• Title/Summary/Keyword: JERS-1 SAR

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Extration of Digital Elevation Models Using InSAR Processing Techique (InSAR 처리기법에 의한 수치고도모형의 추출)

  • Lee Jin-Duk;Yeon Sang-Ho;Bae Sang-Woo
    • Proceedings of the Korea Contents Association Conference
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    • 2005.05a
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    • pp.142-145
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    • 2005
  • As SAR data have the strong point that is not influenced by weather or light amount compared with optical sensor data, they have high usfulness as temporary analysis fast and can be collected in case of like disaster. This study is to extract DEM from L-band data of JERS-1 SAR imagery using InSAR and DInSAR processing techniques. The accuracies of DEM extracted from the SAR data were evaluated by employing DEM derived from the digital topographic maps of 1:5000 scale as standard data.

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Experimental Study on DEM Extraction Using InSAR and 3-Pass DInSAR Processing Techniques (InSAR 및 3-Pass DInSAR 처리기법을 적용한 DEM 추출에 대한 실험 연구)

  • Bae, Sang-Woo;Lee, Jin-Duk
    • The Journal of the Korea Contents Association
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    • v.7 no.3
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    • pp.176-186
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    • 2007
  • As SAR data have the strong point that is not influenced by weather or light amount in comparison with optical sensor data, they are highly useful for temporary analysis and can be collected in time of unforeseen circumstances like disaster. This study is to extract DEM from L-band data of JERS-1 SAR imagery using InSAR and DInSAR processing techniques. As a result of analyzing the extracted coherence and interferogram images, it was shown that the DInSAR 3-pass method produces more suitable coherence values than the InSAR method. The accuracies of DEM extracted from the SAR data were evaluated by employing the DEM derived from the digital topographic maps of 1:5000 scale as reference data. And it was ascertained that baselines between antenna locations largely affect the accuracy of extracted DEM.

Observation of Water Volume Changes of Rivers in Amazon Forests from Multi-temporal JERS-1 SAR Images

  • Takako, Sakurai-Amano;Takagi, Mikio
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.454-459
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    • 2002
  • We have developed a new method to visualize river networks in tropical rain forests from JERS-1 SAR images. This method compresses river information in an original SAR image to a small image displaying wide rivers as dark objects in real size and narrower rivers as bright objects showing brightness level as an indicator of the discharge. We applied this method to 476 images of Amazon forests, 13 observations for path 415 data and 11 observations for path 416 data between 1993 and 1997. We confirmed that a change observed in a preliminary experiment was certainly a part of seasonal changes. The changes roughly correspond to the monthly precipitation changes. Through a simple digital analysis although qualitative, we also detected subtle but consistent regional differences among minor tributaries that belong to a major tributary basin.

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JERS-1 SAR DATA CHARACTERISTICS FOR GEOLOGICAL APPLICATIONS

  • Moon, Wooil-M.;Li, Bo;Won, J.S.;Yoo, H.W.;Singhroy, V.;Yamaguch, Y.
    • Korean Journal of Remote Sensing
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    • v.10 no.2
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    • pp.161-170
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    • 1994
  • The JERS-1 is an Earth Resources Satellite launched by NASDA (Natinal Space Development Agency) of Japan, in February in 1992 and has two sensors; SAR(L-Band Synthetic Aperture Radar) and OPS (SWIR and VNIR radiometers). In this research note, the basic properties and data characteristics of the SAR data are summarized based on the observations made on the data sets received for the Nahanni Canadian test site, Northwest Territories. The JERS-1 SAR data quality. including the spatial resolution of the data, is, in general, excellent for most geological applications.

Land Surface Soil Moisture Effect on DInSAR

  • Lee C.W.;Kim S.W.;Won J.S.
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.174-177
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    • 2004
  • Differential interferometric phases from JERS-1 L­band data sets show spatial variation of path-length ranging from a few mm to several cm. The variation may be caused by changes in soil moisture contents, i.e. variation of penetration depth and the swelling of soils. Although the amount of total effect caused by soil moisture is not measurable, it is clear that the soil moisture according to precipitation is another factor to be considered in DInSAR analysis. We also discuss DInSAR characteristics in a rice paddy according to irrigation conditions, and discrimination of hydrological features such as stream channels and watershed boundaries by applying DInSAR technique.

