• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.269-275
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• 2013

Recently, importance of pedestrian road network is getting emphasized as it is possible to provide mobile device users with both route guidance services and surrounding spatial information. However, it costs a tremendous amount of budget for generating and renovating pedestrian road network nationally, which hinder further advances of these services. Hence, algorithms extracting pedestrian road network automatically based on raster data are needed. On the other hand, road dataset generated from raster data usually has unnecessary vertices which lead to maintenance disutility such as excessive turns and increase in data memory. Therefore, this study proposed a method of selecting a proper threshold automatically for separate road entity using not only Douglas-Peucker algorithm but also road attribute data of digital map in order to remove redundant vertices, which maximizes line simplification efficiency and minimizes distortion of shape of roads simultaneously. As a result of the test, proposed method was suitable for automatic line simplification in terms of reduction ratio of vertices and accuracy of position.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.133-139
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• 2021

Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.623-633
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• 2020

As the time spent in indoor space has increased, the demand for services targeting indoor spaces also continues to increase. To provide indoor spatial information services, the construction of indoor spatial information should be done first. In the study, a method of generation IndoorGML, which is the international standard data format for Indoor space, from existing BIM data. The characteristics of IFC objects were investigated, and objects that need to be converted to IndoorGML were selected and classified into objects that restrict the expression of Indoor space and internal passages. Using the proposed method, a part of data set provided by the BIMserver github and the IFC model of the 21st Century Building in University of Seoul were used to perform experiments to generate PrimalSpaceFeatures of IndoorGML. As a result of the experiments, the geometric information of IFC objects was represented completely as IndoorGML, and it was shown that NavigableBoundary, one of major features of PrimalSpaceFeatures in IndoorGML, was accurately generated. In the future, the proposed method will improve to generate various types of objects such as IfcStair, and additional method for automatically generating MultiLayeredGraph of IndoorGML using PrimalSpaceFeatures should be developed to be sure of completeness of IndoorGML.

• Korean Journal of Remote Sensing
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• v.19 no.4
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• pp.319-328
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• 2003

The automatic analysis of high-resolution satellite image is important in cartography, surveillance, exploiting resources etc. However, the automatic analysis of high resolution satellite image in the urban area has lots of difficulty including a shadow, the difference of illumination with time, the complexity of image so that the present techniques are seemed to be impossible to resolve. This paper proposes a new way of change detection of building objects in urban area, in which the objects in digital vector map are designated and superimposed on the the high-resolution satellite image. The proposed way makes the buildings on the vector map parameterize, and searches them in the preprocessed high-resolution satellite image by using generalized Hough transform. The designated building objects are overlaid on the satellite image and the result can help to search the changes in building objects rapidly.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.1-30
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• 2013

The capitalization of know-how, knowledge management, and the control of the constantly growing information mass has become the new strategic challenge for organizations that aim to capture the entire wealth of knowledge (tacit and explicit). Thus, knowledge mapping is a means of (cognitive) navigation to access the resources of the strategic heritage knowledge of an organization. In this paper, we present a new mapping approach based on the Boolean modeling of critical domain knowledge and on the use of different data sources via the data mining technique in order to improve the process of acquiring knowledge explicitly. To evaluate our approach, we have initiated a process of mapping that is guided by machine learning that is artificially operated in the following two stages: data mining and automatic mapping. Data mining is be initially run from an induction of Boolean case studies (explicit). The mapping rules are then used to automatically improve the Boolean model of the mapping of critical knowledge.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.67-72
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• 2003

We have seen rapid changes in road systems and networks in urban areas due to fast urbanization and increased traffic demands. As a result, many researchers have put greater importance on extraction, correction and updating of information about road systems. Also, by using the various data on road systems and its condition, we can manage our road more efficiently and economically. Furthermore, such information can be used as input for digital map and GIS analysis. In this research, we used a high resolution aerial photo of the roads in Seongnam area. First, we applied the top-hat filter to the area of interest so that the road markings could be extracted in an efficient manner. The lane separation lines were selected, considering the shape similarity between the selected lane separation line and reference data. Next, we extracted the roads in the urban area using the aforementioned road marking. Using this technique, we could easily extract roads in urban area in semi-automatic way.

