• Title/Summary/Keyword: RADARSAT/SAR

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Mapping Paddy Rice Varieties Using Multi-temporal RADARSAT SAR Images

  • Jang, Min-Won;Kim, Yi-Hyun;Park, No-Wook;Hong, Suk-Young
    • Korean Journal of Remote Sensing
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    • v.28 no.6
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    • pp.653-660
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    • 2012
  • This study classified paddy fields according to rice varieties and monitored temporal changes in rice growth using SAR backscatter coefficients (${\sigma}^{\circ}$). A growing period time-series of backscatter coefficients was set up for nine fine-beam mode RADARSAT-1 SAR images from April to October 2005. The images were compared with field-measured rice growth parameters such as leaf area index (LAI), plant height, fresh and dry biomass, and water content in grain and plants for 45 parcels in Dangjin-gun, Chungnam Province, South Korea. The average backscatter coefficients for early-maturing rice varieties (13 parcels) ranged from -18.17 dB to -6.06 dB and were lower than those for medium-late maturing rice varieties during most of the growing season. Both crops showed the highest backscatter coefficient values at the heading stage (late July) for early-maturing rice, and the difference was greatest before harvest for early-maturing rice. The temporal difference in backscatter coefficients between rice varieties may play a key role in identifying early-maturing rice fields. On the other hand, comparisons with field-measured parameters of rice growth showed that backscatter coefficients decreased or remained on a plateau after the heading stage, even though the growth of the rice canopy had advanced.

DTM GENERATION OF RADARSAT AND SPOT SATELLITE IMAGERY USING GROUND CONTROL POINTS EXTRACTED FROM SAR IMAGE

  • PARK DOO-YOUL;KIM JIN-KWANG;LEE HO-NAM;WON JOONG-SUN
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.667-670
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    • 2005
  • Ground control points(GCPs) can be extracted from SAR data given precise orbit for DTM generation using optic images and other SAR data. In this study, we extract GCPs from ERS SAR data and SRTM DEM. Although it is very difficult to identify GCPs in ERS SAR image, the geometry of optic image and other SAR data are able to be corrected and more precise DTM can be constructed from stereo optic images. Twenty GCPs were obtained from the ERS SAR data with precise Delft orbit information. After the correction was applied, the mean values of planimetric distance errors of the GCPs were 3.7m, 12.1 and -0.8m with standard deviations of 19.9m, 18.1, and 7.8m in geocentric X, Y, and Z coordinates, respectively. The geometries of SPOT stereo pair were corrected by 13 GCPs, and r.m.s. errors were 405m, 705m and 8.6m in northing, easting and height direction, respectively. And the geometries of RADARS AT stereo pair were corrected by 12 GCPs, and r.m.s. errors were 804m, 7.9m and 6.9m in northing, easting and height direction, respectively. DTMs, through a method of area based matching with pyramid images, were generated by SPOT stereo images and RADARS AT stereo images. Comparison between points of the obtained DTMs and points estimated from a national 1 :5,000 digital map was performed. For DTM by SPOT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. For DTM by RADARSAT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. These results met the accuracy of DTED level 2

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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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UTLIZIATION OF RADARSAT FOR FORECASTING OIL SLICKT RAJECTORY MOVEMENT

  • Marghany, Maged
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.435-437
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    • 2003
  • This study presents work to utilize RADARSAT SAR image for forecast oil slick trajectory movement. The fractal dimension algorithm used to detect oil slick. The Doppler frequency shift and quasi-linear model was used to simulate a current pattern from RADARSAT image. The Fay’s algorithm of oil slick spreading was developed based on a Doppler frequency shift model. Thus, the study shows that fractal dimension algorithm discriminated the oil slick from the surrounding water features. The quasi-linear model shows that the current pattern can be simulated from single RADARSAT image. The oil slick trajectory model shows that after 48 hrs, the oil slick parcels deposited along the coastal waters.

