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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Li-hua Wang Yun-xuan Zhou Xing Li |
| Copyright Year | 2010 |
| Description | Author affiliation: State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China (Li-hua Wang; Yun-xuan Zhou; Xing Li) |
| Abstract | Optical remote sensing (ORS) technology has been extensively used for the investigation of the environment and resources. Considering it is heavily constrained by the weather conditions, especially in the coastal zone, the round-the-clock SAR (Synthetic Aperture Radar) data are chosen to compensate for the shortcomings of optical data. In this paper, we will use the fusion image of ASAR and TM to identify five land cover types in Chongming Dongtan. And the SVM algorithm is adopted because of its capability to take numerous and heterogeneous parameters into account. Results have been shown that the fusion data of SAR and ORS is particularly suited to account for the rainy and cloudy weather in costal zone. And the SVM algorithm has attained a high level of classification performance with the overall accuracy 90.83%. |
| Starting Page | 2134 |
| Ending Page | 2138 |
| File Size | 721428 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424465132 |
| e-ISBN | 9781424465163 |
| DOI | 10.1109/CISP.2010.5647331 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-16 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines Image color analysis SAR Scattering Vegetation mapping classification accuracy Classification algorithms SVM optical remote sensing Remote sensing Backscatter |
| Content Type | Text |
| Resource Type | Article |
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