• Title/Summary/Keyword: spatial data mining

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Research on regional spatial information analysis platform about NTIS raw data (국가과학기술지식 원시데이터에 관한 지역 공간정보 분석 플랫폼 연구)

  • Lim, Jung-Sun;Kim, Sanggook;Bae, Seoung Hun;Kim, Kwang-Hoon;Won, Dong-Kyu
    • Journal of Cadastre & Land InformatiX
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    • v.50 no.2
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    • pp.21-35
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    • 2020
  • Due to the coronavirus pandemic and diplomatic disputes, governments are actively developing a policy to revitalize·reshore manufacturing and to diversify international cooperations. In order to develop such a policy, it is very important to compare and analyze domestic·international geospatial information. Over the decade, the US·EC governments have conducted a series of national researches to build data-based tools that can monitor·analyze regional geospatial information driven by government R&D investments. In the case of the EC system, it can compare geospatial information in domestic and international(including Korea) regions. Compared to US·EC cases, Korean examples of national researches with available data analplatform need future improvements. Current study is investigating an automated analysis methodologies using "National Institute of Science and Technology Information (NTIS)" DB, which was national security data until recently. Research on data-mining regional geospatial information can contribute to support policy fields that need to discover new issues in response to unexpected social problems such as recently faced corona and trade disputes.

Analysis of the Research Trends by Environmental Spatial-Information Using Text-Mining Technology (텍스트 마이닝 기법을 활용한 환경공간정보 연구 동향 분석)

  • OH, Kwan-Young;LEE, Moung-Jin;PARK, Bo-Young;LEE, Jung-Ho;YOON, Jung-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.20 no.1
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    • pp.113-126
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    • 2017
  • This study aimed to quantitatively analyze the trends in environmental research that utilize environmental geospatial information through text mining, one of the big data analysis technologies. The analysis was conducted on a total of 869 papers published in the Republic of Korea, which were collected from the National Digital Science Library (NDSL). On the basis of the classification scheme, the keywords extracted from the papers were recategorized into 10 environmental fields including "general environment", "climate", "air quality", and 20 environmental geospatial information fields including "satellite image", "numerical map", and "disaster". With the recategorized keywords, their frequency levels and time series changes in the collected papers were analyzed, as well as the association rules between keywords. First, the results of frequency analysis showed that "general environment"(40.85%) and "satellite image"(24.87%) had the highest frequency levels among environmental fields and environmental geospatial information fields, respectively. Second, the results of the time series analysis on environmental fields showed that the share of "climate" between 1996 and 2000 was high, but since 2001, that of "general environment" has increased. In terms of environmental geospatial information fields, the demand for "satellite image" was highest throughout the period analyzed, and its utilization share has also gradually increased. Third, a total of 80 correlation rules were generated for environmental fields and environmental geospatial information fields. Among environmental fields, "general environment" generated the highest number of correlation rules (17) with environmental geospatial information fields such as "satellite image" and "digital map".

Pattern Analysis for Civil Complaints of Local Governments Using a Text Mining (텍스트마이닝에 의한 지자체 민원청구 패턴 분석)

  • Won, Tae Hong;Yoo, Hwan Hee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.3
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    • pp.319-327
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    • 2016
  • Korea faces a wide range of problems in areas such as safety, environment, and traffic due to the rapid economic development and urbanization process. Despite the local governments’ efforts to deal with electronic civil complaints and solve urban problems, civil complaints have been on the increase year by year. In this study, we collected civil complaint data over the last six years from a small and medium-sized city, Jinju-si. In order to conduct a spatial distribution pattern analysis, we indicated the location data on the area through Geocoding after classifying the reasons for civil complaints and then extracted the location data of the civil complaint occurrence spots in order to analyze the correlation between electronic civil complaints and land use. Results demonstrated that electronic civil complaints in Jinju-si were clustered in residential, central commercial, and residential-industrial mixed-use areas—areas where land development had been completed within the city center. After analyzing the civil complaints according to the land use, results revealed that complaints about illegal parking were the highest. Regarding the analysis results of facility distribution within a 50m radius from the civil complaint areas, civil complaints occurred a lot in detached housing areas located within the commercial and residential-industrial mixed-use areas. In the case of residential areas(old downtown), civil complaints were condensed in the areas with many ordinary restaurants. This research explored civil complaints in terms of the urban space and can be expected to be effectively utilized in finding solutions to the civil complaints

