• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.24-27
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• 2006

항공사진이나 고해상도 위성영상으로부터 건물의 정보를 추출하기 위한 많은 연구들이 이전부터 수행되어 왔다. 많은 연구들은 스테레오 영상을 이용하여 DEM을 생성하고 이로부터 3차원 건물 정보를 추출하였다 본 연구에서는 단일 위성영상만을 이용하여 3차원 건물 정보를 추출하는 알고리즘을 제안한다. 제안된 방식은 가상의 그림자를 영상에 투영시키고, 투영된 그림자와 영상 위에 나타난 실제 건물의 그림자가 일치했을 때, 건물의 높이를 결정한다 결정된 건물 높이를 이용하여 연직선을 생성시키고, 이 연직선을 따라서 건물의 지붕 외곽선을 이동시키면, 이동된 지붕 외곽선은 건물의 바닥 외곽선이 된다. 이를 통해서 건물의 높이와 위치 정보를 취득할 수 있다. 건물이 밀집한 지역에서는 지표면에 나타난 건물의 그림자가 다른 건물에 가려지는 경우가 많다 이러한 경우를 고려하여 제안된 알고리즘은 지표면 위에 나타난 그림자를 이용한 방법과 그림자를 가린 건물 정면에 나타난 그림자를 이용한 방법을 사용한다. 알고리즘의 검증을 위해서 본 연구에서는 스테레오 영상에서 추출한 건물의 높이와 본 연구에서 제안한 알고리즘으로 추출한 건물의 높이를 비교하였다. 두 방법에 대해서 각각 30개의 건물 높이를 비교한 결과 RMSE는 약 1.5 m로 나타났다.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.23-28
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• 2005

고해상도 위성영상으로부터 건물, 도로 등의 인공지물의 정보를 추출하기 위한 연구들이 현재 활발히 진행되고 있다. 대부분의 기존 연구들의 경우, 위성영상에서 3차원 건물정보를 추출하기 위해서는 영상과 별도의 기준점을 필요로 하며, 영상에서의 측정값을 3차원 정보로 변환하기 위해서는 센서모델링의 과정을 거쳐야 했다. 이 연구에서는 단안식 (Monoscopic)영상으로부터 이러한 복잡한 과정을 거치지 않고 직접 건물의 3차원 정보를 추출하는 기술개발에 대하여 소개한다. 제안하는 방식은 단안식 영상에서 영상의 방위각 및 촬영지역에서의 태양과 카메라의 방위각 및 고도각을 이용하여 건물의 높이가 주어졌을 때 이에 따르는 건물 수직선과 건물 그림자를 영상에 투영시키는 과정을 반복함으로써 투영된 건물 그림자가 실제 영상에서 관측되는 건물의 그림자와 일치될 대의 건물의 높이 값을 구하고 건물 지붕 외각선을 구해진 건물의 높이 값에 따르는 건물 수식선 만큼 수평 이동하여 건물의 위치를 구하게 된다. 실제 대전지역을 촬영한 IKONS 영상을 이용하여 실험한 결과 이와 같은 방법으로 취득 된 건물 높이값이 약 1m 내외의 정확도를 가지는 것을 나타났다.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.3-13
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• 2006

Extraction of man-made objects from high resolution satellite images has been studied by many researchers. In order to reconstruct accurate 3D building structures most of previous approaches assumed 3D information obtained by stereo analysis. For this, they need the process of sensor modeling, etc. We argue that a single image itself contains many clues of 3D information. The algorithm we propose projects virtual shadow on the image. When the shadow matches against the actual shadow, the height of a building can be determined. If the height of a building is determined, the algorithm draws vertical lines of sides of the building onto the building in the image. Then the roof boundary moves along vertical lines and the footprint of the building is extracted. The algorithm proposed can use the shadow cast onto the ground surface and onto facades of another building. This study compared the building heights determined by the algorithm proposed and those calculated by stereo analysis. As the results of verification, root mean square errors of building heights were about 1.5m.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.352-362
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• 2019

The old residences and shops in the backside blocks are affected by the traffic noises from the main road. The noise of the backside roads is affected by the following factors such as the height of the roadside buildings, the distance between the road and the backside streets, distance among adjacent roadside buildings, and the difference of the adjacent building heights. The both noise levels on the road and the backside street were measured simultaneously in 15 urban blocks of a city which can be categorized into two types of roadside building plans ; 1) one single building along the street, 2) buildings arranged on one axis beside the road. As the results, there is no significant noise reduction due to the width of the buildings in general. However, in the cases of buildings arranged on one axis beside the road, it was found that the average noise reduction was 12 dB(A) on the basis of the building height of 4 m. Also, it was analysed that for each 4 m increase in the building height, noise reduction occurred by 2 dB(A) beyond building height of 4 m. In general, it was proved that the noise of the back streets is mainly affected by the lowest height of the roadside buildings. It was found that noise is increased by 1 dB(A) for each 4 m increase of the height difference between adjacent buildings. Also, It was revealed that for each 0.5 m increase in the distance between roadside building, noise reduction decreased by 1 dB(A).

