Abstract
For purpose of improving the accuracy of the built-up quick map**, this paper proposed an improved optimal segmentation threshold algorithm, namely the improved double-window flexible pace search (IDFPS) approach, by redesigning the valuation criteria and the sampling method based on the double-window flexible pace search (DFPS) approach. Moreover, the Normalized Difference Built-up Index (NDBI), the Index-based Built-up Index (IBI), the Enhanced Built-up and Bareness Index (EBBI) and the Urban Index (UI) inversed from Landsat 5 TM images were used for quick map** by the IDFPS approach and the DFPS approach in different geographical areas. Results from the experiments exemplified by Chongqing (a mountain city) and Chengdu (a plain city) showed that the IDFPS approach was comprehensively superior to the DFPS approach. The IDFPS approach had more than 4.30% higher overall accuracy and 0.12 higher Kappa coefficients than the DFPS approach when both were implemented simultaneously at both the above-mentioned study areas. Besides, a new discovery in this paper was found that the UI had a better performance with higher overall accuracy and Kappa coefficient, lower omission error and commission error than the NDBI, IBI and EBBI because of the strong relationship between the UI and the density of built-up land. This new method has an important reference value for built-up quick map** and some other applied researches.
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Acknowledgements
This work is supported by the Special Innovation Project of Society, Livelihood and Technology of Chongqing (cstc2015shmszx00010), the Special Foundation of Postdoctoral Scientific Research Project of Chongqing (Xm2016081) and the Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJ120517, KJ1400420). The authors wish to thank the Institute of Remote Sensing and Digital Earth, Chinese Academic of Sciences for the availability of the satellite data, and the NASA for the atmospheric correction tool.
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DOI: https://doi.org/10.1007/s12524-016-0656-4