• 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.483-491
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• 2013

By a development of car navigation systems and mobile or positioning technology, it increases interest in location based services, especially pedestrian navigation systems. Updating of digital maps is important because digital maps are mass data and required to short updating cycle. In this paper, we proposed change detection for different network data-sets based on areal feature matching. Prior to change detection, we defined type of updating between different network data-sets. Next, we transformed road lines into areal features(block) that are surrounded by them and calculated a shape similarity between blocks in different data-sets. Blocks that a shape similarity is more than 0.6 are selected candidate block pairs. Secondly, we detected changed-block pairs by bipartite graph clustering or properties of a concave polygon according to types of updating, and calculated Fr$\acute{e}$chet distance between segments within the block or forming it. At this time, road segments of KAIS map that Fr$\acute{e}$chet distance is more than 50 are extracted as updating road features. As a result of accuracy evaluation, a value of detection rate appears high at 0.965. We could thus identify that a proposed method is able to apply to change detection between different network data-sets.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.3
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• pp.303-312
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• 2005

Digital map, DEM and orthophoto were produced by using PC based digital photogrammetric system and aerial photo images that were obtained with scale of 1/5,000 and scanning density of 1200dpi and 600dpi, and the accuracies of these outputs were evaluated by various methods. Non-skilled operator produced digital map with PC based digital photogrammetric system and aerial photo images scanned by 1200dpi. The results showed that it was impossible to insert contour lines, but the rest elements could be drawn with the accuracy of 1/1,000. In automatic generation of DEM, scanning density of aerial photo and grid interval of DEM didn't affect the accuracy of DEM. In production of orthophoto, we could know that the larger grid interval of DEM, the lower accuracy of orthophoto, but scanning density of original image had more effect on quality of orthophoto. By the way, accuracy comparison between orthophoto and digital map with same check points showed that orthophoto was more accurate than digital map, and orthophoto could be used in more diverse areas. Hereafter in civilian part, aerial photo image and PC based digital photogrammetric system could make practical application of data correction and update in GIS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.151-159
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• 2004

The diversity, expansion of human activity and rapid urbanization make modem society to faced with problems like damage of nature and drain of natural resources. Under these circumstances rapid and accurate change detection techniques, which can detect wide range utilization changes, are needed for efficient management and utilization plan of national territory. In this study to perform change detection from remote sensing images, space analysis technique contained in Geographic Information System is applied. And from this technique, the software. that can execute new change detection algorithm, query, inquiry and analysis, is produced. This software is on the basis of graphic user interface and has many functions such as format conversion, grid calculation, statistical processing, display and reference. In this study, simultaneously change detection for multi-temporal satellite images can be performed and integrated one change image about four different periods was produced. Further more software user can acquire land cover change information for an specific area through querying and questioning about yearly changes. Finally making of every application module for change detection into one window based visual basic program, can be produced user convenience and automatic performances.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.417-424
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• 2006

Despite of many researches related to create 3D digital maps, it is still time-consuming and costly because a large part of 3D digital mapping is conducted manually. To circumvent this limitation, we proposed methodologies to create 3D digital maps with 3D symbols automatically. For this purpose, firstly, the 3D symbol library to represent 3D objects as 3D symbols was constructed. In this library, we stored the attribute and geometry information of 3D objects which define types and shapes of symbols respectively. These information were used to match 3D objects with 3D symbols and extracted from 2D digital maps and LiDAR(Light Detection and Ranging) data. Then, to locate 3D symbols into a base map automatically, we used predefined parameters such as the size, the height, the rotation angle and the center of gravity of 3D objects which are extracted from LiDAR data. Finally, the 3D digital map in urban area was constructed and the results were tested. Through this research, we can identify that the developed algorithms can be used as effective techniques for 3D digital mapping.