Extraction of urban built-up areas based on Sentinel-2Aand NPP-VIIRS nighttime light data
Zhili LIU1, Qibin ZHANG1, Depeng YUE1(), Yuguang HAO2, Kai SU1
1. College of Forestry, Beijing Forestry University, Beijing 100083, China 2. Experimental Center of Desert Forestry, Chinese Academy of Forestry, Bayannur 015200, China
Recently, the utilization of nighttime light data and optical remote sensing images to extract urban built-up areas has become a research hotspot, and the vegetation adjusted nighttime light data (NTL) urban index (VANUI) is widely used. However, it may easily lead to confusion of buildings and water bodies at the edge of the city, and the spatial resolution is relatively low. Therefore, some improvements were made on this index in this paper, and the building adjusted NTL urban index was proposed. The means was used to extract urban built-up areas in Baotou City in this paper. Firstly, normalized difference build-up index (NDBI) was extracted from Sentinel-2A image data and it was combined with NTL to obtain building adjusted NTL urban index BANUI with the spatial resolution of 20 m, which has higher spatial resolution and more information about the building. Finally, the watershed segmentation algorithm was applied to the extraction of urban built-up area of Baotou City from BANUI, VANUI and NTL, and the results were comparatively studied. The extraction results show that the overall precision of the urban built-up area extracted by BANUI could reach 93.61%, the Kappa coefficient is 0.793 4, the user accuracy is 81.34%, and the producer accuracy is 85.34%. The extraction results are consistent with the distribution of actual urban built-up area, and the accuracy is high. The result is better than the area extracted by the other two kinds of data. This method could provide some reference for the study of the extraction of urban built-up area from NTL, and could also be used to monitor the development of urban planning.
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2019, Vol. 31 
), 郝玉光2, 苏凯1