Analysis of Dog-Related Outdoor Public Space Conflicts Using Complaint Data (민원 자료를 활용한 반려견 관련 옥외 공공공간 갈등 분석)

  • Yoo, Ye-seul;Son, Yong-Hoon;Zoh, Kyung-Jin
    • Journal of the Korean Institute of Landscape Architecture
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    • v.52 no.1
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    • pp.34-45
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    • 2024
  • Companion animals are increasingly being recognized as members of society in outdoor public spaces. However, the presence of dogs in cities has become a subject of conflict between pet owners and non-pet owners, causing problems in terms of hygiene and noise. This study was conducted to analyze public complaint data using the keywords 'dog,' 'pet,' and 'puppy' through text mining techniques to identify the causes of conflicts in outdoor public spaces related to dogs and to identify key issues. The main findings of the study are as follows. First, the majority of dog-related complaints were related to the use of outdoor public spaces. Second, different types of outdoor public spaces have different spatial issues. Third, there were a total of four topics of dog-related complaints: 'Requesting a dog playground', 'Raising safety issues related to animals', 'Using facilities other than dog-only areas', and 'Requesting increased park management and enforcement related to pet tickets'. This study analyzed the perceptions of citizens surrounding pets at a time when the creation and use of public spaces related to pets are expanding. In particular, it is significant in that it applied a new method of collecting public opinions by adopting complaint data that clearly presents problems and requests.

Service Design for Utilizing Government Information -Focusing on the Case of Gov3.0 Design Group for East North Statistics- (정부 정보의 활용을 위한 서비스디자인 -동북지방통계청의 국민디자인단 사례를 중심으로-)

  • Lee, Yun-Ju;Baek, Su-hyun;Kim, Sun-Ah
    • Journal of Digital Convergence
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    • v.16 no.6
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    • pp.335-341
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    • 2018
  • This study is to innovate policy service development by utilizing beneficiary - centered service design to public information and public data and services that citizens can experience. The Gov 3.0 Design Group operated by the Dongbuk Regional Bureau of Statistics in Daegu in 2015, proposed a 'start-up decision support service' for pre-founders, using data mining on the GIS spatial information held by the Statistical Office and real-time settlement information of credit card companies. For this, service design process and methodology were adopted and participation of various stakeholders. This study suggests that national design activity based on service design is effective in transforming public service based on government information disclosure. It is also worthwhile as an approach that can be considered when the government wants to release or open information or public data in useful form to the public.

Analysis of Manganese Nodule Abundance in KODOS Area (KODOS 지역의 망간단괴 부존률 분포해석)

  • Jung, Moon Young;Kim, In Kee;Sung, Won Mo;Kang, Jung Keuk
    • Economic and Environmental Geology
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    • v.28 no.3
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    • pp.199-211
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    • 1995
  • The deep sea camera system could render it possible to obtain the detailed information of the nodule distribution, but difficult to estimate nodule abundance quantitatively. In order to estimate nodule abundance quantitatively from deep seabed photographs, the nodule abundance equation was derived from the box core data obtained in KODOS area(long.: $154^{\circ}{\sim}151^{\circ}W$, lat.: $9^{\circ}{\sim}12^{\circ}N$) during two survey cruises carried out in 1989 and 1990. The regression equation derived by considering extent of burial of nodule to Handa's equation compensates for the abundance error attributable to partial burial of some nodules by sediments. An average long axis and average extent of burial of nodules in photographed area are determined according to the surface textures of nodules, and nodule coverage is calculated by the image analysis method. Average nodule abundance estimated from seabed photographs by using the equation is approximately 92% of the actual average abundance in KODOS area. The measured sampling points by box core or free fall grab are in general very sparse and hence nodule abundance distribution should be interpolated and extrapolated from measured data to uncharacterized areas. The another goal of this study is to depict continuous distribution of nodule abundance in KODOS area by using PC-version of geostatistical model in which several stages are systematically proceeded. Geostatistics was used to analyse spatial structure and distribution of regionalized variable(nodule abundance) within sets of real data. In order to investigate the spatial structure of nodule abundance in KODOS area, experimental variograms were calculated and fitted to a spherical models in isotropy and anisotropy, respectively. The spherical structure models were used to map out distribution of the nodule abundance for isotropic and anisotropic models by using the kriging method. The result from anisotropic model is much more reliable than one of isotropic model. Distribution map of nodule abundance produced by PC-version of geostatistical model indicates that approximately 40% of KODOS area is considered to be promising area(nodule abundance > $5kg/m^2$) for mining in case of anisotropy.

