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Abstract
In recent years, there has been significant focus on smart cities, on how they operate and develop, and on their technical and social challenges. The importance of infrastructure as a major pillar of support in cities, in addition to the rapid developments in smart city research, necessitate an up-to-date review of smart cities’ infrastructure issues and challenges. Traditionally, a majority of studies have focused on traffic control and management, transport network design, smart grid initiatives, IoT (Internet of Things) integration, big data, land use development, and how urbanization processes impact land use in the long run. The work presented herein proposes a novel review framework that analyzes how smart city infrastructure is related to the urbanization process while presenting developments in IoT sensor networks, big data analysis of the generated information, and green construction. A classification framework was proposed to give insights on new initiatives regarding smart city infrastructure through answering the following questions: (i) What are the various dimensions on which smart city infrastructure research focuses? (ii) What are the themes and classes associated with these dimensions? (iii) What are the main shortcomings in current approaches, and what would be a good research agenda for the future? A bibliometric analysis was conducted, presenting cluster maps that can be used to understand different research trends and refine further searches. A bibliographic analysis was then followed, presenting a review of the most relevant studies over the last five years. The method proposed serves to stress where future research into understanding smart systems, their implementation and functionality would be best directed. This research concluded that future research on the topic should conceptualize smart cities as an emergent socio-techno phenomenon.
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Research on Population Spatiotemporal Aggregation Characteristics of a Small City: A Case Study on Shehong County Based on Baidu Heat Maps. SUSTAINABILITY 2019. [DOI: 10.3390/su11226276] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Baidu heat maps can be used to explore the pattern of individual citizens conducting their activities and their agglomeration effects at the city scale. To investigate the spatiotemporal pattern of population aggregation and its relationship with land parcel attributes in small cities, we collected Baidu heat map data for a weekday and a weekend day in Shehong County and used Getis–Ord general G and the raster overlay methods to analyze population aggregation spatiotemporal characteristics. Chi-squared and Pearson correlation tests were used to analyze the correlation between population aggregation and land parcel attributes against three types of land parcel divisions: land use parcels, road network blocks, and grids. The results showed that, (1) for most hours of the workday, the degree of population aggregation was greater than on the weekend, and the fluctuation magnitude on the workday was higher as well. (2) On the weekday, people clustered and dispersed faster than on the weekend. (3) On the weekday and weekend, the spatial position of people aggregation was highly overlapping. (4) The correlation between the degree of population aggregation and the type of parcel was not significant. (5) Regarding different parcel unit sizes, the correlations between population aggregation degree and point of interest (POI) density, floor area ratio, and building density were significant and positively correlated, and the correlation coefficients increased as the grid size increased.
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Sustainable Land Urbanization and Ecological Carrying Capacity: A Spatially Explicit Perspective. SUSTAINABILITY 2018. [DOI: 10.3390/su10093070] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Rapid urbanization has become a common occurrence all over the world, particularly in developing countries, and has thus resulted in various eco-environmental problems. In China, urban land has expanded at an unprecedented rate in the past several decades, and sustainable land urbanization has become an important issue in promoting sustainable development. Hence, scholars have proposed ecological carrying capacity (ECC) as a solution to balance socio-economic development and the ecosystems for achieving sustainable development. In the current work, we explored the spatial influence of ECC on land urbanization and its driving mechanism, using the Wuhan agglomeration as a case study. In the first step, we calculated the ECC at the county level using the ecological footprint method. Then, we applied a combination of kernel density and the “densi-graph method” on the basis of points of interest, in order to identify urbanized areas and to measure land urbanization rates. Finally, we devised spatial models with ECC-based spatial weight matrices to examine the potential spatial interactions or constraints and the influencing factors. Results indicate the following. (1) Land urbanization rates in most counties increased, whereas the average ECC per capita in the Wuhan urban agglomeration decreased from 2010 to 2015; (2) China’s land urbanization is primarily driven by socio-economic development, in which fixed asset investments and urban income present positive influences and agricultural outputs show a negative influence; (3) Spatial interaction was formulated through ECC during the land urbanization process. However, this effect was attenuated in 2010–2015. The findings are beneficial for understanding the regional spatial influence of ECC on urban land urbanization. They should also facilitate the formulation of relevant policies for protecting, restoring, and promoting the sustainable use of terrestrial ecosystems to ultimately achieve coordinated and balanced regional development.
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