Fusion and classification of Beijing-1 small satellite remote sensing image for land cover monitoring in mining area |
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| Authors: | Peijun Du Linshan Yuan Junshi Xia Jianguo He |
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| Institution: | (1) Aviation and Aerial Photography Division, Digital Mapping Department, National Authority for Remote Sensing and Space Sciences, 23 Joseph Tito st., El Nozha El Gedida, P.O.Box 1564, Alf Maskan, Cairo, Egypt;(2) Engineering Applications and Water Division, Engineering Applications Department, National Authority for Remote Sensing and Space Sciences, 23 Joseph Tito st., El Nozha El Gedida, P.O.Box 1564, Alf Maskan, Cairo, Egypt |
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| Abstract: | In order to promote the application of Beijing-1 small satellite (BJ-1) remote sensing data, the multispectral and panchromatic
images captured by BJ-1 were used for land cover classification in Pangzhuang Coal Mining. An improved Intensity-Hue-Saturation
(IHS) fusion algorithm is proposed to fuse panchromatic and multispectral images, in which intensity component and panchromatic
image are combined using the weights determined by edge pixels in the panchromatic image identified by grey absolute correlation
degree. This improved IHS fusion algorithm outperforms traditional IHS fusion method to a certain extent, evidenced by its
ability in preserving spectral information and enhancing spatial details. Dempster-Shafer (D-S) evidence theory was adopted
to combine the outputs of three member classifiers to generate the final classification map with higher accuracy than that
by any individual classifier. Based on this study, we conclude that Beijing-1 small satellite remote sensing images are useful
to monitor and analyze land cover change and ecological environment degradation in mining areas, and the proposed fusion algorithms
at data and decision levels can integrate the advantages of multi-resolution images and multiple classifiers, improve the
overall accuracy and produce a more reliable land cover map. |
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