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Spacio-temporal Analysis of Urban Population Exposure to Traffic-Related air Pollution (교통흐름에 기인하는 미세먼지 노출 도시인구에 대한 시.공간적 분석)

  • Lee, Keum-Sook
    • Journal of the Economic Geographical Society of Korea
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    • v.11 no.1
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    • pp.59-77
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    • 2008
  • The purpose of this study is to investigate the impact of traffic-related air pollution on the urban population in the Metropolitan Seoul area. In particular, this study analyzes urban population exposure to traffic-related particulate materials(PM). For the purpose, this study examines the relationships between traffic flows and PM concentration levels during the last fifteen years. Traffic volumes have been decreased significantly in recent year in Seoul, however, PM levels have been declined less compare to traffic volumes. It may be related with the rapid growth in the population and vehicle numbers in Gyenggi, the outskirt of Seoul, where several New Towns have been developed in the middle of 1990's. The spatial pattern of commuting has changed, and thus and travel distances and traffic volumes have increased along the main roads connecting CBDs in Seoul and New Towns consisting of large residential apartment complexes. These changes in traffic flows and travel behaviors cause increasing exposure to traffic-related air pollution for urban population over the Metropolitan Seoul area. GIS techniques are applied to analyze the spatial patterns of traffic flows, population distributions, PM distributions, and passenger flows comprehensively. This study also analyzes real time base traffic flow data and passenger flow data obtained from T-card transaction database applying data mining techniques. This study also attempts to develop a space-time model for assessing journey-time exposure to traffic related air pollutants based on travel passenger frequency distribution function. The results of this study can be used for the implications for sustainable transport systems, public health and transportation policy by reducing urban air pollution and road traffics in the Metropolitan Seoul area.

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Construction of 3D Geospatial Information for Development and Safety Management of Open-pit Mine (노천광산 개발 및 안전관리를 위한 3차원 지형정보 구축 및 정확도 분석)

  • Park, Joon Kyu;Jung, Kap Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.1
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    • pp.43-48
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    • 2020
  • Open pit mines for limestone mining require rapid development of technologies and efforts to prevent safety accidents due to rapid deterioration of the slope due to deforestation and rapid changes in the topography. Accurate three-dimensional spatial information on the terrain should be the basis for reducing environmental degradation and safe development of open pit mines. Therefore, this study constructed spatial information about open pit mine using UAV(Unmanned Aerial Vehicle) and analyzed its utility. images and 3D laser scan data were acquired using UAV, and digital surface model, digital elevation model and ortho image were generated through data processing. DSM(Digital Surface Model) and ortho image were constructed using image obtained from UAV. Trees were removed using 3D laser scan data and numerical elevation models were produced. As a result of the accuracy analysis compared with the check points, the accuracy of the digital surface model and the digital elevation model was about 11cm and 8cm, respectively. The use of three-dimensional geospatial information in the mineral resource development field will greatly contribute to effective mine management and prevention of safety accidents.

A Study on Correlation Analysis of One-Person Housing Space Design Convergence Contents by Using Social Network Analysis (소셜 네트워크 분석 방법론을 활용한 1인 주거공간디자인 융합콘텐츠 상관관계 분석)

  • Park, Eun Soo;Kim, Ji Eun
    • Korea Science and Art Forum
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    • v.34
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    • pp.133-148
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    • 2018
  • Korea's housing structure is predicted that one-person housing will be the most common type of housing in Korea. Therefore, this study intends to derive contents for designing a one-person housing space considering the life of a rapidly increasing one-person householder. For this purpose, this study objectively derives the social, economic and cultural influencing factors of one-person households through big data analysis, and analyzed the correlation between contents using social network analysis methodology. In this paper, 60 core contents related to one person housing space were derived by applying big data analysis methodology. And through social network analysis, the most influential contents were derived from the space editing and space composition categories. This means that the residential space is an important part of the design idea that can flexibly respond to changes in the user's life. Based on this study, future research will focus on the concept and design methodology of one-person housing space.

Development of System for Real-Time Object Recognition and Matching using Deep Learning at Simulated Lunar Surface Environment (딥러닝 기반 달 표면 모사 환경 실시간 객체 인식 및 매칭 시스템 개발)

  • Jong-Ho Na;Jun-Ho Gong;Su-Deuk Lee;Hyu-Soung Shin
    • Tunnel and Underground Space
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    • v.33 no.4
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    • pp.281-298
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    • 2023
  • Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.