• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.47-57
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• 2002

The intention of this study is to construct the spatial database and to extract attribute data which are able to complete the omitted data in the topographical map or completion map of construction using the image data of various form such as artificial satellite images, aerial photographs, terrestrial photographs and so on. This study used the single frame images only for the raw image data, supposing the case of rigorous photogrammetric method is not available or rapid acquisition of information is need. The extracted spatial and attribute data from the images are used for modifying and updating the database, and for providing visual effect useful for guide and management of the facilities. This study intended to develop the technique able to apply in the case where comparative high accuracy is not required or rapid modification is necessary, and to verify the possibility of editing and updating the digital map using the photographs or video images remained as old data. Many of previous research on the management system for university facility has been accomplished focusing on the design and construction of database itself. Otherwise, this study aimed for the construction of guide and management system based on compiling the digital map of present state using multi-imagery, and the more applicability was intended too.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.609-616
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• 2017

National Geographic Information Institute has established a plan that preoccupies UCPs (Unified Control Points) at 2~3km intervals in urban areas by considering the distance between existing UCPs by satellite images and aerial photographs in 2015. In this study, we discussed the method of selecting the locations of optimal UCPs by simulating GPS reception environment in candidate sites for UCPs using GIS. For this purpose, we selected new candidate sites for installing UCPs using satellite images and aerial photographs, and analyzed the GPS reception environment by calculating the visibility distance from buildings around UCPs using GIS skyline analysis. The number of and the arrangement of visible satellites that are capable of GPS satellite reception from the viewpoint of sky view were showed by GIS skyline analysis. Quality evaluation results of GPS observation data were compared with average PDOP calculated from hourly PDOP and TEQC in two points of Sungkyunkwan University during 8 hours. As a result of GPS reception environment using GIS, if the PDOP increases, the data acquisition rate is lowed, and the multipath error and the cycle slip are increased. Thus, this study verified that the quality of GPS observation data can be secured by constructing three-dimensional spatial information and simulating PDOP when preoccupying multiple UCPs using GIS.

• Journal of Korea Multimedia Society
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• v.20 no.3
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• pp.581-592
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• 2017

Geographic Information System (GIS) is a method of expressing objects in a space. Currently, many research and developments are being conducted to implement 3D GIS. In previous studies, 3D GIS applications have been developed using Unity 3D, which is a 3D engine with good development accessibility. However, it requires manual work to enter various formats of GIS data, making it difficult to immediately reflect GIS data that change frequently. To improve this problem, this study developed a method for automatically reading and outputting various GIS data from the existing Unity 3D application. The improved application could read Satellite Images, Aerial Photographs, Digital Elevation Models (DEM) and Shapefiles with no transformation through other commercial programs, and they could be implemented as 3D objects. This study automated the GIS data conversion which had been manually performed and as a result, the manpower, time, and resources required for 3D GIS implementation can be saved.

• Journal of Environmental Impact Assessment
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• v.8 no.3
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• pp.77-90
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• 1999

The degree of green naturality (DGN) has played a key role for maintaining the environmental quality from inappropriate developments, although the quality and effectiveness of the mapping of DGN has been under debate. In this study, spatial distribution of degree of green naturality was initially estimated from forest stand maps that were produced from the aerial photo interpretation and extensive field survey. Once the boundary of initial classes of DGN were defined, it were overlaid with normalized difference vegetation index (NDVI) data that were derived from the recently obtained Landsat Thematic Mapper data. NDVI was calculated for each pixel from the radiometrically corrected satellite image. There were no significant differences in mean values of vegetation index among the initial DGN classes. However, the satellite derived vegetation index was very effective to delineate the developed and damaged forest lands and to adjust the initial value of DGN according to the distribution of NDVI within each class.

