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Mapping tropical coastal vegetation using JERS-1 and ERS-1 radar data with a decision tree classifier

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Abstract:

The objective of this paper is to investigate the complementarity of JERS-1 and ERS-1 data for mapping coastal tropical regions. We use a decision tree classifier to classify a coastal region of Gabon and describe the feature contribution using the decision tree diagram. The JERS-1 Global Rain Forest Mapping (GRFM) and ERS-1 Central Africa Mosaic Project (CAMP) datasets are used. The result is a land cover map of the west coast of Gabon. The analysis explicitly shows the complementary characteristics of the L- and C-band Synthetic Aperture Radar (SAR) instruments. We demonstrate the usefulness of combined use of L- and C-band data for large area mapping of coastal regions, especially in flooded areas for discrimination of high and low mangroves as well as grasses and tree swamps. The overall classification accuracy increases by 18% over single band classification.

Document Type: Research Article

DOI: https://doi.org/10.1080/01431160110092984

Publication date: 2002-04-10

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