• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.767-785
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• 2021

With the rapid development of information technology, it is now possible to analyze the spatial patterns of cultivated land and its evolution by combining GIS, geostatistical analysis models and spatiotemporal big data for the dynamic monitoring and management of cultivated land resources. The spatial pattern of cultivated land and its evolutionary patterns in Luoyang City, China from 2009 to 2019 were analyzed using spatial autocorrelation and spatial autoregressive models on the basis of GIS technology. It was found that: (1) the area of cultivated land in Luoyang decreased then increased between 2009 and 2019, with an overall increase of 0.43% in 2019 compared to 2009, with cultivated land being dominant in the overall landscape of Luoyang; (2) cultivated land holdings in Luoyang are highly spatially autocorrelated, with the 'high-high'-type area being concentrated in the border area directly north and northeast of Luoyang, while the 'low-low'-type area is concentrated in the south and in the municipal area of Luoyang, and being heavily influenced by topography and urbanization. The expansion determined during the study period mainly took place in the Luoyang City, with most of it being transferred from the 'high-low'-type area; (3) elevation, slope and industrial output values from analysis of the bivariate spatial autocorrelation and spatial autoregressive models of the drivers all had significant effects on the amount of cultivated land holdings, with elevation having a positive effect, and slope and industrial output having a negative effect.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.67-87
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• 2021

Public library accessibility directly affects library usage, and the disproportionate distribution of accessibility is a decisive factor limiting the equitable provision of library services. In this regard, this study analyzed the spatial accessibility of public libraries in Busan and identified the factors affecting accessibility of public libraries using spatial regression analysis. As a results of the analysis, the accessibility of public libraries in the Busan showed large deviations by region. Also, spatial distribution of public libraries had no correlation with the settled population and use of public transportation, and location of public libraries was inefficient, in terms of social equity. The results of this study will assist to understand the spatial accessibility of public libraries in Busan, to identify factors that affect the accessibility. Moreover, this study is expected to be utilized as fundamental data for releasing disparities of the spatial accessibility and selecting new location of public library in Busan.

• Journal of Korean Society of Rural Planning
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• v.29 no.3
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• pp.79-89
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• 2023

As the demand for environmental-friendly agricultural products continues to rise due to increased concerns regarding food safety and ecosystem conservation, it is becoming important to identify regions and spatial locations where environmental-friendly should be intensively established for production integration. This study aims to analyze the spatial distribution of environmental-friendly certified farms in Jeollanam-do, South Korea. Spatial statistical analysis based on Local Moran's I and Getis-Ord Gi^* were used to identify spatial cluster characteristics and landscape indices were utilized to analyze spatial patterns of environmental-friendly certified farms. The results indicated that Haenam-gun, Gangjin-gun, Muan-gun, and Jindo-gun were identified as hotspots, while Muan-gun, Goheung-gun, and Jindo-gun exhibited high connectivity. This suggests that environmental-friendly certified farms in Muan-gun and Jindo-gun were clustered and closely connected to one another. Based on the results of the spatial distribution of environmental-friendly certified farms, areas belonging to the hotspot and with high connectivity should be managed as clustered districts to secure the foundation and system of environmental-friendly certified farms. Areas that belong to cold spots and have low connectivity should be preceded by measures to promote conversion to environmental-friendly agriculture. In addition, it is necessary to make it possible to create a large-scale cluster district through a long-term spatial planning strategy to expand the environmental-friendly certified farms. The findings of this study can provide quantitative data on policies and discussions for developing a model for rural spatial planning.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.125-140
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• 2017

Until recently, regression based spatial interpolation methods and Kriging based spatial interpolation methods have been largely used to estimate land price or housing price, but less attention has been paid on comparing the performance of these spatial interpolation methods. In this regard, this research applied regression based spatial interpolators and Kriging based spatial interpolators for estimating the land prices in Dalseo-gu, Daegu metropolitan city and evaluated the accuracy of eight spatial interpolators. OLS, SLM, SEM, and GWR were used as regression based spatial interpolators while SK, OK, UK, and CK were employed as Kriging based spatial interpolators. The global accuracy was statistically evaluated by RMSE, adjusted RMSE, and COD. The relative accuracy was visually compared by three-dimensional residual error map and scatterplot. Results from statistical and visual analyses indicate that GWR reflecting the spatial non-stationarity was a relatively more accurate spatial predictor to estimate land prices in the study area than SAR and Kriging based spatial interpolators considering the spatial dependence. The findings from this research will contribute to the secondary research into analyzing the urban spatial structure with land prices.

