• Journal of the Korean association of regional geographers
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• v.15 no.2
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• pp.307-315
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• 2009

The purpose of map generalization is a method of map making to transmit the concise cartographic representation and geographic meaning. New generalization algorithm has been developed to be applied in the digital environments by the development of computer cartography. This study aims to look into possibilities of the multiscale mapping by generalization in application with the coordinate transformation and LoD(level of detail) in the web cartography. A method of the coordinate transformation is to improve a transmission of spatial data. Lod is a method which is making web map with selection spatial data by zoom level of users. Layers for test constructed contour line, stream network, the name of a place, a summit of mountain, and administrative office. The generalization was applied to zoom levels by scale for the linear and polygonal features using XML-Based scalable vector graphics(SVG). Resultantly, storage capacity of data was minimized 41% from 9.76mb to 4.08mb in SVG. Generalization of LoD was applied to map elements by stages of the zoom level. In the first stages of zoom level, the main name of places and administrative office, higher order of stream channels, main summit of mountain was represented, and become increase numbers of map elements in the higher levels. Results of this study can help to improve esthetic map and data minimization in web cartography, and also need to make an efforts to research an algorithm on the map generalization over the web.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.7-21
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• 2019

In order to improve the edge segmentation effect of the level set image segmentation and avoid the influence of the initial contour on the level set method, a saliency level set image segmentation model based on local Renyi entropy is proposed. Firstly, the saliency map of the original image is extracted by using saliency detection algorithm. And the outline of the saliency map can be used to initialize the level set. Secondly, the local energy and edge energy of the image are obtained by using local Renyi entropy and Canny operator respectively. At the same time, new adaptive weight coefficient and boundary indication function are constructed. Finally, the local binary fitting energy model (LBF) as an external energy term is introduced. In this paper, the contrast experiments are implemented in different image database. The robustness of the proposed model for segmentation of images with intensity inhomogeneity and complicated edges is verified.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.289-297
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• 2006

The Land Cover/Land Use Map have been constructed from 1998, which has hierarchical structure according to land cover/land use system. Level 1 classification Map have done using Landsat satellite image over whole Korean peninsula. Level II classification Map have been digitized using IRS-1C, 1D, KOMPSAT and SPOT5 satellite images resolution-merged with low resolution color images. Level II Land Cover/Land Use Map construction by digitizing method, however, is consuming enormous expense for satellite image acquisition, image process and Land Cover/Land Use Map construction. In this paper, the possibility of constructing Level II Land Cover/Land Use Map using hyperspectral satellite image of EO-1 Hyperion, which is studied a lot recently, is studied. The comparison of classifications using Hyperion satellite image offering more spectral information and Landsat-7 ETM+ image is performed to evaluate the availability of Hyperion satellite image. Also, the algorithm of the optimal band selection is presented for effective application of hyperspectral satellite image.

• Journal of the Korean School Mathematics Society
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• v.21 no.4
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• pp.327-342
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• 2018

The purpose of this paper is to review the domestic research on mathematical modeling by using three dimensional mathematical modeling map composed of perspective axis, domain axis, level axis, and to give direction to mathematical modeling research. The findings of this study show that the domestic research on mathematical modeling focuses on application perspective, notions and classroom domain and secondary level, and that we need various studies with concept formation perspective, system domain, tertiary level, and teacher(education) level on the future work about mathematical modeling.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.3-8
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• 2011

In April 2010, Japan Cabinet Office has published the first countermeasure report for severe flood disasters. This report showed various flood-disaster scenarios and factors that widened damages. One of important suggestions was to transmit precious information for long-distance evacuation. So far, local municipalities have made Flood Hazard Map to inform resident risk and evacuation. In this paper, cognition and effectiveness of a flood hazard map in the down ARAKAWA river Tokyo were measured by social questionnaire survey. In conclusion, there were 3 factors to effect validity of a flood hazard map. There were (1) commitment to their neighborhood organization, (2) experience of Kathleen typhoon in 1947 and (3) level of using targeted river. As results, a logical diagram about a flood hazard map perception was drawn and discussed from a view of community-based approach.

