Bin Jiang

Urban structure can be better comprehended through analyzing its cores. Geospatial big data facilitate the identification of urban centers in terms of high accuracy and accessibility. However, previous studies seldom leverage multi-source geospatial big data to identify urban centers from a topological perspective. This study attempts to identify urban centers through the spatial integration of multi-source geospatial big data, including nighttime light imagery (NTL), building footprints (BFP) and street nodes of OpenStreetMap (OSM). We use a novel topological approach to construct complex networks from intra-urban hotspots based on the theory of centers by Christopher Alexander. We compute the degree of wholeness value for each hotspot as the centric index. The overlapped hotspots with the highest centric indices are regarded as urban centers. The identified urban centers in New York, Los Angeles, and …

According to Gestalt theory, any image is perceived subconsciously as a coherent structure (or whole) with two contrast substructures: figure and ground. The figure consists of numerous autogenerated substructures with an inherent hierarchy of far more smalls than larges. Through these substructures, the structural beauty of an image (L), or equivalently the livingness of space, can be computed by the multiplication of the number of substructures (S) and their inherent hierarchy (H). This definition implies that the more substructures something has, the more living or more structurally beautiful it is, and the higher the hierarchy of the substructures, the more living or more structurally beautiful. This is the nonrecursive approach to the structural beauty of images or the livingness of space. In this article we develop a recursive approach, which derives all substructures of an image (instead of its figure) and continues the …

EPB: Urban Analytics and City Science 2023, Vol. 0 (0) 1–11© The Author (s) 2023 Article reuse guidelines: sagepub. com/journals-permissions DOI: 10.1177/23998083231174748 journals. sagepub. com/home/epb

The third view of space states that space is neither lifeless nor neutral, but a living structure capable of being more living or less living. The living structure is defined as a physical and mathematical structure or simply characterized by the recurring notion (or the inherent hierarchy) of far more small substructures than large ones. The more substructures the more living, and the higher hierarchy of the substructures the more living. This paper seeks to lay out a new kind of GeoInformatics on the notion of living structure and on the third view of space. The new GeoInformatics aims not only to better understand the forms and processes of everyday space but also-maybe more importantly-to make the space or the Earth’s surface living or more living. We introduce two fundamental laws of living structure: Tobler’s law on spatial dependence or homogeneity and scaling law on spatial interdependence or heterogeneity. We …

Knowing the multi-level influences of determinants on medical-service resumptions is of great benefits to the policymaking for medical-service recovery at different levels of study units during the post-COVID-19 pandemic era. This article evaluated the hospital- and city-level resumptions of medical services in mainland China based on the data of location-based service (LBS) requests of mobile devices during the two time periods (December 2019 and from February 21 to March 18, 2020). We selected medical-service capacity, human movement, epidemic severity, and socioeconomic factors as the potential determinants on medical-service resumptions and then explicitly assessed their multi-level explanatory powers and the interactive effects of paired determinants using the geographical detector method. The results indicate that various determinants had different individual explanatory powers and interactive …

Urban structure can be better comprehended through analyzing its cores. Geospatial big data facilitate the identification of urban centers in terms of high accuracy and accessibility. However, previous studies seldom leverage multi-source geospatial big data to identify urban centers from a topological perspective. This study attempts to identify urban centers through the fusion of multi-source geospatial big data, including nighttime light imagery (NTL), building footprints (BFP) and street nodes of OpenStreetMap (OSM). We use a novel topological approach to construct complex networks from intra-urban hotspots based on the theory of centers by Christopher Alexander. We compute the degree of wholeness value for each hotspot as the centric index. The overlapped hotspots with the highest centric indices are regarded as urban centers. The identified urban centers in New York, Los Angeles, and Houston are consistent with their downtown areas, with overall accuracy of 90.23 percent. In Chicago, a new urban center is identified considering a larger spatial extent. Moreover, the proposed approach can effectively and objectively prevent counting those hotspots with high intensity values but few neighbors into the result. This study proposes a topological approach for urban center identification and a bottom-up perspective for sustainable urban design.

The disputed endorsement of inherited visceral and universal aesthetic preferences justifies the scientific validity of Alexander’s living structure. Apart from implying a resource-efficient way to promote well-being through urban design, the premise favors a collective approach to human self-perception and social justice. To better understand the contributions of Alexander, this article explores current knowledge about visceral and universal aesthetic preferences for living structure and if and how the new kind of city science, a mathematical model describing living structure, can be used for further testing. It also elaborates on the social impact of living structure, including its premise, and the potential of the new kind of city science to support social sustainability. A literature synthesis on living structure, the new kind of city science, and the premise showed a positive link between well-being and exposure to living structure. Limitations in research design nevertheless precluded conclusions about the associated visceral and universal aesthetic preferences. The new kind of city science was found appropriate for further research by holistically representing living structure. Moreover, like the hypothesized biological origin, social learning and sociocultural transmission were found to theoretically support the premise of universality and a collective approach to human identity and social justice, with further societal implications. For the concept of living structure to support social sustainability, it must be coupled with the promotion of empowerment and community mobilization. Hence, the operationalization of the new kind of city science should align with …

The large concentration of the world’s population in cities, along with rapid urbanization, have brought numerous environmental and socioeconomic challenges to sustainable urban systems (SUS). However, current SUS studies focus heavily on ecological aspects, rely on SUS indicators that are not supported by available data, lack comprehensive analytical frameworks, and neglect SUS regional differences. This paper develops a novel approach to assessing urban sustainability from regional perspectives using commonly enumerated socioeconomic statistics. It integrates land use and land cover change data and ecosystem service values, applies data mining analytics to derive SUS indicators, and evaluates SUS states as trade-offs among relevant SUS indicators. This synthetic approach is called the integrated socioeconomic and land-use data mining–based multi-objective assessment (ISL-DM-MOA). The paper presents a case study of urban sustainability development in cities and counties in Inner Mongolia, China, which face many environmental and sustainable development problems. The case study identifies two SUS types: (1) several large cities that boast well-developed economies, diversified industrial sectors, vital transportation locations, good living conditions, and cleaner environments; and (2) a few small counties that have a small population, small urban construction areas, extensive natural grasslands, and primary grazing economies. The ISL-DM-MOA framework innovatively synthesizes currently available socioeconomic statistics and environmental data as a unified dataset to assess urban sustainability as a total socio …