• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_1
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• pp.493-502
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• 2013

For various geospatial information such as planimetric and topographic features, the required accuracy may be defined depending on the purpose of GIS applications. Also, the accuracy of the geospatial information have a major impact on the quality of the raw surveying data. In order to be usefully applied the precise geospatial information, the accuracy standards must be appropriately set so that the digital map as base map can be accurately made. Before computer mapping and GIS technology existed, paper maps were drawn by hand. So, the map scale was a significant contributor to the map accuracy. As such the past, the accuracy of maps is determined the scale at which the map would be drawn, but recent trends are to treat accuracy as a one of quality elements, rather than a specification for producing the map. Therefore, the purpose of this paper is to set the new korean map accuracy standards appropriate for the construction and application of the precise geospatial information on behalf of the current representation of korean digital maps.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.121-127
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• 2017

Recently, it has been actively Semantic Web studies for 2-dimensional data of the spatial data. 2-dimensional Semantic Web, are fused existing Geospatial Web and the Semantic Web, and integrate with the efficient cooperation of the vast non-spatial information on a variety of geospatial information and general Web, it is possible to provide it is a Web services technology of intelligent geographic information. However, in the research for multi-dimensional data processing, and in those who are missing overall, relevant standards also not been enacted. Therefore, in this paper, by applying a variety of base of the theory and technology related to this to take place the Ontology processing technology, multi-dimensional data processing is possible ontology, question, and suggested the contents of the reasoning. Also, we tried to apply what you have proposed respectively to the multi-dimensional query virtual scenario necessary.

• Journal of the Korean Geographical Society
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• v.47 no.6
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• pp.955-974
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• 2012

This study investigated six teachers who used the lessons utilizing geospatial technologies including GPS and Google Earth. The lessons were designed to ask students to solve problems with the technologies rather than to teach students to just use technology and teachers to function more as a facilitator. Key findings include: (1) The teachers with background and interest in learner-centered teaching were more effective in implementing the lessons with their students while the teachers who were familiar with teacher-centered instruction often reduced learners' roles in the lesson; (2) Generally, students expressed huge interests in the lessons. Changes in attitude and participation toward lessons were more clearly observed from low achievers and passive learners; (3) Key influencing factors in adoption of lessons utilizing geospatial technologies were school culture toward innovativeness, characteristics of school administrators, learning experience of the lessons during the workshops, and support systems for lesson preparation and implementation.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.15-27
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• 2020

Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster-Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future social services and amenities for the local inhabitants.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.744-749
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• 2018

Informatization and visualization technology for real space is a key technology for construction of geospatial information. Three-dimensional (3D) modeling is a method of constructing geospatial information from data measured by various methods. The 3D laser scanner has been mainly used as a method for acquiring digital elevation data. On the other hand, the unmanned aerial vehicle (UAV), which has been attracting attention as a promising technology of the fourth industrial revolution, has been evaluated as a technology for obtaining fast geospatial information, and various studies are being carried out. However, there is a lack of evaluation on the quantitative work efficiency and data accuracy of the data construction technology for 3D geospatial modeling. In this study, various analyses were carried out on the characteristics, work processes, and accuracy of point cloud data acquired by a 3D laser scanner and an unmanned aerial vehicle. The 3D laser scanner and UAV were used to generate digital elevation data of the study area, and the characteristics were analyzed. Through evaluation of the accuracy, it was confirmed that digital elevation data from a 3D laser scanner and UAV show accuracy within a 10 cm maximum, and it is suggested that it can be used for spatial information construction. In the future, collecting 3D elevation data from a 3D laser scanner and UAV is expected to be utilized as an efficient geospatial information-construction method.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.917-927
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• 2020

