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REMOTE-SENSING EXPERT CLASSIFICATION OF LAND USE/LAND COVER TYPES USING FRACTAL DIMENSIONS OVER A SUBTROPICAL HILLY REGION IN CHINA

College of Resources, Shijiazhuang University of Economics, No. 136 Huai'an East Road, Shijiazhuang, Hebei 050031, China

State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China

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ZIYU LIN

College of Earth Science and Survey-Cartography Engineering, East China Institute of Technology, Fuzhou, Jingxi Province 344000, China

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XIAOZHOU LI

College of Resources, Shijiazhuang University of Economics, No. 136 Huai'an East Road, Shijiazhuang, Hebei 050031, China

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https://doi.org/10.1142/S0218348X11005452Cited by:0 (Source: Crossref)

Abstract

In the work, a simple and reliable algorithm is presented to calculate the fractal dimension of single pixel for the remote sensing images, and the fractal dimension values obtained by the algorithm proposed in this work have positive correlation with the complexity of surface features. On the basis of a scene of Landsat7 ETM+ (i.e., Enhanced Thematic Mapper Plus) data and the proposed algorithm, expert classification models and fractal technique were introduced to identify the ground objects in a Chinese subtropical hilly region, where surface features are very diverse and complex. In the work, the different land use/land cover types, especially the different vegetation categories were successfully identified using the ETM+ image, and this classification has an overall accuracy of 80.25% and a K_hat of 0.7738, which are higher than those of the traditional supervised classification.

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