• Title/Summary/Keyword: RADARSAT SAR 영상

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Assessment of DEM Generated by Stereo C-band and X-band SAR images using Radargrammetry (Radargrammetry를 이용한 C-밴드 및 X-밴드 SAR 위성영상의 DEM 생성 평가)

  • Song, Yeong Sun;Kim, Gi Hong
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.4
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    • pp.109-116
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    • 2013
  • To extract the 3D geometric information from SAR(Synthetic Aperture Radar) images, two different techniques, interferometric SAR and radargrammetry, have been widely used. InSAR is most widely used for the generation of precise DEM(Digital Elevation Model) until now. But, Interferometric SAR requires severe temporal correlation over areas covered with vegetation and high relief areas. Because radargrammetry is less sensible to temporal correlation, it can provide better results than interferometric SAR in certain, especially X-band SAR. In this paper, we assess the properties of DEMs generated by radargrammetry using stereo C-band RADARSAT-1 images and X-band TerraSAR-X images.

A Study on the Extraction of Flood Inundated Scar of Rural Small Stream Area Using RADARSAT SAR Images (RADARSAT SAR 영상을 이용한 농촌지역 소하천주변의 침수피해지역 추정 연구)

  • Lee Mi-Seon;Park Geun-Ae;Kim Seong-Joon
    • Proceedings of the KSRS Conference
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    • 2006.03a
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    • pp.139-144
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    • 2006
  • 농촌지역 소하천 주변의 홍수범람지역을 추정하기 위하여 강우와 구름의 영향을 받지 않으며 홍수기간의 데이터 취득이 가능한 RADARSAT 영상을 이용하였다. 대상 지역인 안성천유역의 1998년 9월 홍수시기에 대해서 홍수 전, 직후 그리고 후, 세시기의 RADARSAT 영상을 사용하였다. 5m DEM을 이용하여 정사보정을 한 후 RGB 합성방법과 ratio 방법을 적용하여 성환천과 학성천 합류지점에서 침수지역을 발견하였다. 침수지역은 두개의 하천이 합류하는 지점에서 발생하였으며, 하천의 통수능력을 상실하여 범람한 것으로 분석되었다.

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Extraction of Water Area using Artificial Neural Network from Satellite Imagery and DEM (신경망 알고리즘을 이용한 위성영상과 DEM으로부터의 수계지역 추출)

  • Sohn, Hong-Gyoo;Jung, Won-Jo;Yoo, Hwan-Hee;Song, Yeong-Sun
    • 한국지형공간정보학회:학술대회논문집
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    • 2002.11a
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    • pp.51-57
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    • 2002
  • 국내에서 활발하게 연구되고 있는 위성영상을 이용한 원격탐사는 매핑, 환경관리, 시설물 관리 등에 이용되어 왔다. 본 연구에서는 날씨나 태양의 제약을 받지 않는 RADARSAT SAR 영상의 수계지역을 신경망 기법을 이용하여 분류하고자 하였다. RADARSAT은 경사관측을 통하여 영상을 취득하며 지형의 기복에 의한 음영효과(Shadow effect)로 인하여 수계지역 분류시 정확도를 감소시킨다. 이러한 문제를 해결하기 위해서 본 연구에서는 RADARSAT SAR 영상의 역산란계수를 계산하고 음영효과에 의한 분류오류를 감소시키기 위하여 수치고도모형을 사용하였다. 지형의 기복이 작은 평지와 지형의 기복이 심한 산악지로 나누어 연구를 수행하여 각 지역별로 분류 정확도를 평가하였다. 연구결과로 역산란계수를 신경망기법의 단일 입력 자료로 사용한 경우보다 수치고도모형을 같이 사용한 것이 분류 정확도가 높았다. 또한, 수치고도모형을 역산란계수와 함께 입력 자료로 이용할 경우 평지보다 산악지에서 효율적이었다. 산악지역이 많은 국내에서는 SAR영상의 수계지역 추출을 신경망 기법으로 할 경우에는 수치고도모형을 함께 이용함으로써 분류정확도 향상을 시킬 수 있다고 사료된다.

