• Spatial Information Research
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• v.14 no.1 s.36
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• pp.1-13
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• 2006

To understand road state more quickly and accurately, KICT(Korea Institute of Construction Technology) executing a project that acquire high resolution color CCD images of the whole national highway every 10m, and offer images to the HMS(Highway Management System). At this time, national highway images of the Kyeonggki-Do, Kangwon-Do and Chungcheong-Do province were linked to the HMS and being offered to user. In this paper, from acquisition using highway photologging vehicle to database construction, the whole image-related data processes are described such as match images with their positions one to one or rearrange data acquired by road line to by management office.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.273-278
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• 2004

Feature identification is one of the largest issue in high spatial resolution satellite imagery. A popular method associated with this feature identification is image segmentation to produce image segments that are more likely to features interested. Here, it is, proposed that combination of edge extraction and region growing methods for image segments were used to improve the result of image segmentation. At the intial step, an image was segmented by edge detection method. The segments were assigned IDs, and polygon topology of segments were built. Based on the topology, the segments were tested their similarities with adjacent segments using multivariate analysis. The segments that have similar spectral characteristics were merged into a region. The test application shows that the segments composed of individual large, spectrally homogeneous structures, such as buildings and roads, were merged into more similar shape of structures.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.18-22
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• 2010

본 연구는 고해상도 위성영상의 자료를 비점오염원 분석에 적합한 SWAT모형에 적용할 수 있는 정밀토지이용도의 분류항목으로 설정하고 영상에서 추출 할 수 있는 정보를 효율적으로 이용하여 고해상도 위성영상의 활용성을 높이고자 하였다. 본 연구의 대상지역은 경안천 유역($260.54km^2$)으로 기상자료는 1998년부터 2008년 동안의 경안천유역 6개의 강우관측소 자료와 3개의 기상관측소 자료를 수집하여 구축하였다. 수질자료는 환경부 물환경정보시스템에서 제공하는 자료를 1999~2008년까지 구축하여 사용하였다. 점오염원자료는 경안, 오포, 매산 하수처리장의 1990~2007년까지의 일자료를 사용하였다. 또한 고해상도 위성영상(KOMPSAT-2)을 환경부의 토지피복분류체계와 현장조사를 통하여 토지이용분류 항목을 설정하고 스크린 디지타이징 방법을 통해 제작한 정밀토지이용도를 사용하였다. 정밀토지이용도를 SWAT 모형에 적용하여 분석 시 활용성을 평가하기 위해 30m 중해상도의 환경부 토지이용도와의 모형 결과를 비교하였다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1124-1126
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• 2003

The processes of regional scales in the East Korean coastal waters were investigated by analysis of the Synthetic Aperture Radar (SAR) images taken by the European Research Satellites ERS-1, ERS-2 and Envisat. More than 500 quick look frames taken in 1991-2003 were examined to detect the frames with clearly surface expressions of oceanic phenomena. 26 ERS-1/2 SAR and 11 Envisat wide swath Advanced SAR (ASAR) frames were selected and obtained from the European Space Agency in a form of the precision high-resolution images. The following oceanic phenomena and processes were evident in the radar imagery through the Korean costal waters: fronts, currents, eddies, internal waves, island and ship wakes, oil pollution, etc. They manifested themselves in the field of sea surface roughness, their scale ranged from several tens meters to about 100 km. The most common morphology of these phenomena was a series of contrast dark or light curvilinear lines and bands. The joint analysis of the discussed SAR images with other satellite and in situ data supported and enhanced our interpretation of SAR signatures.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.65-69
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• 2007

The processes of regional scales in the East Korean coastal waters were investigated by analysis of the Synthetic Aperture Radar (SAR) images taken by the European Research Satellites ERS-1, ERS-2 and Envisat. More than 500 quick look frames taken in 1991-2003 were examined to detect the frames with clearly surface expressions of oceanic phenomena. 26 ERS-1/2 SAR and 11 Envisat wide swath Advanced SAR (ASAR) frames were selected and obtained from the European Space Agency in a form of the precision high-resolution images. The following oceanic phenomena and processes were evident in the radar imagery through the Korean costal waters: fronts, currents, eddies, internal waves, island and ship wakes, oil pollution, etc. They manifested themselves in the field of sea surface roughness, their scale ranged from several tens meters to about 100 km. The most common morphology of these phenomena was a series of contrast dark or light curvilinear lines and bands. The joint analysis of the discussed SAR images with other satellite and in situ data supported and enhanced our interpretation of SAR signatures.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.262-266
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• 1999