• ETRI Journal
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• v.33 no.4
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• pp.537-546
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• 2011

This paper introduces an automated method for building height recovery through the integration of high-resolution satellite images and digital vector maps. A cross-correlation matching method along the vertical line locus on the Ikonos images was deployed to recover building heights. The rational function models composed of rational polynomial coefficients were utilized to create a stereopair of the epipolar resampled Ikonos images. Building footprints from the digital maps were used for locating the vertical guideline along the building edges. The digital terrain model (DTM) was generated from the contour layer in the digital maps. The terrain height derived from the DTM at each foot of the buildings was used as the starting location for image matching. At a preset incremental value of height along the vertical guidelines derived from vertical line loci, an evaluation process that is based on the cross-correlation matching of the images was carried out to test if the top of the building has reached where maximum correlation occurs. The accuracy of the reconstructed buildings was evaluated by the comparison with manually digitized 3D building data derived from aerial photographs.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.35-45
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• 2010

The objective of this study is to verify the positional accuracy by performing the orthometric corrections on the high resolution satellite images and to analyze the band correlation between the high resolution images corrected with orthometric correction. The objectives also included an analysis on the correlation of NDVI. For the orthometric correction of images from KOMPSAT2 and IKONOS, systematic errors were removed in use of RPC data, and non-planar distortions were corrected with GPS surveying data. Also, by preempting the image points at the same positions within ortho images, a comparison was performed on positional accuracies between image points of each image and GPS surveying points. The comparison was also made on the positional accuracies of image points. between the images. For correlation of band and correlation of NDVI, the descriptive statistics of DN values were acquired for respective bands by adding the Quickbird images and Aerial Photographs undergone through orthometric correction at the time of purchase. As result, from a comparison on positional accuracies of Orthoimages from KOMPSAT2 and Ortho Images of IKONOS was made. From the comparison the distance between the image points within each image and GPS surveying points was identified as 3.41m for KOMPSAT2 and as 1.45m for IKONOS, presenting a difference of 1.96m. Whereas, RMSE between image points was identified as 1.88m. The level of correlation was measured by using Quickbird, KOMPSAT2, IKONOS and Aerial Photographs between inter-image bands and NDVI, showing that there were high levels of correlation between Quickbird and IKONOS identified from all bands as well as from NDVI, except a high level of correlation that was identified between the Aerial Photographs and KOMPSAT2 from Band 2. Low levels of correlation were also identified between Quickbird and Aerial Photographs from Band 1. and between KOMPSAT2 and IKONOS from Band 2 and Band 4, whereas, KOMPSAT2 showed low correlations with Aerial Photographs from Band 3. For NDVI, KOMPSAT2 showed low level of correlations with both of QuickBird and IKONOS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.73-83
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• 2008

For spatial analysis and decision-making based on territorial and urban information, technologies on 3D GIS with digital image data and photo-realistic 3D image models to visualize 3D modeling are being rapidly developed. Currently, satellite images, aerial images and aerial LiDAR data are mostly used to build 3D models and textures from oblique aerial photographs or terrestrial photographs are used to create 3D image models. However, we are in need of quality 3D image models as current models cannot express topographic and features most elaborately and realistically. Thus, this study analyzed techniques to use aerial photographs, aerial LiDAR, terrestrial photographs and terrestrial LiDAR to create a 3D image model with artificial features and special topographic that emphasize spatial accuracy, delicate depiction and photo-realistic imaging. A 3D image model with spatial accuracy and photographic texture was built to be served via 3D image map services systems on the Internet. As it was necessary to consider intended use and display scale when building 3D image models, in this study, we applied the concept of LoD(Level of Detail) to define 3D image model of buildings in five levels and established the models by following the levels.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.83-91
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• 2012

Crown density, which is defined as the proportion of the forest floor concealed by tree crown, is important and useful information in various fields. Previous methods of measuring crown density have estimated crown density by interpreting aerial photographs or through a ground survey. These are time-consuming, labor-intensive, expensive and inconsistent approaches, as they involve a great deal of subjectivity and rely on the experience of the interpreter. In this study, the crown density of a forest in Korea was estimated using KOMPSAT-2 high-resolution satellite images. Using the image segmentation technique and stand information of the digital forest map, the forest area was divided into zones. The crown density for each segment was determined using the discriminant analysis method and the forest ratio method. The results showed that the accuracy of the discriminant analysis method was about 60%, while the accuracy of the forest ratio method was about 85%. The probability of extraction of candidate to update was verified by comparing the result with the digital forest map.

• 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.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.530-535
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• 2002

An approach for quickly updating GIS building data using high resolution remotely sensed data is proposed in this paper. High resolution remotely sensed data could be aerial photographs, satellite images and airborne laser scanning data. Data from different types of sensors are integrated in building extraction. Based on the extracted buildings and the outdated GIS database, the change-detection-template can be automatically created. Then, GIS building data can be fast updated by semiautomatically processing the change-detection-temp late. It is demonstrated that this approach is quick, effective and applicable.