کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
555154 | 1451342 | 2006 | 9 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Multiple support vector machines for land cover change detection: An application for mapping urban extensions Multiple support vector machines for land cover change detection: An application for mapping urban extensions](/preview/png/555154.png)
The reliability of support vector machines for classifying hyper-spectral images of remote sensing has been proven in various studies. In this paper, we investigate their applicability for land cover change detection. First, SVM-based change detection is presented and performed for mapping urban growth in the Algerian capital. Different performance indicators, as well as a comparison with artificial neural networks, are used to support our experimental analysis. In a second step, a combination framework is proposed to improve change detection accuracy. Two combination rules, namely, Fuzzy Integral and Attractor Dynamics, are implemented and evaluated with respect to individual SVMs. Recognition rates achieved by individual SVMs, compared to neural networks, confirm their efficiency for land cover change detection. Furthermore, the relevance of SVM combination is highlighted.
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 61, Issue 2, November 2006, Pages 125–133