Several commercial companies that plan to provide improved panchromatic and/or multi-spectral remote sensor data in the near future are suggesting that merge datasets will be of significant value. This study evaluated the utility of one major merging process-process components analysis and its inverse. The 6 bands of 30$\times$30m Landsat TM data and the 10$\times$l0m SPOT panchromatic data were used to create a new 10$\times$10m merged data file. For the image classification, 6 bands that is 1st, 2nd, 3rd, 4th, 5th and 7th band may be used in conjunction with supervised classification algorithms except band 6. One of the 7 bands is Band 6 that records thermal IR energy and is rarely used because of its coarse spatial resolution (120m) except being employed in thermal mapping. Because SPOT panchromatic has high resolution it makes 10$\times$10m SPOT panchromatic data be used to classify for the detailed classification. SPOT as the Landsat has acquired hundreds of thousands of images in digital format that are commercially available and are used by scientists in different fields. After the merged, the classifications used supervised classification and neural network. The method of the supervised classification is what used parallelepiped and/or minimum distance and MLC(Maximum Likelihood Classification) The back-propagation in the multi-layer perception is one of the neural network. The used method in this paper is MLC(Maximum Likelihood Classification) of the supervised classification and the back-propagation of the neural network. Later in this research SPOT systems and images are compared with these classification. A comparative analysis of the classifications from the TM and merged SPOT/TM datasets will be resulted in some conclusions.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.121-128
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• 2014

This study investigated the accuracy of DEM generated by heterogeneous stereo satellite images based on RPC. Heterogeneous sensor images with different spatial resolution are SPOT-5 panchromatic and IKONOS images. For the accuracy evaluation of the DEM, we compared the DEMs generated from two kinds of sensors and that produced using homogeneous SPOT-5 and IKONOS stereo images. As results of the evaluation, accuracy of 3D positioning by heterogeneous images was substantially similar to that of homogeneous stereo images for exact conjugate points. But, in terms of quality of the DEM, DEM generated by heterogeneous sensor showed a lower accuracy about twice in RMSE and about 3 times in LE90 than that of homogeneous sensors. As a result, DEM can be generated by using heterogenous satellite imagery. But if we use a stereo image with different spatial resolution, the performance of image matching was very important factor for the production of high-quality DEM.

• Spatial Information Research
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• v.18 no.2
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• pp.35-44
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• 2010

This research intended to estimate the damage information from torrential rainfalls using airphotos and spatial data which have been rapidly increasing their applicability recently. The study area was Bonghwagun of Gyungsangbukdo where the large amount of damages were occurred from torrential rainfall in July, 2008. For this study, the database was constructed for the study area by collecting usable data. The interpretable items from the airphotos of 40cm spatial resolution were selected. Also, the useful GIS layers such as road were selected in the digital map to extract the damage information more accurately and rapidly. The damaged area was easily identified through the comparison of pre- and post-disaster airphotos. The recovery cost was estimated by applying unit cost to the damaged area. GIS's overlay function was used to extract the damage information of for individual items damaged. The method for extracting damages information using GIS and airphotos could be more efficient and cost effective in case of relatively wide and unapproachable damaged areas. It is also expected that the method using high resolution imagery would lead to minimize the secondary damages as well since it can facilitate the damage estimation within short period of time thereby supporting early securing budget for recovery.

• Korean Journal of Remote Sensing
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• v.22 no.4
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• pp.295-304
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• 2006

Image fusion is defined as making new image by merging two or more images using special algorithms. In case of remote sensing, it means fusing multispectral low-resolution remotely sensed image with panchromatic high-resolution image. Generally, hyperspectral image fusion is accomplished by utilizing fusion technique of multispectral imagery or spectral unmixing model. But, the former may distort spectral information and the latter needs endmember data or additional data, and has a problem with not preserving spatial information well. This study proposes a new algorithm based on two stage spectral unmixing model for preserving hyperspectral image's spectral information. The proposed fusion technique is implemented and tested using Hyperion and ALI images. it is shown to work well on maintaining more spatial/spectral information than the PCA/GS fusion algorithms.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.132-144
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• 2018

3D Geo-spatial information models have been widely used in the field of Civil Engineering, Medical, Computer Graphics, Urban Management and many other. Especially, in surveying and geo-spatial field, the demand for high quality 3D geospatial information and indoor spatial information is so highly increasing. However, it is so difficult to provide a low-cost and high efficiency service to the field which demand the highest quality of 3D model, because pre-constructed spatial data are composed of different formats and storage structures according to the application purpose of each institutes. In fact, the techniques to construct a high applicable 3D geo-spatial model is very expensive to collect and analyze geo-spatial data, but most demanders of 3D geo-spatial model never want to pay the high-cost to that. This study, therefore, suggest the effective way to construct 3D geo-spatial model with low-cost of construction. In general, the effective way to reduce the cost of constructing 3D geo-spatial model as presented in previous studies is to combine the raw data obtained from point cloud observatory and UAV imagery, however this method has some limitation of usage from difficulties to approve the use of raw data because of those have been managed separately by various institutes. To solve this problem, we developed the linking & management system for unifying a high-Resolution raw geo-spatial data based on the point cloud DB and apply this system to extract the basic database from 3D geo-spatial mode for the road database registration. As a result of this study, it can be provided six contents of main entries for road registration by applying the developed system based on the point cloud DB.