• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.23 no.4
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• pp.204-217
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• 2018

This study proposes a cost-effective method to monitor coastal environments using e-Navigation-implemented domestic and international ferries, and to analyze big data of records such as wind, temperature, salinity, waves, and currents that are gathered through e-Navigation system. First, we present the concept and architecture of e-Navigation operation system based on the General Information Center on Maritime Safety and Security. Then, the marine observation system that can be applied to ferries operating in our nation's territory is discussed. Analytical methods, such as spatio-temporal mixed effects model, ensemble method, and meshfree method, in handling real-time big data obtained by the e-Navigation observing system are then explained in detail. This study will support the implementation of the Korean e-Navigation project that focuses on the safety of small vessels such as coasters and fishing vessels.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.130-145
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• 2021

As part of the Smart Seoul policy, the importance of using big urban data is being highlighted. Furthermore interest in the impact of transportation-related urban environmental factors such as PM10 and noise on citizen's quality of life is steadily increasing. This study established the integrated DB by matching IoT big data with transportation data, including traffic volume and speed in the microscopic Spatio-temporal scope. This data analyzed the impact of a spatial unit in the road-effect zone on environmental risk level. In addition, spatial units with similar characteristics of road traffic and environmental factors were clustered. The results of this study can provide the basis for systematically establishing environmental risk management of urban spatial units such as PM10 or PM2.5 hot-spot and noise hot-spot.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.833-836
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• 2017

최근 블랙박스 및 CCTV 같은 영상 촬영 장치가 보편화되면서, 방대한 양의 영상 데이터가 실시간으로 생성되고 있다. 만약 이 대용량 데이터 안의 차량 정보를 추출할 수 있다면 범죄 차량 추적, 교통 혼잡도 측정 등의 활용이 가능할 것이다. 이를 구현하기 위해서는 수많은 자동차에서 실시간으로 생성되는 영상 데이터를 처리할 수 있는 시스템이 필수적이나, 이러한 시스템을 찾기 힘든 것이 현실이다. 이를 위해 이 논문에서는 아파치 카프카, Hbase를 이용한 영상 빅데이터 처리 시스템을 제안한다. 아파치 카프카는 시스템 내에서 영상 손실이 없는 전송과 영상 처리 노드의 스케줄링을 수행하며, Hbase는 처리된 데이터를 테이블로 저장하고 사용자가 보낸 쿼리를 처리한다. 더불어, Hbase에 인덱스를 구성하여 빠른 쿼리 처리가 가능하도록 만든다. 실험 결과, 제안된 시스템은 인덱스가 없을 때보다 뛰어난 쿼리 처리 성능을 보이는 것을 확인할 수 있었다.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.773-776
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• 2020

웹 뉴스 기사는 태풍과 같은 재해 발생상황에 대한 신속하고 정확한 정보를 포함하고 있다. 예를 들어, 태풍의 발생시점, 이동·예측경로, 피해·사고 현황 등 유용한 정보를 텍스트, 이미지, 동영상의 형태로 관련 상황정보를 전달한다. 그러나 대부분의 재해재난 관련 뉴스 기사는 특정 시점의 정보만을 웹페이지 형태로 제공하므로, 시계열 측면의 연결성을 지니는 기사들에 대한 정보를 전달하기 어렵다. 또한 시간적 변화에 따라 기사 내용에 포함된 장소, 지역, 건물 등의 지명에 대한 공간적 정보를 지도와 연계하여 정보를 전달하는데 한계가 있어, 시공간적 변화에 따른 특정 재해재난 상황정보에 대한 전체적인 현황파악이 어렵다. 따라서, 본 논문에서는 데이터 시각화 측면에서 이러한 한계를 극복하기 위해, 1) 웹크롤링을 통해 구축된 뉴스 빅데이터를 자연어 처리를 통해 태풍과 관련된 뉴스 기사들을 추출하였고, 2) 시공간적 관련 정보를 지식그래프로 구축하였고, 이를 통해 최근 발생한 태풍 사건들과 관련된 뉴스 정보를 시계열 특성을 고려하여 3) 인터렉티브 지도 기반의 태풍 상황정보를 시각화하는 방안을 연구하였다.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.321-327
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• 2017

China is experiencing the urbanization at an unprecedented speed and scale in human history. The continuing growth of China's big cities, both in city land and population, has already led to great challenges in China's urban planning and construction activities, such as the continuous increase of construction and demolition (C&D) waste. Therefore, how to characterize cities' construction activities, particularly dynamically quantify the flows of building materials and construction debris, has become a pressing problem to alleviate the current shortage of resources and realize urban sustainable development. Accordingly, this study is designed to employ 4D-GIS (four dimensions-Geographic Information System) and Internet Plus to offer new approach for accurate but dynamic C&D waste management. The present study established a spatio-temporal pattern and material metabolism evolution model to characterize the geo-distribution of C&D waste by combing material flow analysis (MFA) and 4D-GIS. In addition, this study developed a mobile application (APP) for C&D waste trading and information management, which could be more effective for stakeholders to obtain useful information. Moreover, a cloud database was built in the APP to disclose the flows of C&D waste by the monitoring information from vehicles at regional level. To summarize, these findings could provide basic data and management methods for the supply and reverse supply of building materials. Meanwhile, the methodologies are practical to C&D waste management and beyond.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.90-104
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• 2015

The purpose of this paper is to build a spatio-temporal evapotranspiration(ET) estimation model using Terra MODIS satellite image and by calibrating with the flux tower ET data from watershed. The fundamentals of spatial ET model, Surface Energy Balance Algorithm for Land(SEBAL) was adopted and modified to estimate the daily ET of Yongdam Dam watershed in South Korea. The daily Normalized Distribution Vegetation Index(NDVI), Albedo, and Land Surface Temperature(LST) from MODIS and the ground measured wind speed and solar radiation data were prepared for 2 years(2012-2013). The SEBAL was calibrated with the forest ET measured by Deokyusan flux tower in the study watershed. Among the model parameters, the important parameters were surface albedo, NDVI and surface roughness in order for momentum transport during calculation of sensible heat flux. As a result of the final calibration, the monthly averaged albedo and NDVI were used because the daily values showed big deviation with unrealistic change. The determination coefficient($R^2$) between SEBAL and flux data was 0.45. The spatial ET reflected the geographical characteristics showing the ET of lowland areas was higher than the highland ET.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.499-509
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• 2016

The occurrence of sand dust has been steadily increased since 1990 and the amount of damage was also increased. In most of previous studies, ground based observations were used for sand dust analyses, but its high spatio-temporal variability has not been well understood. In this study, satellite aerosol observations were used to overcome current limitations of the sand dust variability in space and time and to estimate associations with morbidity of respiratory and cardiovascular ailments. In general, high AODs were observed in the west part of the Koran peninsula in spring. The reasonable associations between the morbidity and sand dust were observed from April to July with highest positive correlation (~0.6) at three month lags (lag 3). Based on the results, we found a utility of the satellite aerosol observations for sand dust analyses by considering of morbidity effects. In addition, health effect against the sand dust is proved to be examined and smooth medical supplies and prevention of undesired medical expenses would be possible.