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.71-79
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• 2009

We expanded the 3D building information extraction method using shadow and vertical line from single high resolution image with meta information into the method for single high resolution image without meta information. Our method guesses an azimuth angle and an elevation angle of the sensor and the sun using reference building, selected by user, on an image. For test, we used an IKONOS image and an image extracted from the Google Earth. We calculated the Root Mean Square (RMS) error of heights extracted by our method using the building height extracted from stereo IKONOS image as reference, and the RMS error from the IKONOS image and the Google Earth image was under than 3 m. We also calculated the RMS error of horizontality position by comparison between building position extracted from only the IKONOS image and it from 1:1,000 digital map, and the result was under than 3 m. This test results showed that the height pattern of building models by our method was similar with it by the method using meta information.

• Spatial Information Research
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• v.7 no.1
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• pp.89-101
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• 1999

This paper represents methods to calculate heights of buildings by estimating their shadow lengths in a single and panchromatic image of the KVR-1000 camera system Shadows are identified Com brightness intensity of each pixel, and their lengths are measured. Two methods are implemented to estimate heights from shadows. One method is to use a ratio of shadow s lengths with respect to heights of reference buildings measured on site. The other method uses sun elevation angles calculated from various camera s parameters at the exposure time. The estimated heights of 20 buildings are compared with heights measured on site, and the RMS errors for each method are 1.70m and 1.75m, respectively. When a resampling method to enhance identification of shadows is used and their lengths are accordingly re-calculated, the estimated errors for each method are significantly reduced to 1.17m and 1.16m, respectively. Meanwhile, effects of land slope on shadows can be hardly obtained unless detailed DTM(digital terrain model) are available, and they introduce additional errors up to 25m.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.361-373
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• 2013

The monitoring of urban area, target detection and building reconstruction have been actively studied and investigated since high resolution X-band SAR images could be acquired by airborne and/or satellite SAR systems. This paper describes an efficient approach to reconstruct artificial structures (e.g. apartment, building and house) in urban area using high resolution X-band SAR images. Building footprint was first extracted from 1:25,000 digital topographic map and then a corner line of building was detected by an automatic detecting algorithm. With SAR amplitude images, an initial building height was calculated by the length of layover estimated using KS-test (Kolmogorov-Smirnov test) from the corner line. The interferometric SAR phases were simulated depending on SAR geometry and changable building heights ranging from -10 m to +10 m of the initial building height. With an interferogram from real SAR data set, the simulation results were compared using the method of the phase consistency. One of results can be finally defined as the reconstructed building height. The developed algorithm was applied to repeat-pass TerraSAR-X spotlight mode data set over an apartment complex in Daejeon city, Korea. The final building heights were validated against reference heights extracted from LiDAR DSM, with an RMSE (Root Mean Square Error) of about 1~2m.

• Journal of Korean Association for Spatial Structures
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• v.12 no.2
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• pp.73-80
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• 2012

According to the global status of terroristic acts occurred from 2002 to 2010, 10,431(nearly 52.2%) of 19,946 cases have happened by bomb blasts, and 10,431(nearly 52.2%) of weapons used for terrorism were explosive substances Therefore, this study analyzed the terrorism risks of buildings according to height through FEMA 455 - rapid visual screening. As a result, the higher the building is, the higher the terror risk gets. It shows that total risk increases proportionally to buildings's height. In case of buildings over 100 meter high, the total risk is most affected by threat items. According to the risk of explosion associated with the scenario analysis, buildings over 100 meter high have high risks of Internal-Explosive.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.621-626
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• 2006

Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Extraction of 3D building information from high resolution satellite imagery is one of the most active research topics. There have been many previous works to extract 3D information based on stereo analysis, including sensor modelling. Practically, it is not easy to obtain stereo high resolution satellite images. On single image performance, most studies applied the roof-bottom points or shadow length extracted manually to sensor models with DEM. It is not suitable to apply these algorithms for dense buildings. We aim to extract 3D building information from a single satellite image in a simple and practical way. To measure as many buildings as possible, in this paper, we suggested a new way to extract building height by triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and decrease the digitizing error and the computation efficiency.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.87-92
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• 2010

아름다운 자연경관은 인구의 도시집중과 토목 건축 기술 기반의 도시공간구조 다양화로 자연경관은 그 모습을 잃어가고 있다. 이러한 변화 이변에는 자연경관의 보존에 대한 도시민의 욕구가 날로 증가하고 있어 경관자원의 보전 및 보호를 위한 체계가 필요한 실정이다. 체계적이고 종합적인 경관관리로 도시민들에게 우수한 경관을 제공하기 위해서는 경관의 변화 정도를 정량적이고 객관적으로 측정하고 모니터링 할 수 있어야 한다. 따라서 본 연구에서는 건물배치 및 높이에 따른 산림녹시율을 3D GIS기반에서 분석하여 산림녹시율이 인간에게 미치는 영향을 규명하고자 한다.