• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.5
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• pp.487-496
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• 2020

This study introduces how GISs (Geographic Information Systems) are used to assess spatial disparities in urban green spaces in the Chicago. Green spaces provide us with a variety of benefits, namely environmental, economic, and physical benefits. This study seeks to explore socioeconomic relationships between green spaces and their surrounding communities and to evaluate spatial disparities from a variety of perspectives, such as health-related, socioeconomic, and physical environment factors. To achieve this goal, this study used spatial statistics, such as optimized hotspot analysis, network analysis, and space-time cluster analysis, which enable conclusions to be drawn from the geographic data. In particular, 12 variables within the three factors are used to assess spatial disparities in the benefits of the use of green spaces. Finally, the variables are standardized to rank the community areas and identify where the most vulnerable community areas or parks are. To evaluate the benefits given to the community areas, this study used the z- and composite scores, which are compared in the three different combinations. After identifying the most vulnerable community area, crime data is used to spatially understand when and where crimes occur near the parks selected. This work contributes to the work of urban planners who need to spatially evaluate community areas in considering the benefits of the uses of green spaces.

• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.35-53
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• 2021

The study reported in this paper aimed to evaluate the topics and opinions of COVID-19 discussion found on Twitter. It performed topic modeling and sentiment analysis of tweets posted during the COVID-19 outbreak, and compared these results over space and time. In addition, by covering a more recent and a longer period of the pandemic timeline, several patterns not previously reported in the literature were revealed. Author-pooled Latent Dirichlet Allocation (LDA) was used to generate twenty topics that discuss different aspects related to the pandemic. Time-series analysis of the distribution of tweets over topics was performed to explore how the discussion on each topic changed over time, and the potential reasons behind the change. In addition, spatial analysis of topics was performed by comparing the percentage of tweets in each topic among top tweeting countries. Afterward, sentiment analysis of tweets was performed at both temporal and spatial levels. Our intention was to analyze how the sentiment differs between countries and in response to certain events. The performance of the topic model was assessed by being compared with other alternative topic modeling techniques. The topic coherence was measured for the different techniques while changing the number of topics. Results showed that the pooling by author before performing LDA significantly improved the produced topic models.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.2 s.16
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• pp.71-78
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• 2000

In these days, the attributes data recorded in computerization of cadastral maps is just written in its own format, not considered the relation with graphic data. Therefore, digital information linked attribute data to graphic data is necessary to be performed as fundamental data of graphic information and analysis of various spatial information. This study is to present the possibility of GIS application by constructing cadastral information related to graphic and attribute Information based on the cadastral map. Attribute information was constructed as a relational database form using data modeling and entity-relationship diagram. Thus, this study is expected to be used as a fundamental data for various public planning and design including the effective management of cadastral information and building parcel based land information system by presenting various spatial analysis and application methods.

• Spatial Information Research
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• v.21 no.4
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• pp.1-6
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• 2013

This study presents the analysis of temporal and spatial distribution of occurrences of wind gust over Korea from 2002 to 2009. The events during typhoons are excluded and the topographical effects on the wind speed are also corrected using KBC (2005). As the results, the frequency of the occurrences is as high as 286 and the higher occurrences appear mainly along the coastal area. This study also shows that the uncertainty of the appearance of wind gust during thunderstorm is much higher than in synoptic wind by comparing wind speed records for both events. This study also found that the spatial distribution of cumulative cloud quotient is closely correlated to that of occurrences of thunderstorm wind gust, which suggests the possible utilization of the cloud quotient as weighting factors in assessing wind gust risk.

• Annual Conference of KIPS
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• 2006.11a
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• pp.309-312
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• 2006

In order to highly applying for the GIS. it is necessary to the SDSS that is possible to the systematic spatial analysis with spatial information and attribute information, I studied it for SDSS construction and implementation, and I brought up the phase of the spatial decision support through the case study.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.99-101
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• 2010

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.1
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• pp.41-46
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• 2010

The latest multi-dimension spatial information technology is emerging its importance as material for carrying out efficient facilities management's supporting business about numerous facilities inside a university, budgeting decision-making supporting business such as operating expenses' budgeting and management, etc. and admission advertisement, etc. Accordingly, the present study selected an optimal location that can maximize spatial utilization of a building to be newly built by constructing multi-dimension spatial information for facilities management of a university, and executed a site suitability analysis according to transfer of a university symbol and a landscape analysis, etc. according to external environment change. As a result, it appeared that the effects such as prevention of duplicate investment and budget saving, etc. due to university's comfortable spatial composition and systematic comprehensive development & budgeting or decision-making support in case of execution, etc. caused by rationalization of facilities plan & management can be maximized.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.269-281
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• 2016

The process of spatial big data, such as social media, is being paid more attention in the field of spatial information in recent years. This study, as an example of spatial big data analysis, analyzed the spatial and temporal distribution of Tweet data based on the location and time information. In addition, the characteristics of its spatial pattern by times were identified. Tweet data in Busan city are collected, processed, and analyzed to identify the characteristics of the temporal and spatial pattern. Then, the results of Tweet data analysis were compared with the characteristics of the land type. This study found that spatial pattern of tweeting in the city was associated with given time periods such as daytime and nighttime in both weekdays and weekends. The spatial distribution patterns of individual time periods were compared with the characteristics of the land for the spatially concentrated area. The results of this study showed that tweeted data would be related to different spatial distribution depending on the time, which potentially reflects the daily pattern and characteristics of the land type of urban area to some extent. This study presented the possible incorporation of social media data, e. g. Tweet data, into the field of spatial information. It is expected that there will be more advantage to use a variety of social media data in areas such as land planning and urban planning.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.367-371
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• 2002

I construct a chaotically driven contraction system having some analogy with the information transfer mechanism in the brain system especially from CA1 cell to CA3 cell known from the empirical result. And I consider the properties of the response system on a state space according to the external input into the drive neuron by observing the fractal hierarchical structure. Then I induce the relation between the information about state transition of the chaotic time series and the spatial information on a fractal attractor to confirm the possibility of encoding of time series data to spatial information.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.357-366
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• 2006

A traditional image analysis or classification method using satellite imagery is mostly based on the spectral information. However, the spatial information is more important according as the resolution is higher and spatial patterns are more complex. In this study, we attempted to compare and analyze the variogram properties of actual high resolution imageries mainly in the urban area. Through the several experiments, we have understood that the variogram is various according to a sensor type, spatial resolution, a location, a feature type, time, season and so on and shows the information related to a feature size. With simple modeling, we confirmed that the unique variogram types were shown unlike the classical variogram in case of small subsets. Based on the grasped variogram characteristics, we made a level index map for determining urban complexity or land-use classification. These results will become more and more important and be widely applied to the various fields of high-resolution imagery such as KOMPSAT-2 and KOMPSAT-3 which is scheduled to be launched.