• Spatial Information Research
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• v.15 no.1
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• pp.67-80
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• 2007

The land cover map represent the state of earth surfaces. It can be used as basic data to explore present conditions of earth surfaces and develop future plans for local areas. To produce the land cover map with efficiency, gathering geographic information from satellite images is important. Exporting, building, and managing processes on the land cover information are needed as well. In this study we aim to review the producing process of the level-2 land cover map in detail and enhance it. h present status of the producing process of the land cover map in Korea is reviewed, problems of the process are explored, and measures for improving it are proposed. The criteria for fixing boundaries and providing attributes for the land cover map are proposed. This proposed criteria may solve problems in a present producing process. The improving measures proposed in this study should be continuously revised in future studies.

• Spatial Information Research
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• v.23 no.3
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• pp.1-10
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• 2015

Due to recent improvement of various sensor technologies, indoor positioning becomes available. However, Indoor positioning technologies by Wi-Fi radio map and acceleration sensor and digital campus still have a certain level of errors and a number of researches have been done to increase the positioning accuracy of the indoor positioning. If we could provide a room level accuracy, indoor location based services with current indoor positioning methods such as Wi-Fi radio map and acceleration sensors would be possible. In this paper, we propose an indoor map matching method to provide a room level accuracy based on hidden markov model.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.108-114
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• 2015

Automated driving systems require a high level of performance regarding environmental perception, especially in urban environments. Today's on-board sensors such as radars or cameras do not reach a satisfying level of development from the point of view of robustness and availability. Thus, map data is often used as an additional data input to support these systems. An accurate digital map is used as a powerful additional sensor. In this paper, we propose a new approach for vehicle localization using a lane map and a single-layer LiDAR. The maps are created beforehand using a highly accurate DGPS and a single-layer LiDAR. A pose estimation of the vehicle was derived from an iterative closest point (ICP) match of LiDAR's intensity data to the lane map, and the estimated pose was used as an observation inside a Kalmanfilter framework. The achieved accuracy of the proposed localization algorithm is evaluated with a highly accurate DGPS to investigate the performance with respect to lateral vehicle control.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.381-386
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• 2006

Currently, 1/5,000 Digital Topographic Map covers the whole country with administrative boundary of Gu, while some region has already been constructed with 1/1,000 digital topographic map has legal boundary of Dong. Here, Dong in 1/1,000 scale represents the legal boundary which is used in the address most of time. Therefore, there is no administrative-Dong yet although it is very useful in various fields. In this study, we suggested a method to construct the administrative boundary extending to the level of Dong empirically. In addition, the practical application of the administrative boundary in GIS is discussed. Two methods are applied to construct the administrative boundary to the level of administration-Dong; using the edited cadastral map and the digital topographic map. When the edited cadastral map is used, some problems such as boundary discordance to superordinate administrative area is appeared. On the other hand, using digital topographic map showed simple construction processes and easy connection with other framework data. Therefore, it is recommended that the digital topographic map should be used in the construction of the administrative boundary It would be useful as framework data in various industries and public operations.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.587-598
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• 2022

To increase building change recognition accuracy, we present a deep learning-based building change detection using remote sensing images. In the proposed approach, by merging pixel-level and object-level information of multitemporal remote sensing images, we create the difference image (DI), and the frequency-domain significance technique is used to generate the DI saliency map. The fuzzy C-means clustering technique pre-classifies the coarse change detection map by defining the DI saliency map threshold. We then extract the neighborhood features of the unchanged pixels and the changed (buildings) from pixel-level and object-level feature images, which are then used as valid deep neural network (DNN) training samples. The trained DNNs are then utilized to identify changes in DI. The suggested strategy was evaluated and compared to current detection methods using two datasets. The results suggest that our proposed technique can detect more building change information and improve change detection accuracy.