• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.313-316
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• 2003

Growing urban areas modify patterns of local land use and land cover. Land use changes associated with an urban area can be extensive. One way to understand and document land use change and urbanization is to establish benchmark maps compiled from satellite imagery The use of satellite imagery for monitoring urban growth has been widely demonstrated. Multi-temporal LANSAT TM image data has created the potential for monitoring urban change and land cover identification. In this study, for extracting urban boundary GLCM method and visual interpretation were used in CORONA imagery and SPOT imagery.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.259-266
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• 2015

Change detection using the heterogeneous data such as aerial images, aerial LiDAR (Light Detection And Ranging), and satellite images needs to be developed to efficiently monitor the complicating land use change. We approached this problem not relying on the intensity value of the geospatial image, but by using RECC(Relative Edge Cross Correlation) which is based on the edge information over the urban and suburban area. The experiment was carried out for the aerial LiDAR data with high-resolution Kompsat-2 and −3 images. We derived the optimal window size and threshold value for RECC-based change detection, and then we observed the overall change detection accuracy of 80% by comparing the results to the manually acquired reference data.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.156-158
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• 2003

Analysis of high-resolution satellite image becomes important for cartography, surveillance, and remote sensing. However, there are lots of problems to be solved for automatic analysis of high-resolution satellite image especially in urban area. The problems are originated from the increased complexity due to the unnecessary details and shadows, and time-varying illuminations. Because of such obstacles, it seems impossible to make automatic analysis. This paper proposes a way of change detection of buildings in urban area by using digital vector map. The proposed way makes the buildings on the vector map parameterized, and searches them in the preprocessed high-resolution image by using generalized Hough transform. The searched building objects are overlaid on the satellite image. The overlaid image can help to detect the change of building rapidly.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.131-137
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• 2004

This study presents the application of multi-temporal aerial photographs in detecting change in a small urban area. For the panchromatic aerial images of the scale of 1/20000 and 1/37500 photographed in 1987, 1996 and 2000, image geometric correction and registration were carried out before performing change detection in a common reference system and then image mosaicking. The image differencing technigue was employed to detect urban features and landcover change and then the results were compared to those of image ratioing techniques. Also threshold values were suggested in applying image differencing for change detection.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.2 no.3
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• pp.38-46
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• 1999

The purpose of the study is to analyze the effect of urbanization, the degree of development in urban scale and the comparative analysis of landuse change in order to construct the important basic data for establishing development direction and characterizing each city. To analyze the urban growth patterns a land cover classification using Landsat TM data was performed : 1987 and 1997 for the change detection of each land cover. The results of this study demonstrates that urban areas increased on while forest areas had decreased all over the Korean cities. Especially, in case of the analysis on landuse conversion rate, we found out that the forest areas was first changed into agricultural areas, then it is consequently developed into urban areas in most rural areas. This study concludes that the insufficiency of the number of knowledged officials in the local administration and a government official in one's charge, tight financial conditions and absence of recognition of cities' characteristics, urban development following unrefined development patterns, inappropriate urban planning and policy of metropolitan cities and the negligence of peculiar development patterns of each city.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1727-1737
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• 2018

In this paper, we propose a system to detect spatial structures in land cover maps and to detect time-series spatial structure changes. At first, the proposed system detects patches in a certain area at different times and calculates their measures to analyse spatial structure patterns of the area. Then the system conducts patch mapping among the detected time-series patches and decides 6 types of patch changes such as keeping, creating, disappearing, splitting, merging, and changing in a mixed way. Also, the system stores the patch-based spatial structure patterns of time-series land cover maps in binary form to extract changes. This demonstrated that the proposed change detection system can be used as a basis for planning the reconstruction of the urban spatial structure by measuring the degree of urban sprawl.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.1
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• pp.73-83
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• 1999

The land use/cover information, which is periodically obtained from satellite imagery, can be effectively applied to change detection in rapidly changing urban areas. Also it can be used not only as base maps for spatial database in urban information system but as decision-making data for desired urban planning and development direction. In this study, we carried out both unsupervised and supervised classification on land use from Landsat TM and JERS-1 OPS data, which were collected respectively in 1991 and 1997, covering Kumi City and then detected land use changes.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.177-182
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• 2004

This study presents the application of aerial photographs and KOMPSAT-1 Electro-Optical Camera(EOC) imagery in detecting the change of an urban area that has been rapidly growing. For the study, we used multi-time images which were acquired by two different sensors. For all of the images, the coordinate reference system and scale were first made identical through the 1st and 2nd geometric corrections and then image resampling were carried out to spatial resolution of 7m to detect changes under the same conditions. The Image Differencing was employed as a change detection technique. It was confirmed to be able to detect the changes of terrestrial surface like building, structure and road features from aerial photos and KOMPSAT EOC images with single band. The changes could be detected to some extent with the images acquired from different kinds of sensors as well as the same kinds of sensors.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.2 s.29
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• pp.43-52
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• 2004

This study presents the application of aerial photographs and the Korea Multi-Purpose Satellite, KOMPSAT-1 Electro-Optical Camera(EOC) imagery in detecting change in an urban area that has been rapidly growing. For the study, we used multi-temporal images which were acquired by two different sensors. Image registration and resampling were rallied out before performing change detection in a common reference system with the same spatial resolution. for all of the images. Results from image differencing and image ratioing techniques show that panchromatic aerial photographs and KOMPSAT-1 EOC images collected by different sensors have potential to detect changes of urban features such as building, road and other man-made structure. And the optimal threshold values were suggested in applying image differencing and image ratioing techniques for change detection.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.766-771
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• 2002

Automatic change detection based on the vector-to-raster comparison is hard especially in high-resolution image. This paper proposes a method to designate roads in high-resolution image in sequential manner using the information from vector map in which Hough transform is used for reliability. By its linearity, the road of urban areas in a vector map can be easily parameterized. Following some pre-processing to remove undesirable objects, we obtain the edge map of raster image. Then the edge map is transformed to a parameter space to find the selected road from vector map. The comparison is done in the parameter space to find the best matching. The set of parameters of a road from vector map is treated as the constraints to do matching. After designating the road, we may overlay it on the raster image for precise monitoring. The results can be used for detection of changes in road object in a semi-automatic fashion.