Urban Mapping Using Coarse SAR and Optical Data: Outcome of the 2007 GRSS Data Fusion Contest

Author

Pacifici, Fabio ; Frate, Fabio Del ; Emery, William J. ; Gamba, Paolo ; Chanussot, Jocelyn

Author_Institution

Dept. of Comput. Sci., Syst. & Production, Tor Vergata Univ., Rome

Volume

5

Issue

3

fYear

2008

fDate

7/1/2008 12:00:00 AM

Firstpage

331

Lastpage

335

Abstract

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.

Keywords

geophysical signal processing; neural nets; sensor fusion; spaceborne radar; synthetic aperture radar; terrain mapping; AD 2007; GRSS Data Fusion Contest; IEEE Geoscience and Remote Sensing Data Fusion Technical Committee; coarse SAR data; coarse optical data; land use-land cover map extraction; mapping accuracy; multisource coarse resolution data set; multitemporal resolution data set; pre-postprocessing enhanced neural classification; satellite sensors; synthetic aperture radar; urban mapping; Data fusion; European Remote Sensing satellite (ERS); Landsat; image classification; neural networks (NNs); urban remote sensing;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing Letters, IEEE

Publisher

ieee

ISSN

1545-598X

Type

jour

DOI

10.1109/LGRS.2008.915939

Filename

4476092