Quantitative Analysis of Urban Polycentric Interaction Using Nighttime Light Data: A Case Study of Shanghai, China

Abstract

The urban polycentric structure is connected to the economy and enormously impacts socio-economic development and policies. Unlike traffic data and big geographic data, remote sensing data have shown an accessible way to measure urban spatial interaction. However, most existing studies only focused on the interaction among cities rather than within cities. Meanwhile, the urban spatial interaction, which should be directional, was always expressed as an undirected graph. Therefore, this study developed a network-based radiation model using nighttime light remote sensing data and mapped a directed interaction network (inward and outward direction) among urban centers. Taking the region within the outer ring of Shanghai as an example, the taxi trajectory data were adopted to validate the result with the R 2 of 0.61. We discovered that: (1) The urban polycentric interaction network is dumbbell-shaped with an east-west development corridor crossing the main center and connecting two main urban center clusters. (2) The in-strength and out-strength interaction of each urban center have a similar distribution. The urban centers with higher in-strength and out-strength are mainly concentrated toward the main center, especially in the east-west direction. (3) At the urban center level, the total inward interaction is slightly higher than the total outward interaction of most urban centers. Spatially, an unbalanced distribution was found. In summary, our proposed method effectively indicates the urban polycentric interaction and is applicable to other regions since it requires no arbitrary parameters and the input data (e.g., nighttime light data) is readily available.

Research on Temporal and Spatial Distribution Pattern of the Night-Time Economy Supported by Multi-Source Data—A Case Study of Xiamen City, Fujian Province, China

“…Lighting is a necessary condition for modern human production and life at night. With the development of image enhancement and processing technology [19], satellite images of nighttime lights are increasingly applied to estimate economic growth [9], evaluate the development level of townships and transport hubs [20], visualize the spatial distribution of the GDP [21], explore human mobility [22], and identify regional economic centers [23]. However, these researchers ignored that a night light image itself is a direct reflection of the illumination at night.…”

Poverty Estimation Using a ConvLSTM-Based Model With Multisource Remote Sensing Data: A Case Study in Nigeria

“…Unlike typical statistical or survey data, remote sensing data are objective and stable sources of information that can be updated quickly [19]. Nighttime light (NTL) remote sensing data captures Earth's NTL from space and has been widely used to monitor human economic activities, such as impervious surfaces [20], food security [21], carbon dioxide emissions [22], urban development [23][24][25][26], GDP [27,28], electricity consumption [29], and population changes [30]. Because NTL intensity can effectively reflect the regional economic situation [31], it is commonly used for poverty assessments [32][33][34][35].…”