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A method of extracting construction areas using Gaofen-1 remote sensing images
Author(s): Bin Wu; Chao Wang; Qiang Cong; Huan Yin; Jun Zhu; Suju Li; Dongxu He; Anzhi Yue
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Paper Abstract

The precisely extraction of construction areas in remote sensing images can play an important role in territorial planning, land use management, urban environments and disaster reduction. In this article, we propose a method for extracting construction areas using Gaofen-1 panchromatic remote sensing images by adopting the improved Pantex[1] (a procedure for the calculation of texture-derived built-up presence index) and unsupervised classification. First of all, texture cooccurrence measures of 10 different directions and displacements are calculated. In this step, we improve the built-up presence index that we use the windows size of 21*21 to calculate the GLCM contrast measure instead of 9*9 according to the spatial resolution of Gaofen-1 panchromatic image. Then we use the intersection operator “MIN” to combine the 10 different anisotropic GLCM contrast measure to generate the final built-up presence index result. At last, we use the unsupervised classification method to classify the Pantex result into two classes and the one with larger cluster center is the construction area class. Confusion matrix of Beijing-Tianjin-Hebei region experiment shows that this method can effectively and accurately extract the construction areas in Gaofen-1 panchromatic images with the overall accuracy of more than 92%.

Paper Details

Date Published: 9 October 2018
PDF: 7 pages
Proc. SPIE 10789, Image and Signal Processing for Remote Sensing XXIV, 107891D (9 October 2018); doi: 10.1117/12.2325040
Show Author Affiliations
Bin Wu, Aerospace Dong Fang Hong Satellite Co., Ltd. (China)
National Disaster Reduction Ctr. of China (China)
Chao Wang, Aerospace Dong Fang Hong Satellite Co., Ltd. (China)
Qiang Cong, Aerospace Dong Fang Hong Satellite Co., Ltd. (China)
Huan Yin, Aerospace Dong Fang Hong Satellite Co., Ltd. (China)
Jun Zhu, Aerospace Dong Fang Hong Satellite Co., Ltd. (China)
Suju Li, National Disaster Reduction Ctr. of China (China)
Dongxu He, Institute of Remote Sensing and Digital Earth (China)
Anzhi Yue, Institute of Remote Sensing and Digital Earth (China)


Published in SPIE Proceedings Vol. 10789:
Image and Signal Processing for Remote Sensing XXIV
Lorenzo Bruzzone; Francesca Bovolo, Editor(s)

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