• Title/Summary/Keyword: inverse geolocation algorithm

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Extraction of Ground Control Points from TerraSAR-X Data

  • Park, Jeong-Won;Hong, Sang-Hoon;Won, Joong-Sun
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.328-331
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    • 2008
  • It is possible to extract qualified ground control points (GCPs) solely from SAR data without published maps. TerraSAR-X is now in orbit and provides valuable data that have one of the highest spatial resolutions among civilian SAR systems. In this study, a sophisticated method for GCP coordinate extraction from TerraSAR-X stripmap mode data with a 3 m resolution was tested and the quality of the extracted GCPs was evaluated. An inverse-geolocation algorithm was applied to obtain GCPs from TerraSAR-X data. SRTM 90m DEM was used as an auxiliary data set for azimuth time correction of the SAR data. Mean values of the distance errors were 0.11 m and -3.96 m with standard deviations of 6.52 m and 5.11 m in easting and northing, respectively. The result is one of the best among GCPs possibly extracted from current civilian remote sensing systems. The extracted GCPs were used for geo-rectification of an IKONOS image, which demonstrated the applicability of the GCPs to geo-rectification of high resolution optic image. The method used in this study can be applied to KOMPSAT-5 for geo-rectification of high-resolution optic images acquired by KOMPSAT-2 or follow-up missions.

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Validation and selection of GCPs obtained from ERS SAR and the SRTM DEM: Application to SPOT DEM Construction

  • Jung, Hyung-Sup;Hong, Sang-Hoon;Won, Joong-Sun
    • Korean Journal of Remote Sensing
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    • v.24 no.5
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    • pp.483-496
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    • 2008
  • Qualified ground control points (GCPs) are required to construct a digital elevation model (DEM) from a pushbroom stereo pair. An inverse geolocation algorithm for extracting GCPs from ERS SAR data and the SRTM DEM was recently developed. However, not all GCPs established by this method are accurate enough for direct application to the geometric correction of pushbroom images such as SPOT, IRS, etc, and thus a method for selecting and removing inaccurate points from the sets of GCPs is needed. In this study, we propose a method for evaluating GCP accuracy and winnowing sets of GCPs through orientation modeling of pushbroom image and validate performance of this method using SPOT stereo pair of Daejon City. It has been found that the statistical distribution of GCP positional errors is approximately Gaussian without bias, and that the residual errors estimated by orientation modeling have a linear relationship with the positional errors. Inaccurate GCPs have large positional errors and can be iteratively eliminated by thresholding the residual errors. Forty-one GCPs were initially extracted for the test, with mean the positional error values of 25.6m, 2.5m and -6.1m in the X-, Y- and Z-directions, respectively, and standard deviations of 62.4m, 37.6m and 15.0m. Twenty-one GCPs were eliminated by the proposed method, resulting in the standard deviations of the positional errors of the 20 final GCPs being reduced to 13.9m, 8.5m and 7.5m in the X-, Y- and Z-directions, respectively. Orientation modeling of the SPOT stereo pair was performed using the 20 GCPs, and the model was checked against 15 map-based points. The root mean square errors (RMSEs) of the model were 10.4m, 7.1m and 12.1m in X-, Y- and Z-directions, respectively. A SPOT DEM with a 20m ground resolution was successfully constructed using a automatic matching procedure.