Abstract: High remote sensing image has been applied in extracting urban green space information widely, however effectiveness of fusion algorithms need further research. GS, PCA, Ehlers, Wavelet, HIS are applied to merger of urban WorldView-2 and PL-1A image. Then the effectiveness of fusion algorithms are evaluated according to quality of fusion and accuracy of urban green space information extraction. The results show that GS fusion algorithm achieves the best results. Quality of WorldView-2 fusion images using PCA and Ehlers fusion algorithms is better than that of PL-1A fusion images applied same algorithms. Wavelet and HIS are worst in five algorithms. Accuracy of urban green space extraction based GS, PCA, Ehlers, and Wavelet fusion images are better than accuracy of multispectral images. In those four fusion algorithms, GS and PCA are best while Ehlers and Wavelet are slightly inferior. From what has been discussed above shows that fusion algorithms can improve the accuracy of green space information extraction obviously. The GS algorithm has best fusion result and good universality in five fusion algorithms.

Key words: urban green space, fusion image, information extraction, accuracy assessment