| Titre | Urban Mapping Using Coarse SAR and Optical Data: Outcome of the 2007 GRSS Data Fusion Contest |
| Type de publication | Journal Article |
| Nouvelles publications | 2008 |
| Auteurs | Pacifici, F., F. Del Frate, W. J. Emery, P. Gamba, and J. Chanussot |
| Journal | IEEE Geoscience and Remote Sensing Letters |
| Volume | 5 |
| Fascicule | 3 |
| Pagination | 331 - 335 |
| Année de publication | 2008 |
| Numéro | 1545-598X |
| Mots clés | AD 2007, coarse optical data, coarse SAR data, data fusion, European Remote Sensing satellite (ERS), geophysical signal processing, GRSS Data Fusion Contest, IEEE Geoscience and Remote Sensing Data Fusion Technical Committee, image classification, land use-land cover map extraction, Landsat, mapping accuracy, multisource coarse resolution data set, multitemporal resolution data set, neural nets, neural networks (NNs), pre-postprocessing enhanced neural classification, satellite sensors, sensor fusion, spaceborne radar, synthetic aperture radar, terrain mapping, urban mapping, urban remote sensing |
| Résumé | The 2007 data fusion contest that was organized by the IEEE Geoscience and Remote Sensing Data Fusion Technical Committee was dealing with the extraction of a land use/land cover maps in and around an urban area, exploiting multitemporal and multisource coarse-resolution data sets. In particular, synthetic aperture radar and optical data from satellite sensors were considered. Excellent indicators for mapping accuracy were obtained by the top teams. The best algorithm is based on a neural classification enhanced by preprocessing and postprocessing steps. |
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Urban Mapping Using Coarse SAR and Optical Data: Outcome of the 2007 GRSS Data Fusion Contest
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