Paper
14 November 2007 Novel urban land use/cover mapping approach based on the combination of fraction image and MNF image using decision tree method
Su Li, Wenzheng Li, Jianjun Zhou, Dafang Zhuang
Author Affiliations +
Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67903M (2007) https://doi.org/10.1117/12.752008
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
Urban land use/cover mapping is very important and it is the base of further urban analysis and research. Whereas urban land use/cover mapping of using remotely sensed images having medium spatial resolution presents numerous challenges due to the intensive heterogeneity of urban landscapes. In order to solve the above challenges and improve the accuracy of urban land cover/use mapping, we proposed a novel approach. Firstly, fraction image is attained based on spectral mixture analysis, and normalized MNF image is gained based on spectral normalization of the origin image and MNF transform. Secondly, combination image is produced based on fraction image and normalized MNF image. Finally, we performed decision tree classification to the combination image and gained urban land use/cover mapping. An ETM+ image acquired in 2001 was used as data source and Nanjing City, China was selected as study area. The accuracy of classification result was validated using IKONOS images of the study area acquired in 2000 and was compared with the other three classification schemes. Results show that this decision tree classification scheme based on the combination image of fraction image and normalized MNF image is superior to the other classification schemes evidently.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Su Li, Wenzheng Li, Jianjun Zhou, and Dafang Zhuang "Novel urban land use/cover mapping approach based on the combination of fraction image and MNF image using decision tree method", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67903M (14 November 2007); https://doi.org/10.1117/12.752008
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KEYWORDS
Image classification

Vegetation

Reflectivity

Earth observing sensors

Analytical research

Associative arrays

Shape memory alloys

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