• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.44-53
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• 2016

The era of Big Data has come and the importance of Big Data has been rapidly growing. The part of transportation, the Four-Step Travel Demand Model(FSTDM), a traditional Trip-Based Model(TBM) reaches its limit. In recent years, a traffic demand forecasting method using the Activity-Based Model(ABM) emerged as a new paradigm. Given that transportation means the spatial movement of people and goods in a certain period of time, transportation could be very closely associated with spatial data. So, I mined Spatial Big Data from SNS. After that, I analyzed the character of these data from SNS and test the reliability of the data through compared with the attributes of TBM. Finally, I built a database from SNS for the operation of ABM and manipulate an ABM simulator, then I consider the result. Through this research, I was successfully able to create a spatial database from SNS and I found possibilities to overcome technical limitations on using Spatial Big Data in the transportation planning process. Moreover, it was an opportunity to seek ways of further research development.

• 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 Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.145-147
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• 2021

도시에 인접한 섬마을은 농어촌지역의 섬마을과는 차별화된 해양문화콘텐츠가 필요하나, 섬마을 내 농어업을 영위하는 주민들의 생업 형태는 대부분 유사한 실정임. 본 연구에서는 도시에 인접한 섬마을의 해양공간환경 데이터를 분석하여 실리도만의 특색있는 해양문화콘텐츠 계획안을 제시하고자 함

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.331-331
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• 2023

일반적으로 가뭄을 해석하기 위하여 가뭄심도, 빈도, 피해면적 및 기간의 영향 등을 고려한 가뭄지수를 이용하며, 이러한 가뭄지수는 주로 지점자료 기반 지상관측자료를 활용하여 산정한다. 하지만 지점자료 특성상 미계측 지역에 대한 정확한 데이터 취득이 어렵기 때문에 미계측 지역에 대한 가뭄 분석의 한계가 발생한다. 다양한 계측기반의 지상센서들이 확충되면서 통계학적 기법기반 공간분포 개선방안을 제시하고 있지만, 정확한 가뭄평가 자료가 추가 및 개선되는 것이 중요하다. 본 연구에서는 원격탐사기술을 활용하여 지점자료의 한계를 극복한 격자기반의 공간정보를 표출함으로써 새로운 가뭄모니터링 방안을 제시하는 것을 목표로 한다. 이를 위해 지상관측자료로 가뭄을 판단하기 어려운 미계측 지역에 대한 가뭄 판단 및 예측 정확도 향상을 위하여 원격탐사기술을 활용한 공간정보 빅데이터를 구축하고자 한다. 미국 국립가뭄경감센터에서 제시한 식생가뭄반응지수 (VegDRI, Vegetation Drought Response Index)는 식생지수, 기상학적 가뭄지수, 지역적 특성을 반영한 생물물리학적 정보를 통합한 하이브리드 가뭄지수로 가뭄과 관련된 공간정보를 활용하여 가뭄을 판단하는 지표이다. VegDRI 산정을 위하여 ERA5의 격자기반 강수자료, MODIS 센서 기반 식생지수 등 격자기반의 공간정보를 수집하였으며, 전처리 모듈을 구축하였다. 또한, 기존 기상학적 가뭄지수인 표준강수지수 (SPI, Standardized Precipitation Index)와 비교를 통해 VegDRI의 국내 적용성을 평가하였으며, 국내 가뭄사례에 적용하여 적절한 가뭄 판단지표로써 활용할 수 있을 것으로 판단된다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.71-72
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• 2023

해양 디지털 트윈 구축을 위해서는 바다와 인접한 육상공간, 해상 및 해저 공간 등의 공간 정보와 시시각각 변하는 해양 환경 데이터, 그리고 해양 생태계 및 해양 자원 등 관련된 해양 데이터를 수집하고 이를 트윈에 적용하는 것이 필수적이다. 본 논문에서는 해양 디지털트윈 구축을 위해 필요한 해양 데이터의 국내 제공 현황을 정리하였다.

• Spatial Information Research
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• v.22 no.5
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• pp.43-52
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• 2014

Recently, Big Data is a buzzword in the creative economy generation. The organizations related to spatial information society focus on building the spatial big data systems. As spatial big data is a combination of spatial information and big data, the data visualization is essential in order to utilize them efficiently. One of the great methodologies for data visualization is infographics. Nationally, Chousn.com initiated the infographics news in 2010. Korean Administration Branches also recognized the importance of infographic and they adopted infographics for their briefings from 2013. Internationally, Visual.ly is leading company in the infographics market and they produced noticeable interactive infographics for Egypt Parliamentary Elections results. In the defense part, Guardian's datajournalism of Afghanistan war log was a good example of utilizing infographics. Throughout the research, five requirements are extracted. First source data should have precision and accuracy in terms of time and space manner. Second, infographics images have a compressibility. Third, the infographics is properly processed for military commanders. Fourth, sharing, openness and communication are essential for high quality infographic. Lastly, infographics should be an analytic tool for predicting future event based on the past data. Infographics is not a direct representation of data but an analytic tool for helping user's choice and decision in critical moments.

