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Many countries have been constructing modern ground transportation projects. This raises questions about the impacts of such projects on development of impervious surfaces, yet there have been few attempts to systematically analyze these impacts. This paper attempts to narrow this information gap using the Hangzhou Bay Bridge project, China, as an exploratory case study. Using remotely sensed data, we developed a framework based on statistical techniques, wavelet multi-resolution analysis and Theil-Sen slope analysis to measure the changes in impervious surfaces. The derived changes were then linked to the bridge project with respect to socio-economic factors and land use development activities. The findings highlight that the analytical framework could reliably quantify the area, pattern and form of new urban area and urban intensification. Change detection analysis showed that urban area, GDP and the length of highways increased moderately in the pre-Hangzhou Bay Bridge period (1995–2002) while all of these variables increased more substantially during (2002–2009) and after (2009–2013) the bridge construction. The results indicate that the development of impervious surfaces due to new urban area came at the expense of permeable surfaces in the urban fringe and within rural regions, while urban intensification occurred mainly in the form of the redevelopment of older structures to modern high-rise buildings within existing urban regions. In the context of improved transportation infrastructure, our findings suggest that new urban area and urban intensification can be attributed to consecutive events which act like a chain reaction: construction of improved transportation projects, their impacts on land use development policies, effects of both systems on socio-economic variables, and finally all these changes influence new urban area and urban intensification. However, more research is needed to better understand this sequential process and to examine the broader applicability of the concept in other developing regions. [ABSTRACT FROM AUTHOR]

Urbanization has proceeded at an unprecedented speed in China during the last 20 years, resulting in extensive natural landscapes being transformed into impervious surface. The “ghost city” phenomenon has emerged due to the unreasonable urban expansion which far exceeds the actual demand of human habitat. Previously, few research studies have provided objective and sufficient knowledge with regard to identify “ghost cities” and their spatial distribution. In this paper, we proposed an effective and feasible framework to monitor and evaluate “ghost cities” utilizing nighttime light imagery obtained from day-night band (DNB) of Visible Infrared Imaging Radiometer Suite (VIIRS). We established a “ghost city” index (GCI) to quantify the intensity of the phenomenon in the northeast of China, and analyzed the spatial pattern of “ghost cities” for different GCI classes. Our results indicate that the intensity of “ghost city” phenomenon decrease from regions adjacent to the border to interior areas, whilst regions with extremely high GCI are mostly districts and county cities. Tests of typical regions show that non-lit built-up area for high GCI regions is spatially clustered and low population regions have a high tendency to suffer from the “ghost city” phenomenon. Therefore, our findings provide a spatial-explicit insight into the “ghost city” phenomenon, and consequently can be beneficial to assist sustainable urban planning. [ABSTRACT FROM AUTHOR]