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LAND COVER CLASSIFICATION BY USING SAR COHERENCE IMAGES

  • Yoon, Bo-Yeol;Kim, Youn-Soo
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.76-79
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    • 2008
  • This study presents the use of multi-temporal JERS-1 SAR images to the land cover classification. So far, land cover classified by high resolution aerial photo and field survey and so on. The study site was located in Non-san area. This study developed on multi-temporal land cover status monitoring and coherence information mapping can be processing by L band SAR image. From July, 1997 to October, 1998 JERS SAR images (9 scenes) coherence values are analyzed and then classified land cover. This technique which forms the basis of what is called SAR Interferometry or InSAR for short has also been employed in spaceborne systems. In such systems the separation of the antennas, called the baseline is obtained by utilizing a single antenna in a repeat pass

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Landcover classification by coherence analysis from multi-temporal SAR images (다중시기 SAR 영상자료 긴밀도 분석을 통한 토지피복 분류)

  • Yoon, Bo-Yeol;Kim, Youn-Soo
    • Aerospace Engineering and Technology
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    • v.8 no.1
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    • pp.132-137
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    • 2009
  • This study has regard to classification by using multi-temporal SAR data. Multi-temporal JERS-1 SAR images are used for extract the land cover information and possibility. So far, land cover information extracted by high resolution aerial photo, satellite images, and field survey. This study developed on multi-temporal land cover status monitoring and coherence information mapping can be processing by L band SAR image. From July, 1997 to October, 1998 JERS SAR images (9 scenes) coherence values are analyzed and then extracted land cover information factors, so on. This technique which forms the basis of what is called SAR Interferometry or InSAR for short has also been employed in spaceborne systems. In such systems the separation of the antennas, called the baseline is obtained by utilizing a single antenna in a repeat pass.

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SUBSIDENCE AT DUK-PO AREA REVEALED BY DINSAR AND INTERFEROGRAM STACKING

  • Hong, Sang-Hoon;Kim, Sang-Wan;Won, Joong-Sun
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.308-311
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    • 2002
  • Radar interferometric phase is sensitive to both ground topography and coherent surface displacement. The basic tactics of differential interferometric synthetic aperture radar (DInSAR) technique are to separate the two effects. Applications of DInSAR to Duk-Po area in Busan were studied. In the study area, an abrupt subsidence, possibly caused by sub-way construction, was observed by JERS-1 SAR interferometry. Differential interferograms were generated using twenty-three JERS-1 SAR data acquired between April 24, 1992, and August 7, 1998. Because the area is relatively flat with little topographic relief the topographic effects were not removed. A phase filtering and interferogram techniques were applied to increase fringe clarity as well as to decrease decorrelation error. The stacking improves the quality of interferograms especially when the displacement is discontinuous. The interferograms clearly show the evidence of subsidence along Duk-Po subway railroad. These results demonstrate that the interferogram stacking technique can improve the detectability of radar interferometry to an abrupt displacement and DInSAR is useful to geological engineering applications.

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INVESTIGATION OF BAIKDU-SAN VOLCANO WITH SPACE-BORNE SAR SYSTEM

  • Kim, Duk-Jin;Feng, Lanying;Moon, Wooil-M.
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.148-153
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    • 1999
  • Baikdu-san was a very active volcano during the Cenozoic era and is believed to be formed in late Cenozoic era. Recently it was also reported that there was a major eruption in or around 1002 A.D. and there are evidences which indicate that it is still an active volcano and a potential volcanic hazard. Remote sensing techniques have been widely used to monitor various natural hazards, including volcanic hazards. However, during an active volcanic eruption, volcanic ash can basically cover the sky and often blocks the solar radiation preventing any use of optical sensors. Synthetic aperture radar(SAR) is an ideal tool to monitor the volcanic activities and lava flows, because the wavelength of the microwave signal is considerably longer that the average volcanic ash particle size. In this study we have utilized several sets of SAR data to evaluate the utility of the space-borne SAR system. The data sets include JERS-1(L-band) SAR, and RADARSAT(C-band) data which included both standard mode and the ScanSAR mode data sets. We also utilized several sets of auxiliary data such as local geological maps and JERS-1 OPS data. The routine preprocessing and image processing steps were applied to these data sets before any attempts of classifying and mapping surface geological features. Although we computed sigma nought ($\sigma$$^{0}$) values far the standard mode RADARSAT data, the utility of sigma nought image was minimal in this study. Application of various types of classification algorithms to identify and map several stages of volcanic flows was not very successful. Although this research is still in progress, the following preliminary conclusions could be made: (1) sigma nought (RADARSAT standard mode data) and DN (JERS-1 SAR and RADARSAT ScanSAR data) have limited usefulness for distinguishing early basalt lava flows from late trachyte flows or later trachyte flows from the old basement granitic rocks around Baikdu-san volcano, (2) surface geological structure features such as several faults and volcanic lava flow channels can easily be identified and mapped, and (3) routine application of unsupervised classification methods cannot be used for mapping any types of surface lava flow patterns.

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