A new approach for urban-rural fringe identification: Integrating impervious surface area and spatial continuous wavelet transform

Abstract Urban-rural fringe is the frontier of urban expansion and the most dynamic area in urban region. Identifying the urban-rural fringe accurately is of great significance, as it helps to measure the extent of urbanization and its environmental effects from the urban-rural contrast perspective. However, traditional studies with spatial discrete data and threshold methods make it difficult to identify its boundary objectively and accurately. To solve this problem, a new approach was proposed in this study, integrating the spatial continuous data of impervious surface area (ISA) and the method of spatial continuous wavelet transform (SCWT). Taking Beijing City, one of the largest city in China, as a case, this study identified the boundary of urban-rural fringe, which extended mainly in the southwestern and northeastern direction, with the area increased by 18.75% between 2009 and 2014. The accuracy of the identification result was verified by spatial differentiation characteristics of nighttime light and normalized difference vegetation index. Meanwhile, when compared with the subjective threshold method, it showed that SCWT could identify the fringe more accurately. And the ISA based identification result was more consistent with the actual spatial patterns of urban development in Beijing City than land use degree index based one, which showed the remotely sensed spatial continuous data performed more effectively well on identifying the urban-rural fringe. The proposed approach can identify the urban-rural fringe directly from remote sensing images, which is of great significance to quickly urbanization monitoring and thus sustainable urban planning and management.

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