Change Detection Using Original and Fused Landsat and Worldview Images

In this paper, we present some preliminary results on change detection using satellite images. We first present a change detection framework that incorporates multiple change detection algorithms. A number of change detection maps, including normalized difference of vegetation index (NDVI), nonhomogeneous feature difference (NFHD), global Reed-Xiaoli (GRX), chronochrome (CC), etc. are integrated to generate the final change map. We then present an algorithm to fuse low spatial resolution but high temporal Landsat and high spatial resolution but low temporal resolution Worldview images. Finally, we compare change detection results using pure Landsat images, pure Worldview images, and fused images. Our results indicate that there is definitely some advantages in using fused images for change detection. It was observed that change maps based on the fused images are slightly better than that of using the pure Landsat images and are worse than the pure Worldview images maps. Consequently, more research is needed in generating high quality fused images so that change detection using fused images can be further improved.

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