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Poster Session 1
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Supervised Classification
of Multi-Temporal Remote Sensing Images
Case 4
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(b) |
(c) |
Fig.4 (a) simulated 1st-period image; (b) 2nd-period image (case 4); (c) classification image
Case 4 represents the situation with 'increase' in class numbers, and 'change' in both class contents and class positions. The testing results are showing in Figure 4. The visual inspection (Fig.4(b) and (c)) and 97% overall accuracy indicate a successful classification.
Case 5
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(b) |
(c) |
Fig.5 (a) simulated 1st-period image; (b) 2nd-period image (case 5); (c) classification image
Case 5 represents the situation with 'decrease' in class numbers, and 'change' in both class contents and class positions. The testing results are showing in Figure 5. The visual inspection (Fig.5(b) and (c)) and 99% overall accuracy indicate a successful classification.
4. Conclusion
This study proposes a supervised fuzzy classification for multi-temporal remote sensing images. The class variation between multi-temporal images normally requires the selection of training data for every image when performing classification. An automatic procedure to generate the training data for multi-temporal image classification is presented here. The procedure combines the classification map from first-period image and the fuzzy training method to automatically collect the training data for second-period image. A series of simulated images are created for testing the proposed method. Their results suggest that the practical application of the method to the multi-temporal remote sensing images can be expected.
References
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Baber, M. L., D. Wood, and R. A. McBride, 1985. Classification of Corn and Soybeans Using Multitemporal Thematic Mapper Data. Remote Sensing of Environment, Vol. 16, pp.175-181.
- Lillesand, T. M., and R. W. Kiefer, 2000. Remote Sensing and Image Interpretation. 4th edition, John Wiley & Sons, Inc,.
- Richards, J. A., 1993. Remote Sensing Digital ImageAnalysis: An Introduction. 2nd Ed., Springer-Verlag Berlin Heidelberg.
- Schowengerdt, R. A., 1997. Remote Sensing: Models and Methods for Image Processing . 2nd Edition, Academic Press, pp. 522.
- Wang, F., 1990. Fuzzy Supervised Classification of Remote Sensing Images. IEEE Trans. on Geoscience and Remote Sensing, GE-28(2), pp. 194-201.
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