Geo-referencing of continental-scale JERS-1 SAR mosaics based on matching homologous features with a digital elevation model: theory and practice

• Published in: International journal of remote sensing Vol. 33; no. 8; pp. 2413 - 2433
• Main Authors: Kropáček, Jan, De Grandi, Gianfranco, Rauste, Yrjö
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 01.01.2012
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; boreal forests; Earth sciences; Earth, ocean, space; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Landsat; rain forests; spatial distribution; surface water; synthetic aperture radar; Teledetection and vegetation maps; topography; Africa; Siberia; Eurasia; Russian Federation; shorelines; practice; Rain forest; simulation; global; Image; Information; matching; mosaics; data bases; Synthetic aperture radar; Littoral zone; Boreal forest; water body; Space remote sensing; Landsat; topography; L band; digital elevation models; cartography; Landsat satellite; surface water; geometry; radar methods; theory
• ISSN: 1366-5901; 0143-1161; 1366-5901
• DOI: 10.1080/01431161.2011.609843

An effective method for a posteriori ortho-rectification of continental-scale synthetic aperture radar (SAR) mosaics using a digital elevation model (DEM) has been developed. The method is based on homologous feature matching between the DEM and a simulated SAR image. The simulated image is derived from the radar-viewing geometry, topographic information and contextual information provided by the Shuttle Radar Topography Mission (SRTM), shorelines and water bodies database (SWBD) and GeoCover Landsat mosaics. Two large L-band SAR mosaics (the global boreal forest mapping (GBFM) Siberia mosaic and the global rain forest mapping (GRFM) Africa mosaic), assembled from the Japanese Earth Resources Satellite-1 (JERS-1) data, were accurately geo-referenced and ortho-rectified. The GRFM Africa mosaic was also radiometrically corrected for topographic effects. The accurate co-registration with the DEM allows for improved classification methods based on the combination of SAR backscatter with terrain features. Comparison of the revised GBFM and GRFM mosaics with a forthcoming set of continental-scale mosaics assembled from the Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data will offer a unique possibility for change detection studies over the Tropical and Boreal forest zones with a temporal spacing of some 10 years.