A New Approach for Detecting Urban Centers and Their Spatial Structure With Nighttime Light Remote Sensing

Abstract

Urban spatial structure affects many aspects of urban functions and has implications for accessibility, environmental sustainability, and public expenditures. During the urbanization process, a careful and efficient examination of the urban spatial structure is crucial. Different from the traditional approach that relies on population or employment census data, this research exploits the nighttime light (NTL) intensity of the earth surface recorded by satellite sensors. The NTL intensity is represented as a continuous mathematical surface of human activities, and the elemental features of urban structures are identified by analogy with earth’s topography. We use a topographical metaphor of a mount to identify an urban center or subcenter and the surface slope to indicate an urban land-use intensity gradient. An urban center can be defined as a continuous area with higher concentration or density of employments and human activities. We successfully identified 33 urban centers, delimited their corresponding boundaries, and determined their spatial relations for Shanghai metropolitan area, by developing a localized contour tree method. In addition, several useful properties of the urban centers have been derived, such as 9% of Shanghai administrative area has become urban centers. We believe that this method is applicable to other metropolitan regions at different spatial scales.