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Estimation of the Flood Area Using Multi-temporal RADARSAT SAR Imagery

  • Sohn, Hong-Gyoo;Song, Yeong-Sun;Yoo, Hwan-Hee;Jung, Won-Jo
    • Korean Journal of Geomatics
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    • v.2 no.1
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    • pp.37-46
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    • 2002
  • Accurate classification of water area is an preliminary step to accurately analyze the flooded area and damages caused by flood. This step is especially useful for monitoring the region where annually repeating flood is a problem. The accurate estimation of flooded area can ultimately be utilized as a primary source of information for the policy decision. Although SAR (Synthetic Aperture Radar) imagery with its own energy source is sensitive to the water area, its shadow effect similar to the reflectance signature of the water area should be carefully checked before accurate classification. Especially when we want to identify small flood area with mountainous environment, the step for removing shadow effect turns out to be essential in order to accurately classify the water area from the SAR imagery. In this paper, the flood area was classified and monitored using multi-temporal RADARSAT SAR images of Ok-Chun and Bo-Eun located in Chung-Book Province taken in 12th (during the flood) and 19th (after the flood) of August, 1998. We applied several steps of geometric and radiometric calculations to the SAR imagery. First we reduced the speckle noise of two SAR images and then calculated the radar backscattering coefficient $(\sigma^0)$. After that we performed the ortho-rectification via satellite orbit modeling developed in this study using the ephemeris information of the satellite images and ground control points. We also corrected radiometric distortion caused by the terrain relief. Finally, the water area was identified from two images and the flood area is calculated accordingly. The identified flood area is analyzed by overlapping with the existing land use map.

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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.

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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InSAR Studies of Alaska Volcanoes

  • Lu Zhong;Wicks Chuck;Dzurisin Dan;Power John
    • Korean Journal of Remote Sensing
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    • v.21 no.1
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    • pp.59-72
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    • 2005
  • Interferometric synthetic aperture radar (InSAR) is a remote sensing technique capable of measuring ground surface deformation with sub-centimeter precision and spatial resolution in tens-of­meters over a large region. This paper describes basics of InSAR and highlights our studies of Alaskan volcanoes with InSAR images acquired from European ERS-l and ERS-2, Canadian Radarsat-l, and Japanese JERS-l satellites.

Ship Detection by Satellite Data: Radiometric and Geometric Calibrations of RADARS AT Data (위성 데이터에 의한 선박 탐지: RADARSAT의 대기보정과 기하보정)

  • Yang, Chan-Su
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.10 no.1 s.20
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    • pp.1-7
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    • 2004
  • RADARSAT is one of many possible data sources that can play an important role in marine surveillance including ship detection because radar sensors have the two primary advantages: all-weather and day or night imaging. However, atmospheric effects on SAR imaging can not be bypassed and any remote sensing image has various geometric distortions, In this study, radiometric and geometric calibrations for RADARSAT/SAT data are tried using SGX products georeferenced as level 1. Even comparison of the near vs. far range sections of the same images requires such calibration Radiometric calibration is performed by compensating for effects of local illuminated area and incidence angle on the local backscatter, Conversion method of the pixel DNs to beta nought and sigma nought is also investigated. Finally, automatic geometric calibration based on the 4 pixels from the header file is compared to a marine chart. The errors for latitude and longitude directions are 300m and 260m, respectively. It can be concluded that the error extent is acceptable for an application to open sea and can be calibrated using a ground control point.

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Vessel Detection Using Satellite SAR Images and AIS Data (위성 SAR 영상과 AIS을 활용한 선박 탐지)

  • Lee, Kyung-Yup;Hong, Sang-Hoon;Yoon, Bo-Yeol;Kim, Youn-Soo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.2
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    • pp.103-112
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    • 2012
  • We demonstrate the preliminary results of ship detection application using synthetic aperture radar (SAR) and automatic identification system (AIS) together. Multi-frequency and multi-temporal SAR images such as TerraSAR-X and Cosmo-SkyMed (X-band), and Radarsat-2 (C-band) are acquired over the West Sea in South Korea. In order to compare with SAR data, we also collected an AIS data. The SAR data are pre-processed considering by the characteristics of scattering mechanism as for sea surface. We proposed the "Adaptive Threshold Algorithm" for classification ship efficiently. The analyses using the combination of the SAR and AIS data with time series will be very useful to ship detection or tracing of the ship.