The saturation and overflow effects of DMSP/OLS data tend to misclassified the boundary pixels between urban built-up and non-urban built-up areas as urban built-up areas, which will affect the extraction accuracy of urban built-up areas. This paper proposed an urban built-up area extraction method based on the combination value of light brightness. By determining the accurate boundary location between built-up and non-built-up area, the authors tried to improve the extraction accuracy of built-up area. First, the combination of the brightness of the light is constructed to highlight the difference between the urban built-up and the non-urban built-up area. Second, the Mann-Kendall non-parametric test method is used to determine the change-point of the combination value of light brightness of adjacent pixels, which is used as edge pixel to identify urban built-up area. The relevant experiments were carried out in Guangzhou, Shenzhen, Wuhan and Nanjing. The results show that, the average area error is only 10.89%, the average coverage of spatial overlap is 84.93%, the kappa coefficient is 0.863 0, and the overall accuracy is 91.68%. Compared with threshold method, NSA and feature combination method, this method can reach the highest extraction accuracy, and hence the authors provide an effective and reliable method for extracting urban built-up area based on nighttime light data.
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2020, Vol. 32 
), 孙文彬(
