Rationale

With more than half the world population now living in urban area, cities around the world have seen an unprecedented need for delicacy management on each possible aspect of the urban life, including political processes, administrative governance, economic regulation, daily urban problem handling, environmental governance, and beyond. This would inevitably require understandings on the patterns, processes, and mechanisms of city dynamics, especially the “high-frequent” ones, i.e., the mobile elements of the city, such as people, information, economic transactions. They form flows and networks, and interact with the more inert, built elements of the city in complex ways. Their fine spatial, temporal, and semantic granularity demand for accurate observation and analysis of the city life, to which the emerging spatiotemporal intelligence method would significantly contribute. These include the exploration of spatiotemporal data of various sources, the development of spatiotemporal technologies and algorithms, and the application and implementation of the data and methods for the innovation and improvements in real-world urban management. Ultimately, we expect that new urban theories should emerge with the methodological and practical endeavors, such that the world be better prepared for the planetary urbanization future in the time of “high-frequent” urbanism.

The scope of Topics

We are excited to invite submissions to a special issue on Spatiotemporal Intelligence-Supported Delicacy Management of Cities. Per the statement in the above Rationale, The contributions may include but are not limited to the following topics:

Exploration and exploitation of spatiotemporal data sources that have potential utilization in delicacy urban management. The data can be “conventional” or new, “small” (for example, survey or questionnaire-based) or big, quantitative or qualitative. Specific topics may include:

Description of new data sources;

Data visualization design and methods;

Discussion on the quality and potential bias of existing or new data sources;

Data mining and feature engineering techniques.

Development of spatiotemporal intelligent methods that can be applied in delicacy urban management. These may include:

Pattern recognition;

Time-series analysis;

Spatial interaction analysis;

Spatiotemporal mechanistic analysis;

Operational research methods.

Thematic real-world application of relevant data and methods in delicacy urban management. Specific themes may cover any dimension of urban management, including:

Political/decision-making processes;

Administrative governance;

Environmental governance;

Economic regulation;

Daily urban problem handling;

Transportation management;

Land use management;

Urban problem situation-awareness and diagnostics;

Post-operational evaluations;

Digital management platform design.

Theoretical reflections on spatiotemporal intelligence and delicacy urban management.

Guidelines

Submissions should be prepared according to the “Submission Guidelines” available at the journal homepage https://us.sagepub.com/en-us/nam/transactions-in-urban-data-science-and-technology/journal203731#submission-guidelines 

Potential contributors are welcomed to contact guest editors with a provisional title (max. 30 words) and abstract (max. 200 words). Please visit the Journal’s submission site https://mc.manuscriptcentral.com/tus to upload your manuscript. Submitted papers should not have been previously published nor been currently under consideration for publication elsewhere. To ensure that all manuscripts are correctly identified for inclusion into the special issue, it is important to select “Spatiotemporal Intelligence-Supported Delicacy Management of Cities” when you reach the “Article Type” step in the submission process.

Timeline

Date 1 (OCT30 2022): Abstract submission

Date 2 (DEC31 2022): Full paper submission. 

Please note the papers can be submitted any time before the deadline.

Guest editors

Liyan Xu, xuliyan@pku.edu.cn. College of Architecture and Landscape Architecture, Peking University, Beijing, China.

Yao Shen, eshenyao@tongji.edu.cn. College of Architecture and Urban Planning, Tongji University, Shanghai, China.

link:https://us.sagepub.com/en-us/nam/transactions-in-urban-data-science-and-technology/journal203731