The spatial distribution of public hospitals is a crucial factor in patient access and thus important to health equity, especially amid the COVID-19 pandemic crisis. In China, a major issue is to improve accessibility to public health care in the face of the limited space for further growth of cities. Therefore, this study assesses the current spatial accessibility patterns to public hospitals in Shanghai, using point density analysis and the comprehensively improved gravity model. The results identify the challenges of inadequate and imbalanced spatial distribution of public hospitals at the district level and show that the central urban area has more high-quality public health care resources and also has higher accessibility levels. Based on the comparisons in each district, the study also summarizes four policy implications for future public hospital and public health care system optimization in Shanghai, which can also be leveraged for the planning of public hospitals in other cities or other public service facilities. The first is to deploy public hospitals in areas with a large population and to introduce branches of top-level hospitals to noncentral areas. The second is the full utilization of community health service centers to relieve the burden of public hospitals to improve accessibility.

With the availability of computational resources, geographical information systems, and remote sensing data, urban growth modeling has become a viable tool for predicting urbanization of cities and towns, regions, and nations around the world. This information allows policy makers, urban planners, environmental and civil organizations to make investments, design infrastructure, extend public utility networks, plan housing solutions, and mitigate adverse environmental impacts. Despite its importance, urban growth models often discard the spatiotemporal uncertainties in their prediction estimates. In this paper, we analyzed the uncertainty in the urban land predictions by comparing the outcomes of two different growth models, one based on a widely applied cellular automata model known as the SLEUTH CA and the other one based on a previously published machine learning framework. We selected these two models because they are complementary, the first is based on human knowledge and pre-defined and understandable policies while the second is more data-driven and might be less influenced by any a priori knowledge or bias. To test our methodology, we chose the cities of Jiaxing and Lishui in China because they are representative of new town planning policies and have different characteristics in terms of land extension, geographical conditions, growth rates, and economic drivers. We focused on the spatiotemporal uncertainty, understood as the inherent doubt in the predictions of where and when will a piece of land become urban, using the concepts of certainty area in space and certainty area in time. The proposed analyses in this paper aim to contribute to better urban planning exercises, and they can be extended to other cities worldwide.

Introduction: Resistance and Response in PlanningSusan S. Fainstein and John ForesterIndigenous Resistance as Multiscalar, Insurgent Planning under EmpireKevin Lujan Lee and Tiara R. Na’putiMoving ...

This article suggests that a politics of difference demands a recognition of a paradox of universal welfare and a paradox of pirate modernities. The former rests on the fiscal cartography of institutional governance. The latter rests on a reframing of the notion of arrival in an age of globalisation. Both would benefit from an analytical blurring of perspectives that privilege the everyday world of cities of the Global South and those of the Global North.

In celebrating the volume by Alexander, Chatterji and Jalais “The Bengal Diaspora – Rethinking Muslim Migration”, this piece suggests that the text productively disturbs the central concepts of migration, diaspora and “Muslim”. This opens up further discussion about how interdisciplinary scholarship might rethink the multiple temporalities and cartographies of transnational identification.