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Open Access Precise Georefrencing of Long Strips of ALOS Imagery

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The main obstacle to achieving high precision in georeferencing from high-resolution satellite imagery (HRSI) remains the need for provision of good quality ground control points (GCPs), whether the GCPs are used to remove biases in RPC triangulation or to support physical sensor orientation models. The provision of GCPs can be very costly and is often not feasible in remote regions, the very areas where mapping from satellite imagery shows significant potential. In order to drastically reduce the number of GCPs required for georeferencing from HRSI, a generic sensor orientation model incorporating strip adjustment capability has been adopted. Under this approach, the metadata for each separate scene is merged to produce a single, continuous set of orbit and attitude parameters, such that the entire strip of tens of images can be treated as a single image. The merging of orbit data results in a considerable reduction in both the number of unknown parameters and the number of required GCPs in the sensor orientation. RPCs are then generated from the adjusted orientation data for each image forming the strip or block. Application of the method to very long strips of ALOS PRSIM imagery is reported in this paper. The results of experimental testing indicate that one-pixel level accuracy can be achieved over strip lengths of more than 50 ALOS images, or 1,500 km, with as few as four GCPs.
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Document Type: Research Article

Publication date: January 1, 2011

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  • The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.

    Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies.
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