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The Analysis of Oil Spill Spreading Using SAR Images (SAR영상을 이용한 유류 오염 분포 분석)

  • Kim Taerim;Lee Soo Hyung
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.2 no.2
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    • pp.38-48
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    • 1999
  • The oil spill accident near Goeje Island on April 3, 1997 was analyzed using two RADARSAT SAR images. The first scene was acquired 3 days after the accident as an extended low beam mode and the second scene was acquired 12 hours after the first scene as a standard beam mode. The two scenes showed slicks not only by oil spills but also by oil spill look-alikes caused by wind sheltering, low wind, natural film, and etc. These slicks were analyzed and classified, and natural films produced from aquaculture farms around Goeje Island were also suggested as a strong candidate for slicks on SAR images. The study with two SAR imags indicated the oil spill patterns which spreaded to the southwest immediately after the accident and switched the direction to the east. The spreading patterns shown in two SAR images also showed good agreement with in-situ observations.

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Radarsat-1 ScanSAR Quick-look Signal Processing and Demonstration Using SPECAN Algorithm (SPECAN 알고리즘을 이용한 Radatsat-1 ScanSAR Quick-look 신호 처리 및 검증 알고리즘 구현)

  • Song, Jung-Hwan;Lee, Woo-Kyung;Kim, Dong-Hyun
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.75-86
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    • 2010
  • As the performance of the spaceborne SAR has been dramatically enhanced and demonstrated through advanced missions such as TerraSAR and LRO(Lunar Reconnaissance Orbiter), the need for highly sophisticated and efficient SAR processor is also highlighted. In Korea, the activity of SAR researches has been mainly concerned with SAR image applications and the current SAR raw data studies are mostly limited to stripmap mode cases. The first Korean spaceborne SAR is scheduled to be operational from 2010 and expected to deliver vast amount of SAR raw data acquired from multiple operational scenarios including ScanSAR mode. Hence there will be an increasing demand to implement ground processing systems that enable to analyze the acquired ScanSAR data and generate corresponding images. In this paper, we have developed an efficient ScanSAR processor that can be directly applied to spaceborne ScanSAR mode data. The SPECAN(Spectrum Analysis) algorithm is employed for this purpose and its performance is verified through RADARSAT-1 ScanSAR raw data taken over Korean peninsular. An efficient quick-look processing is carried out to produce a wide-swath SAR image and compared with the conventional RDA processing case.

Flood Monitoring and Extraction of Water Area Using Multi-temporal RADARSAT SAR Imagery (RADARSAT SAR 영상을 이용한 수계지역 추출 및 홍수지역 모니터링)

  • Sohn, Hong-Gyoo;Yoo, Hwan-Hee;Song, Yeong-Sun;Jung, Won-Jo
    • 한국지형공간정보학회:학술대회논문집
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    • 2002.03a
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    • pp.48-53
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    • 2002
  • 본 연구에서는 각각 1998년 8월 12일(홍수 발생시), 8월 19일(홍수 발생 후) 옥천, 보은 지역을 촬영한 RADARSAT SAR 위성영상을 이용하여 수계지역 및 홍수지역 분류를 수행하고자 하였다. 이를 위해, 먼저 두 장의 위성영상에 대해서 각각 스페클 잡영(speckle noise)을 제거하고, ${\sigma}^0$(sigma naught, dB)을 계산한 후 수계지역에 대한 ${\sigma}^0$값을 분석하였다. 이 값을 기준으로 각각 두 장의 위성영상에서 각각 최대우도법을 이용하여 수계지역을 분류하였다. SAR 영상은 영상취득의 원리에 의해 지형의 기복에 따른 음영효과(shadow effect)가 발생하는데, 음영효과가 발생하는 지역의 ${\sigma}^0$값은 수계지역과 비슷한 반사특성(낮은 dB 값)을 보인다. 따라서 지형의 기복이 심한 지역의 수계지역 분류시 음영효과를 제거해야 효과적적인 분류를 할 수 있으며, 이를 위해 위성의 헤더자료로부터 촬영시 각각의 촬영중심을 계산하고, 촬영중심과 지상좌표와의 기하학적 관계를 고려하여 음영효과를 제거하였다. 마지막으로, 수계지역만이 추출된 영상에 대해 영상의 기하보정을 수행하였으며, 기하 보정된 두장의 위성영상에 대해 차분영상를 생성함으로서 홍수지역을 분류하였다.

