| Title | RADARSAT-2 Stereoscopy and Polarimetry for 3-D Mapping |
| Download | Downloads (Preprint) |
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| Licence | Please note the adoption of the Open Government Licence - Canada
supersedes any previous licences. |
| Author | Toutin, T |
| Source | Canadian Journal of Remote Sensing vol. 30, issue 3, 2004 p. 496-503, https://doi.org/10.5589/m03-079 |
| Image |  |
| Year | 2004 |
| Alt Series | Earth Sciences Sector, Contribution Series 20043276 |
| Publisher | Informa UK Limited |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Subjects | geophysics; remote sensing; mapping techniques; topography; RADARSAT-2; synthetic aperture radar surveys (SAR) |
| Illustrations | tables; graphs |
| Released | 2014 06 02 |
| Abstract | Based on research studies over the last twenty years with different satellite synthetic aperture radar (SAR) sensors, a short review of elevation modeling, digital terrain model (DTM) generation and 3D
cartographic feature extraction using stereoscopic and polarimetric methods is given. The results of these research studies were used to evaluate the potential of RADARSAT-2 and three of its new characteristics for mapping applications: Ultra-Fine
mode, better orbit knowledge and polarimetry. Stereoscopy and polarimetry could be used to improve the DTM generation when compared to RADARSAT-1. In the best case, 5-m accuracy (68% confidence level) could be expected in moderate topography. 3D
feature extraction using stereoscopic Ultra-Fine mode data could meet the National Topographic Data Base standard (better than 10-m positioning, 90% confidence level). Polarimetry with two images from crossing orbits (quasi-orthogonal in North) could
also be used for DTM generation depending of the topographic and land-cover conditions. The major drawback is the complex scattering models over forest or agricultural lands with C-band SAR data. In short term, the method could be applied in bare
surfaces. All these forecast improvements should be confirmed with real data. |
| GEOSCAN ID | 220078 |
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