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

Jan Kropácek, Gianfranco De Grandi (Corresponding Author), Yrjö Rauste

Research output: Contribution to journalArticleScientificpeer-review

6 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)2413-2433
Number of pages21
JournalInternational Journal of Remote Sensing
Volume33
Issue number8
DOIs
Publication statusPublished - 2011
MoE publication typeA1 Journal article-refereed

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digital elevation model
synthetic aperture radar
boreal forest
topographic effect
Shuttle Radar Topography Mission
mosaic
JERS
backscatter
tropical forest
Landsat
shoreline
spacing
radar
geometry
method
rain forest

Cite this

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title = "Geo-referencing of continental-scale JERS-1 SAR mosaics based on matching homologous features with a digital elevation model: Theory and practice",
abstract = "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.",
author = "Jan Krop{\'a}cek and Grandi, {Gianfranco De} and Yrj{\"o} Rauste",
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Geo-referencing of continental-scale JERS-1 SAR mosaics based on matching homologous features with a digital elevation model : Theory and practice. / Kropácek, Jan; Grandi, Gianfranco De (Corresponding Author); Rauste, Yrjö.

In: International Journal of Remote Sensing, Vol. 33, No. 8, 2011, p. 2413-2433.

Research output: Contribution to journalArticleScientificpeer-review

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