The Ministry of Land, Infrastructure and Transport of Korea is developing a CAS 500-1/2 satellite capable of photographing a GSD 0.5 m level image, and is developing a technology to utilize this. Therefore, this study attempted to develop a geospatial feature extraction technique aimed at automation as a technique for utilizing CAS 500-1/2 satellite images. KOMPSAT-3A satellite images that are expected to be most similar to CAS 500-1/2 were used for research and the possibility of automation of geospatial feature extraction was analyzed through relative radiometric normalization. For this purpose, the parameters and thresholds were applied equally to the reference images and relative radiometric normalized images, and the geospatial feature were extracted. The qualitative analysis was conducted on whether the extracted geospatial feature is extracted in a similar form from the reference image and relative radiometric normalized image. It was also intended to analyze the possibility of automation of geospatial feature extraction by quantitative analysis of whether the classification accuracy satisfies the target accuracy of 90% or more set in this study. As a result, it was confirmed that shape of geospatial feature extracted from reference image and relative radiometric normalized image were similar, and the classification accuracy analysis results showed that both satisfies the target accuracy of 90% or more. Therefore, it is believed that automation will be possible when extracting spatial objects through relative radiometric normalization.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.2 s.8
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• pp.123-136
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• 1996

Lately, the demand for data standardization become increased to obtain various data jointly along with development of information technology and diversity of society. Thus the research on tile definition and evaluation of data quality indicating accuracy and confidence of geospatial data, is required for this standardization. In this study, by virtue of comparison of definitions and evaluation methods of data quality element being selected from representative countries, the following results were obtained: (1) Application of ISO/TC211's Draft having accepted evaluation standard to KSDTS(Korea Spatial Data Transfer Standard) is desirable for definitions of data quality elements. (2) This study presented the quality evaluation of much more resonable geospatial data accompaning with quality element. Furthermore, this study suggests that this evaluation be applicable to KSDTS and be contained in the digital map product specification of National Geography Institute with more clearness of a report form of data quality evaluation result. (3) Studies on various sampling methods, establishment of AQL(Acceptable Quality Level) suitable for our country, and computer programming which can rapidly and automatically evaluate mass much of data are required.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.1-15
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• 2020

As cities expand and underground utilities construction projects increase, there is an urgent need for a technology capable of analyzing the underground utilities network in 3D. Since 2015, 3D Underground Geospatial Map project, that has been integrating 15 types of underground information such as underground utilities, underground structures, and ground information, is in progress in S. Korea. However, the construction of 3D underground facilities is currently based on manual work and the logic for building a 3D model is very complicated. And it takes a lot of time and cost to process millions of large amounts of data per local governments. By presenting a framework on the processing and partial updating of the 3D underground utilities model, this paper aims to establish a plan to quickly build a 3D underground utility model at a minimum cost. The underground utilities processing and partial update automation technologies developed in this study are expected to be immediately applied to the 3D Underground Geospatial Map project.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.3
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• pp.393-400
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• 2009

Recently demand for the 3D modeling technology to reconstruct real world is getting increasing. However, existing geospatial data are mainly based on the 2D space. In addition, most of the geospatial data provide geometric information only. In consequence, there are limits in various applications to utilize information from those data and to reconstruct the real world in 3D space. Therefore, it is required to develop efficient 3D mapping methodology and data for- mat to establish geospatial database. Especially digital elevation model(DEM) is one of the essential geospatial data, however, DEM provides only spatially distributed 3D coordinates of the natural and artificial surfaces. Moreover, most of DEMs are generated without considering terrain properties such as surface roughness, terrain type, spatial resolution, feature and so on. This paper suggests adaptive and flexible geospatial data format that has possibility to include various information such as terrain characteristics, multiple resolutions, interpolation methods, break line information, model keypoints, and other physical property. The study area was categorized into mountainous area, gently rolling area, and flat area by taking the terrain characteristics into account with respect to terrain roughness. Different resolutions and interpolation methods were applied to each area. Finally, a 3D digital map derived from aerial photographs was integrated with the geospatial data and visualized.

• 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".