Multi sensor data fusion for change detection

When performing post-classification comparison using images of different sensors, change detection is still possible even if images have different resolutions. However, in this case, change pixels are detected in the pixel size of coarser resolution image. This problem can be solved using higher resolution aerial photographs or panchromatic images if available. In multi sensor image fusion, images of higher resolution can be used to increase the resolutions of the multispectral images. In this study IKONOS panchromatic (1 m) and multispectral bands (4 m), taken in 2003, is fused using à trous image fusion algorithm to get 1 m multispectral image. Analogously, 1 m resolution aerial photograph (degraded down from its original 0.5 m resolution) and 30 m resolution ETM+ images, both taken in 2000, are fused to get 1 m resolution ETM+ multispectral image. Once both multispectral image data has 1 m resolution, post-classification comparison method is applied to detect changes occurred on the coastal zone in city of Trabzon. Preliminary results show that à trous fusion algorithm could keep the original spectral content of multispectral images in the fused products. Overall classification accuracies for fused ETM+ and IKONOS images are obtained as 92.40 and 95.2%, respectively. The area of filled earth on costal zone due to highway construction is detected as 186023 m, in 1 m precision.