Search

The smart city concept has taken center stage as a paradigm shift in urban governance, promising innovation, sustainability, and strategic upgrades, and drawing the attention of researchers globally. However, existing frameworks for assessing smart cities remain incomplete and simplistic. This paper aims to address the following question: what is the process and current situation of 30 capitals in China after the implementation of smart city construction, especially from the new perspective of social, physical, and informational space development? To this end, we focus on 30 national and provincial capitals in China, proposing a novel, tri-dimensional SPI model—Social, Physical, and Information space—for smart city spatial development assessment. Employing a robust methodological approach, including entropy weighting, coupled coordination degree models, and the Dagum Gini coefficient, we conduct a spatial development and coordination analysis of these cities from 2011 to 2021. In addition, we utilize BP neural networks to evaluate the contribution of each indicator to the spatial coupled coordination. Our findings indicate a steady increase in the spatial coupled coordination development level of smart capitals in China, alongside a narrowing disparity in development speeds across regions, resulting in a staggered spatial distribution pattern. Specifically, the Information space subsystem represents the most influential driver of coupled coordination. The significance of this research lies in its unique tri-dimensional spatial perspective, offering valuable insights into the spatial development and coordination discrepancies in the smart city concept. These insights offer evidence-based support for regional planning and optimization strategies in China. [ABSTRACT FROM AUTHOR]

[Display omitted] • We modified an ecological connectivity index considering ecological patches' quality. • We found landscape fragmentation and connectivity loss in Jiangsu from 2000 to 2018. • We gave suggestions on improving ecological network in Jiangsu, China. • The combined method can provide valuable tools for spatial planning. Urbanization in China has led to land-use changes resulting in landscape fragmentation, natural habitats loss and ecological connectivity decline. Aiming to support sustainable landscape planning, we proposed an integrated method for ecological structure assessment and optimization including morphological spatial pattern analysis (MSPA), minimal cumulative resistance (MCR) model and circuit theory to assess landscape fragmentation and ecological connectivity change at regional scale. A modified connectivity index is also proposed by employing the index of relative quality of ecological patches and corridors. We applied the combined methods to Jiangsu province in eastern China for multi-temporal landscape analysis and optimization. The results showed that the combined analysis revealed both fragmentation trend of ecological patches and ecological connectivity reduction with regard to all the species as a whole in the study area from 2000 to 2018. While, the trend has been slowed down to a certain extent lately, which is related to a series of ecological protection policies implemented in the study area, including ecological redlines policy, national park construction and returning marginal farmland into forest or grassland. Furthermore, suggestions for improving the ecological network in the study area were proposed. We proposed to improve the ecological network by fostering twenty-five potential ecological sources, maintaining twenty-five pinch points, restoring eleven dredging corridors and planning fifty-three stepping stones. Overall, we argue that the combined method can reveal both structural connectivity and functional connectivity, and the time series analysis can provide dynamics situation for better understanding and planning landscape process. It can also provide planners with a valuable strategic tool that advances the practical utility of landscape ecology techniques for spatial planning, and the combined application of the method helps to reduce some of the limitations of each individual method. [ABSTRACT FROM AUTHOR]