• Journal of KIISE
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• v.44 no.11
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• pp.1209-1218
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• 2017

A variety of sensors is widely used these days, and it has become much easier to acquire spatial big data streams from various sources. Since spatial data streams have inherently skewed and dynamically changing distributions, the system must effectively distribute the load among workers. Previous studies to solve this load imbalance problem are not directly applicable to processing spatial data. In this research, we propose Adaptive Spatial Key Grouping (ASKG). The main idea of ASKG is, by utilizing the previous distribution of the data streams, to adaptively suggest a new grouping scheme that evenly distributes the future load among workers. We evaluate the validity of the proposed algorithm in various environments, by conducting an experiment with real datasets while varying the number of workers, input rate, and processing overhead. Compared to two other alternative algorithms, ASKG improves the system performance in terms of load imbalance, throughput, and latency.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.87-87
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• 2021

이상기후 현상으로 기후변화가 사회와 경제에 미치는 영향이 뚜렷한 추세로 변화되고 있다. 현재 기후변화에 관련된 연구는 사회 시스템에서 위험관리를 위해 기온과 강수량에 따라 다양한 분야에 미치는 영향에 대한 연구를 중점으로 이뤄지고 있다. 본 연구는 여름철 폭염에 의한 기후변화가 하천수질에 미치는 영향을 평가하기 위한 것으로, 우리나라 기상청 91개의 기상관측소에서 일일온도 33℃ 이상의 이벤트를 대상으로 환경부 수질관측망 918개에 대한 14개의 하천수질인자인 DO, BOD, COD, TOC, DOC, TN, DTN, NH4-N, NO2-N, NO3-N, TP, DTP, PO4-P, Chl-a를 분석하였다. 이를 우리나라 117개 중권역별 하천수질과 폭염강도와 지속시간을 나타내는 폭염 지수를 산정하여 분석하였다. 폭염 관련 뉴스 데이터는 2013년부터 2019년까지 Python 기반 뉴스 크롤러를 이용해 폭염 취약지수(Heat Wave Vulnerability Index, HWVI)를 기준으로 분류하여 키워드를 수집하였으며 HWVI 중 '기후노출' 키워드와 관련된 기사는 총 22,514건으로 69.9%로 수집되었다. 공간적 영향 평가를 위해 Getis-Ord Gi*를 이용하여 폭염지수와 하천수질인자간 핫스팟 분석을 실시하고 폭염관련 빅데이터가 하천수질에 미치는 영향을 평가하였다. 폭염지수는 낙동강유역 하류에 대해 Chl-a, TN, TP 항목에서 높은 밀도를 보였다. 분석대상지역 내 폭염이 발생한 확률과 반경 밖에서 발생할 확률의 우도비를 분석하기 위해 SaTScan을 이용한 공간검색통계분석을 실시하였다. 분석결과 폭염지수와 DO의 공간상관성이 높은 것으로 나타났다.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.369-376
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• 2019

This paper studies desirable form of future e-government in terms of intelligent government research in response to new intelligent cyber security services in the fourth industrial revolution. Also, the strategic planning of the future e-government has been contemplated in terms of the centralization and intellectualization which are significant characteristics of the fourth industrial revolution. The new system construction which is applied with security analysis technology using big data through advanced relationship analysis is suggested in the paper. The establishment of the system, such as SIEM(Security Information & Event Management), which anticipatively detects security threat by using log information through big data analysis is suggested in the paper. Once the suggested system is materialized, it will be possible to expand big data object, allow centralization in terms of e-government security in the fourth industrial revolution, boost data process, speed and follow-up response, which allows the system to function anticipatively.

• Informatization Policy
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• v.25 no.4
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• pp.108-120
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• 2018

With the rise of the Fourth Industrial Revolution and I-Korea 4.0, both of which pursue strategies for industrial innovation and for the solution to social problems, the real estate industry needs to change in order to make effective use of available space in smart environments. The implementation of smart spaces is a promising solution for this. The smart space is defined as a good use of space, whether it be a home, office, or retail store, within a smart environment. To enhance the use of smart spaces, efficient decision-making and well-timed and accurate interaction are required. This paper proposes a smart space based on platform which takes advantage of emerging technologies for the efficient storage, processing, analysis, and utilization of big data. The platform is composed of six layers - collection, transfer, storage, service, application, and management - and offers three service frameworks: activity-based, market-based, and policy-based. Based on these smart space services, decision-makers, consumers, clients, and social network participants can make better decisions, respond more quickly, exhibit greater innovation, and develop stronger competitive advantages.