Spatiotemporal Heterogeneity Analysis of Yangtze River Delta Urban Agglomeration: Evidence from Nighttime Light Data (2001–2019)

Min Yu,Zhouwei Liao,Yanning Guan,Zhuangzhuang Tian,Xiaoxin Zhang,Shan Guo,Klaus Fraedrich,Danlu Cai,Chunyan Zhang

doi:10.3390/rs13071235

Abstract

The long-term changes of the relationship between nighttime light and urbanization related built-up areas are explored using nighttime light data obtained from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS, data before 2013) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP/VIIRS, data after 2012) and information of the spatiotemporal heterogeneity of urban evolution. This study assimilates two datasets and diagnoses the spatial heterogeneity in administrative city scale based on built-up area tendencies, temporal heterogeneity in pixel scale based on nighttime light intensity tendencies, and GDP associated spatiotemporal variability over the Yangtze River Delta comparing the first two decades of this century (2001–2010 versus 2011–2019). The analysis reveals the following main results: (1) The built-up areas have generally increased in the second period with the center of fast expansion moving southward, including Suzhou-Wuxi-Changzhou, Hangzhou, Ningbo, Nanjing, and Hefei. (2) Urban development in the original city core has saturated and is spilling over to the suburbs and countryside, leading to nighttime light intensity tendency shift from a “rapid to moderate” and a “moderate to rapid” development (a “hot to cold” and a “cold to hot” spatial clustering distribution). (3) The tendency shifts of built-up area and nighttime light intensity occur most frequently in 2010, after which the urban development is transforming from light intensity growth to built-up area growth, particularly in the developed city cores. The urban agglomeration process with nighttime light intensity reaching saturation prior to the urban development spreading into the surrounding suburbs and countryside, appears to be a suitable model, which provides insights in addressing related environmental problems and contribute to regional sustainable urban planning and management.

Highlights

Geometric correction was applied to DMSP/OLS data by manual interpretation comparing with the NPP/VIIRS data
To obtain a consistent long nighttime light series, the approach developed by Zhao et al [30] is employed: first, a logarithmic (or inverse hyperbolic sine (IHS)) transformation is performed to adjust the range of the NPP/VIIRS data to be comparable with the DMSP/OLS data
Gibson [42] indicates that using the NPP/VIIRS annual composite for 2015 (T2015 ) as the background noise mask has the advantage of creating a like-with-like series to link to DMSP/OLS

Summary

Introduction

Urban agglomeration is a highly developed spatial form of integrated cities, which can be defined as a contiguously built-up area, shaped by one core city or by several adjacent cities, sharing industry-, infrastructure-, and housing-land use with high-density levels with embedded open spaces [1,2,3]. It has been witnessed worldwide in recent decades as one of the most significant changes in human society, and as a “dynamic, multidimensional socio-spatial process” [4]. To obtain a consistent long nighttime light series, the approach developed by Zhao et al [30] (or Gibson et al [43]) is employed: first, a logarithmic (or inverse hyperbolic sine (IHS)) transformation is performed to adjust the range of the NPP/VIIRS data to be comparable with the DMSP/OLS data.

Methods

Results

Discussion

Conclusion