Characterizing spatial patterns and driving forces of expansion and regeneration of industrial regions in the Hangzhou megacity, China

摘要

Urban growth in China has been increasingly investigated, but our knowledge of the expansion and regeneration of industrial regions is still inadequate for well-planning and well-management industry. This paper aims to investigate both industrial expansion from the potential environmental risk (PER) perspective and the re-use pattern of industrial regeneration between 2005 and 2017 in the Hangzhou megacity through integrating remotely sensed images and points of interest. The random forest model is further employed to explore driving forces of industrial expansion and regeneration. Our results showed that the industrial expansion of Hangzhou plunged from 3411.2 ha in 2005-2009 to 2109.6 ha in 2013-2017, while the proportion of expansion in the city periphery increased moderately by 12.1%. The proportion of industries with low PER increased, whereas the proportion of industries with medium PER plummeted. Moreover, industries with high PER tended to expand far away from the city center. Regarding regeneration, the city core witnessed this process during the early period, while the city periphery experienced considerable regeneration after 2013. The preferable choice of re-use type in the core and inner areas was residential land, followed by commercial land. The modeling results indicated that the economic development zone planning played a decisive role in expansion. However, the regeneration decision was largely affected by land price and population density. The distances to the river also contributed relatively highly to regeneration. Local government should strictly control the total supply of industrial land and accelerate industries transformation to reduce environmental pressure. Brownfield regeneration should formulate long-term regeneration scheme and appropriate remedial strategies, meanwhile, consider pluralistic regeneration modes and organic integration into urban functional space. (C) 2020 Elsevier Ltd. All rights reserved.