Paper
28 January 2002 Enhancement of tropical land cover mapping with wavelet-based fusion and unsupervised clustering of SAR and Landsat image data
Jacqueline Le Moigne, Nadine Laporte, Nathan S. Netanyahu
Author Affiliations +
Proceedings Volume 4541, Image and Signal Processing for Remote Sensing VII; (2002) https://doi.org/10.1117/12.454153
Event: International Symposium on Remote Sensing, 2001, Toulouse, France
Abstract
The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument. In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi- sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet- based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jacqueline Le Moigne, Nadine Laporte, and Nathan S. Netanyahu "Enhancement of tropical land cover mapping with wavelet-based fusion and unsupervised clustering of SAR and Landsat image data", Proc. SPIE 4541, Image and Signal Processing for Remote Sensing VII, (28 January 2002); https://doi.org/10.1117/12.454153
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Cited by 2 scholarly publications.
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KEYWORDS
Data fusion

Image fusion

Earth observing sensors

Landsat

Synthetic aperture radar

Wavelets

Remote sensing

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