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| Content Provider | Springer Nature Link |
|---|---|
| Author | Trisasongko, Bambang H. |
| Copyright Year | 2010 |
| Abstract | Tropical forest degradation has been a major area of interest for the remote sensing community. Various sensors have been dedicated to monitor its changes; however, due to widespread cloud cover, limited information could be retrieved through optical datasets. Synthetic Aperture Radar (SAR) sensors provide an alternative for such purpose. This paper discusses an application of SAR polarimetry data coupled with the Cloude-Pottier decomposition theorem as a non-invasive method for the assessment of degraded forests in Indonesia. It was found that Cloude-Pottier feature space provides a convenient way to describe degradation levels, especially using P-band datasets. Both L- and P-band data provided appreciable classification accuracy through Support Vector Machine methods. Results suggest that fully polarimetric SAR data, combined with polarimetric parameters, can be useful for operational monitoring. |
| Starting Page | 1 |
| Ending Page | 13 |
| Page Count | 13 |
| File Format | |
| ISSN | 15572064 |
| Journal | Sensing and Imaging: An International Journal |
| Volume Number | 11 |
| Issue Number | 1 |
| e-ISSN | 15739317 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2010-02-09 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | SAR polarimetry Cloude-Pottier decomposition Support vector machine Forest Mining Imaging Radiology Microwaves, RF and Optical Engineering Electrical Engineering |
| Content Type | Text |
| Resource Type | Article |
| Subject | Instrumentation Electrical and Electronic Engineering |
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