• 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.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.643-652
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• 2006

Decision trees are mainly used for the classification and prediction in data mining. The distribution of spatial data and relationships with their neighborhoods are very important when conducting classification for spatial data mining in the real world. Spatial decision trees in previous works have been designed for reflecting spatial data characteristic by rating Euclidean distance. But it only explains the distance of objects in spatial dimension so that it is hard to represent the distribution of spatial data and their relationships. This paper proposes a decision tree based on spatial entropy that represents the distribution of spatial data with the dispersion and dissimilarity. The dispersion presents the distribution of spatial objects within the belonged class. And dissimilarity indicates the distribution and its relationship with other classes. The rate of dispersion by dissimilarity presents that how related spatial distribution and classified data with non-spatial attributes we. Our experiment evaluates accuracy and building time of a decision tree as compared to previous methods. We achieve an improvement in performance by about 18%, 11%, respectively.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.25-33
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• 2016

In order to visualize point based Location-Based Social Network Services(LBSNS) data on multi-scaled tile map effectively, it is necessary to apply tile-based clustering method. Then determinating reasonable numbers and size of tiles is required. However, there is no such criteria and the numbers and size of tiles are modified based on data type and the purpose of analysis. In other words, researchers' subjectivity is always involved in this type of study. This is when Modifiable Areal Unit Problem(MAUP) occurs, that affects the results of analysis. Among LBSNS, geotagged Twitter data were chosen to find the influence of MAUP in scale effects perspective. For this purpose, the degree of spatial autocorrelation using spatial error model was altered, and change of distributions was analyzed using Morna's I. As a result, positive spatial autocorrelation showed in the original data and the spatial autocorrelation was decreased as the value of spatial autoregressive coefficient was increasing. Therefore, the intensity of the spatial autocorrelation of Twitter data was adjusted to five levels, and for each level, nine different size of grid was created. For each level and different grid sizes, Moran's I was calculated. It was found that the spatial autocorrelation was increased when the aggregation level was being increased and decreased in a certainpoint. Another tendency was found that the scale effect of MAUP was decreased when the spatial autocorrelation was high.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.601-609
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• 2013

Standard lots, which are used to assess values of individual lots in Korea, have been criticized for their improper distribution. However, there has been very little evaluation for the spatial distribution of standard lots, and an evaluation method has never been developed. In order to overcome this situation, we attempt to assess the appropriateness of the spatial distribution of standard lots using the L-index and Monte Carlo simulation. The L-index is a well-known indicator of the complete spatial randomness (CSR) of points in spatial statistics. If the L-index of standard lots is similar to that of individual lots, the former is considered to be randomly distributed according to the latter. By analyzing L-indices of two study areas, Gangnam and Seongdong, we find a statistically significant difference in Gangnam area and a relatively small difference in Seongdong area. We confirm that the spatial distribution of standard lots is not CSR and that the L-index is useful as an evaluation method. These results suggest that the standard lot selection and management guidelines need to be modified to apply the spatial distribution of individual lots to the standard lot selection process.

• Spatial Information Research
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• v.19 no.4
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• pp.33-43
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• 2011

Countries all over the world have been operating various certification systems to protect their consumers, and these systems have become trade barriers between countries. Also, KS and KCC were not designed to reflect characteristics of Geo-Spatial Information Device. The purpose of this study was to derive the plan of Quality Certification System for Geo-Spatial Information Device through the analyses of the existing Quality Certification System. The results of this study were as follows. Firstly, we defined the concept of Quality Certification System for Geo-Spatial Information Device. Secondly, we set the boundary, factors and process of Quality Certification System for Geo-Spatial Information Device through classifying it in detail. Lastly, we suggested about fundamental concept of Quality Certification System for Geo-Spatial Information Device a the analyses of the existing Quality Certification System.

• 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.