Binary JSON (BSON) document data on mobile gateway devices. The proposed spatial index method can efficiently process location-based queries for medical signal monitoring. In order to evaluate our index method, we simulated a small system on MongoDB with our proposed index method, which is a document-based NoSQL database system, and evaluated its performance.

• Journal of Construction Engineering and Project Management
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• v.2 no.4
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• pp.32-41
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• 2012

In recent times, multi-centralization and decentralization as well as large Capital area and suburbanization in the spatial structure of capital area. With rapid growth, urbanization and industrialization are unsystematic, and growth inequality between regions caused negative effects such as discordant centralization and decentralization, fluctuating land value, and gap between living conditions. Accordingly, this study analyzed urban spatial indexes by the self-governed body in the capital area such as Seoul, Incheon, and Gyeonggi province for the analysis of the regional inequality phenomenon. We examined the characteristics of temporal and spatial changes in urban spatial structure in the capital area by utilizing the distribution pattern and density of city indexes such as population, employment, etc, and then drew the commonality of those factors through factor analysis. We evaluated the drawn results through the city standard index by each city, conducted factor score analysis, and identified the interaction between each factor and Housing Purchase Price Composite Indices index, housing rent price index(Housing Jeonse Price Composite Indices), land price fluctuation rate, diffusion ratio of house, and financial independence.

• Spatial Information Research
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• v.16 no.1
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• pp.113-127
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• 2008

This paper proposes an efficient spatial index, named $AR^*$-tree(Area $R^*$-tree) which is a variant of the $R^*$-tree, for mobile software. A MBR(Minimum Bounding Rectangle) structure of the $AR^*$-tree has additional min and max values of area axis as well as x and y axes. The value of area axis is used to determine the significance of a spatial data. If area of a spatial data is large, then it is significant when drawing a map. To reduce complexity of a map on a small screen of mobile device, only significant spatial data can be found by the $AR^*$-tree. The result of a series of tests indicates that the $AR^*$-tree provides a method for control of readability of a map and guarantees an efficient performance at the same time.

• Journal of Environmental Impact Assessment
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• v.15 no.1
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• pp.45-52
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• 2006

The purpose of this study is to assess spatiotemporal variation of coastal water quality according to time and location changes. For this we developed numerical marine trophic index base on four water quality components (chlorophyll, suspended solids, dissolved inorganic nitrogen and phosphorus) and applied this index to the water quality data measured in the korean coastal zone for the 7-years period from 1997 to 2003. Water quality data are obtained only at selected sites even though they are potentially available at any location. Therefore, in order to estimate spatial variation of coastal water quality, it is necessary to estimate the unknown values at unsampled locations based on observation data. In this study, we used IDW (Inverse Distance Weighted) method to predict water quality components at unmeasured locations and applied marine trophic index to predicted values obtained by IDW interpolation. The results of this study indicate that marine trophic index and spatial interpolation are useful for understanding spatiotemporal characteristics of coastal water quality.