Abstract
Three AWiFS scenes from three intra-annual time periods were explored for land cover mapping of mainland Portugal in an annual operational basis. Two different classification approaches were tested: a more conventional parametric classifier, the maximum likelihood classifier, and a nonparametric classifier, a decision tree. Several tests were designed to evaluate the most suitable classification approach, training sample size effect on the classification accuracy and the images's ability for land cover mapping of mainland Portugal. Overall accuracy values achieved were low regardless the classification approach and training sample size, which suggests that AWiFS images are not suitable for land cover mapping the Portuguese landscape. Results also reveal that decision tree classifier is advantageous relatively to maximum likelihood classifier concerning training size and its characteristics.
Original language | English |
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Title of host publication | REMOTE SENSING FOR A CHANGING EUROPE |
Subtitle of host publication | Proceedings of the 28th Symposium of the European Association of Remote Sensing Laboratories, Istanbul, Turkey, 2–5 June 2008 |
Publisher | IOS Press |
Pages | 356-363 |
ISBN (Print) | 978-1-58603-986-8 |
DOIs | |
Publication status | Published - 2009 |
Event | 28th Symposium of the European Association of Remote Sensing Laboratories - Duration: 1 Jan 2009 → … |
Conference
Conference | 28th Symposium of the European Association of Remote Sensing Laboratories |
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Period | 1/01/09 → … |
Keywords
- Land cover map
- AWiFS
- Decision trees
- Maximum likelihood
- Portugal