Abstract
In this study, we present a classification method using both optical and SAR data in order to perform landcover classification. First, different relevant parameters are derived from ERS-SAR data using multitemporal and interferometric analysis. Optical data are then used to define a set of training areas in order to perform a supervised classification. The results of classification using these techniques are compared with existing landuse maps and information derived from SPOT and Landsat data. We point out the usefulness of the coherence γtandemcomponent for this application. Moreover, we show that Δγ (difference between γtandemand γ35-day) can give additional useful information for the classification process.
Original language | English |
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Title of host publication | International Geoscience and Remote Sensing Symposium (IGARSS) |
Publisher | IEEE |
Pages | 813-815 |
Number of pages | 3 |
Publication status | Published - 1 Jan 1997 |
Externally published | Yes |
Event | Proceedings of the 1997 IEEE International Geoscience and Remote Sensing Symposium, IGARSS'97. Part 1 (of 4) - Singapore, Singapore Duration: 3 Aug 1997 → 8 Aug 1997 |
Conference
Conference | Proceedings of the 1997 IEEE International Geoscience and Remote Sensing Symposium, IGARSS'97. Part 1 (of 4) |
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Country/Territory | Singapore |
City | Singapore |
Period | 3/08/97 → 8/08/97 |
ASJC Scopus subject areas
- Computer Science Applications
- General Earth and Planetary Sciences