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Call for Paper on Big Spatial Data in Demography

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Researchers from diverse fields are invited to contribute using Big Spatial Data in Demography


The proliferation of digital technologies has resulted in an unprecedented availability of large-scale, georeferenced datasets encompassing various aspects of human behaviors, interactions, and societal dynamics. These big AND spatial data sources hold immense potential for addressing critical social, economic, and environmental challenges faced by contemporary societies. Spatial demography, an interdisciplinary field bridging demography and spatial analysis, provides a unique lens to analyze and understand the spatial patterns and processes underlying population dynamics.

We invite researchers from diverse disciplines, including but not limited to demography, sociology, geography, economics, computer science, and public health, to submit original research papers that use big AND spatial data to study any population processes (fertility, health and mortality, and migration), and population structure and characteristics (age, gender, urban-rural difference, family and household, and inequalities). The data should be both big and spatial, such as geotagged tweets, mobile phone data, credit card transactions, web scraping, and satellite images. Research topics include, but are not limited to:

• Geotagged social media data and its implications for understanding population dynamics and behaviors

• Mobility patterns and migration analysis using digital trace data

• Urban dynamics and rural development using digital data sources

• Spatial analysis of health-related big data for population health studies

• Geospatial analysis of big data for population studies

• Use of remote sensing and satellite imagery for demographic research

• Applications of machine learning and data mining techniques in demographic research

• Integration of digital big data with traditional survey and census data

• Visualization and interactive tools for analyzing and communicating spatial demographic patterns

Authors are encouraged to present original research that demonstrates novel methods, theoretical advancements, and practical applications related to the utilization of big data for spatial demography research. Both empirical studies and methodological contributions are welcome.

The topical collection will be coordinated by Guangqing Chi (Penn State, USA – e-mail: and Junjun Yin (Penn State, USA – email: with editorial support from Stephen A. Matthews (Penn State, USA – e-mail: Full submissions are preferred by February 29, 2024. We particularly welcome submissions from interdisciplinary submissions that infuse big data methods and approaches for spatial demographic research.

Submit your manuscript through the with a note on the cover letter stating that the submission is for consideration for the Topical Collection on Big Spatial Data in Demography. Please feel free to reach out to the editors about the suitability of a manuscript for this topical collection.

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Big Spatial Data in Demography | SpringerLink