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GEOCODING OF SAR IMAGE USING THE ORBIT AND ATTITUDE DETERMINATION OF RADARSAT (RADARSAT 위성의 궤도결정과 자세결정을 이용한 SAR 영상의 자리매김)

  • 소진욱;최규홍;원중선
    • Journal of Astronomy and Space Sciences
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    • v.15 no.1
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    • pp.183-196
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    • 1998
  • The Synthetic Aperture Radar(SAR) image and the Digital Elevation Model(DEM) of an target area are put into use to generate three dimensional image map. An method of image map generation is explained. The orbit and attitude determination of satellite makes it possible to model signal acquisition configuration precisely, which is a key to mapping image coordinates to geographic coordinates of concerned area. An application is made to RADARSAT in the purpose of testing its validity. To determine the orbit, zero Doppler range is used. And to determine the attitude, Doppler centroid frequency, which is the frequency observed when target is put in the center of antenna's view, is used. Conventional geocoding has been performed on the basis of direct method(mapping image coordinates to geographic coordinates), but in this reserch the inverse method(mapping from geographic coordinates to image coordinates) is taken. This paper shows that precise signal acquisition modeling based on the orbit and attitude determination of satellite as a platform leads to a satellite-centered accurate geocoding process. It also shows how to model relative motion between space-borne radar and target. And the relative motion is described in ECIC(earth-centered-initial coordinates) using Doppler equation and signal acquisition geometry.

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Accurate Classification of Water Area with Fusion of RADARSAT and SPOT Satellite Imagery (RADARSAT 위성영상과 SPOT 위성영상의 영상융합을 이용한 수계영역 분류정확도 향상)

  • 손홍규;송영선;박정환;유환희
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2003.04a
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    • pp.277-281
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    • 2003
  • We fused RADARSAT image and SPOT panchromatic image by wavelet transform in order to improve the accuracy of classification on the water area. Fused image in water not only maintained the characteristic of SAR image (low pixel value)but also had boundary information improved. This leads to accurate method to classify water areas.

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Ground Subsidence Measurements of Noksan National Industrial Complex using C-band Multi-temporal SAR images (C-밴드 다중시기 SAR 위성 영상을 이용한 녹산국가산업단지 일대의 지반침하 관측)

  • Cho, Minji;Lee, Chang-Wook
    • Korean Journal of Remote Sensing
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    • v.30 no.2
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    • pp.161-172
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    • 2014
  • Established in the lower reaches of the Nakdong river in Busan, the Noksan national industrial complex is one of the deepest soft ground areas in Korea. In case of the costal landfill having deep soft ground, there is a significant residual settlement over a long period of time. In this study, there was observed ground subsidence occurred in the Noksan national industrial complex from September 2002 to April 2007 by applying DInSAR and SBAS time series method using RADARSAT-1 and Envisat SAR datasets. As a result, it was calculated that ground subsidence developed at the velocity of about maximum 10 cm/yr and mean 6 cm/yr at the eastern center, west, western center and southern area contiguous on the coastline of the study area during the period from September 2002 to April 2007. In addition, the RADARSAT-1 average displacement map has been compared with the total displacement map observed by accurate magnetic probe extensometer during the period from 2001 to 2002. Since the time series displacement has shown a linear trend mostly, we consider that continuous monitoring should be needed until the ground subsidence of the study area has been stabilized.

Classification for landfast sea ice types in Greenland with texture analysis images (텍스쳐 이미지를 이용한 그린란드 정착빙의 분류)

  • Hwang, Do-Hyun;Hwang, Byong-Jun;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.4
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    • pp.589-593
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    • 2013
  • Remote sensing of SAR images is suitable for sea ice observations to obtain the sea ice data if clouds or weather conditions change. There are various types of sea ice, classification results can be seen more easily to detect the change by types of sea ice. In this study, we classified the image by supervised classification method, which is minimum distance was used. Also, we compared the overall accuracy when compared to the results with classification result of SAR images and the result of texture images. When using Radarsat-2 texture images, the overall accuracy was the highest, generally, when using the SAR images had higher overall accuracy.