Dr Yeran Sun Sun

Research Highlights

1. Sun, Y., Wang, S., & Sun, X. (2020). Estimating neighbourhood-level prevalence of adult obesity by socio-economic, behavioural and built environment factors in New York City. Public Health, 186, 57-62.

   https://doi.org/10.1016/j.puhe.2020.05.003, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56128
2. Sun, Y., Hu, X., & Xie, J. (2021). Spatial inequalities of COVID-19 mortality rate in relation to socioeconomic and environmental factors across England. Science of The Total Environment, 758(143595), 143595

   https://doi.org/10.1016/j.scitotenv.2020.143595, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56127
3. Sun, Y. & Paule, J. (2017). Spatial analysis of users-generated ratings of yelp venues. Open Geospatial Data, Software and Standards, 2(1)

   https://doi.org/10.1186/s40965-017-0020-9, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53532
4. Sun, Y., Du, Y., Wang, Y., & Zhuang, L. (2017). Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data. International Journal of Environmental Research and Public Health, 14(6), 644

   https://doi.org/10.3390/ijerph14060644, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53533
5. Sun, Y. & Mobasheri, A. (2017). Utilizing Crowdsourced Data for Studies of Cycling and Air Pollution Exposure: A Case Study Using Strava Data. International Journal of Environmental Research and Public Health, 14(3), 274

   https://doi.org/10.3390/ijerph14030274, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53534
6. Sun, Y., Fan, H., Li, M., & Zipf, A. (2016). Identifying the city center using human travel flows generated from location-based social networking data. Environment and Planning B: Planning and Design, 43(3), 480-498.

   https://doi.org/10.1177/0265813515617642, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53535
7. Sun, Y., Moshfeghi, Y., & Liu, Z. (2017). Exploiting crowdsourced geographic information and GIS for assessment of air pollution exposure during active travel. Journal of Transport & Health, 6, 93-104.

   https://doi.org/10.1016/j.jth.2017.06.004, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53536
8. Sun, Y., Fan, H., Bakillah, M., & Zipf, A. (2015). Road-based travel recommendation using geo-tagged images. Computers, Environment and Urban Systems, 53, 110-122.

   https://doi.org/10.1016/j.compenvurbsys.2013.07.006, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53537
9. Anejionu, O., Sun, Y., Thakuriah, P., McHugh, A., & Mason, P. (2019). Great Britain transport, housing, and employment access datasets for small-area urban area analytics. Data in Brief, 27, 104616

   https://doi.org/10.1016/j.dib.2019.104616, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53538
10. Wang, S., Sun, Y., Sun, Y., Guan, Y., Feng, Z., Lu, H., Cai, W., & Long, L. (2019). A Hybrid Framework for High-Performance Modeling of Three-Dimensional Pipe Networks. ISPRS International Journal of Geo-Information, 8(10), 441

    https://doi.org/10.3390/ijgi8100441, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53539
11. Anejionu, O., Thakuriah, P., McHugh, A., Sun, Y., McArthur, D., Mason, P., & Walpole, R. (2019). Spatial urban data system: A cloud-enabled big data infrastructure for social and economic urban analytics. Future Generation Computer Systems, 98, 456-473.

    https://doi.org/10.1016/j.future.2019.03.052, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53540
12. Paule, J., Sun, Y., & Moshfeghi, Y. (2019). On fine-grained geolocalisation of tweets and real-time traffic incident detection. Information Processing & Management, 56(3), 1119-1132.

    https://doi.org/10.1016/j.ipm.2018.03.011, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53541

    https://strathprints.strath.ac.uk/63881/
13. Sun, Y., Mburu, L., & Wang, S. (2016). Analysis of community properties and node properties to understand the structure of the bus transport network. Physica A: Statistical Mechanics and its Applications, 450, 523-530.

    https://doi.org/10.1016/j.physa.2015.12.150, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53542
14. Wu, W., Dong, G., Sun, Y., & Yun, Y. (2020). Contextualized effects of Park access and usage on residential satisfaction: A spatial approach. Land Use Policy, 94, 104532

    https://doi.org/10.1016/j.landusepol.2020.104532, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53734
15. Sun, Y., Wang, S., & Wang, Y. (2020). Estimating local-scale urban heat island intensity using nighttime light satellite imageries. Sustainable Cities and Society, 57, 102125

    https://doi.org/10.1016/j.scs.2020.102125, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53825
16. Sun, Y., Ren, Y., & Sun, X. (2020). Uber Movement Data: A Proxy for Average One-way Commuting Times by Car. ISPRS International Journal of Geo-Information, 9(3), 184

    https://doi.org/10.3390/ijgi9030184, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa53945
17. Sun, Y., Wang, S., Zhang, X., Chan, T., & Wu, W. (2021). Estimating local-scale domestic electricity energy consumption using demographic, nighttime light imagery and Twitter data. Energy, 226, 120351

    https://doi.org/10.1016/j.energy.2021.120351, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57075
18. Sun, Y., Huang, Y., Yuan, K., Chan, T., & Wang, Y. (2021). Spatial Patterns of COVID-19 Incidence in Relation to Crime Rate Across London. ISPRS International Journal of Geo-Information, 10(2), 53

    https://doi.org/10.3390/ijgi10020053, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57090

All Research

• Untitled (current)

  MSc

  Other supervisor: Dr Iain Robertson

• GEG130 Globalisation

  This module explores the fundamental geographical concept of globalisation, introduces students to theories seeking to explain the processes of globalisation, and examines the implications of globalisation for the geography of the global economy, health, and human and non-human mobility and migration.

• GEG140 Project and Methods

  This module involves training in fieldwork and GIS skills for both human and physical geographers. In part 1, students can choose from a physical or human geography project option: Part 1: Physical Geography The project, entitled ¿Reconstructing Quaternary environmental change on the south coast of the Gower peninsula¿, focuses on some of the field techniques and approaches (mainly sedimentological) that are used to reconstruct environmental change with particular reference to the alternation of glacial and interglacial episodes. The aims are to examine the evidence remaining in the landscape, to describe and analyse the evidence systematically, to interpret the evidence in terms of environmental change, and to reconstruct the sequence of events that have affected this part of Gower. The Gower peninsula is particularly significant in reconstructing Quaternary environmental changes because it lies close to the limit of the last (Devensian) ice sheet. Part 1: Human Geography The human geography project focusses on Cities and Photography. Students will investigate the use of photography through three Visual Methodologies: Photo-Documentation, Photo-Elicitation, and Photo-Essays. Students will take part in a photo documentation workshop and group photography fieldwork in Swansea City Centre. They will also complete a photo essay aided by group discussion to select concept, theme, whether analytical or evocative photographs (or both), and dicussion of the links between practice and visual methodologies literature. Part 2: GIS Project. This element of the module will introduce students to key skills in Mapping, Spatial Data and GIS. They will explore how maps and spatial analysis can help us to understand and monitor our world. Students will consider the use of maps to analyse the environment and share the results in the media. They will Explore GIS software (arc Map, QGIS) and take their ffirst steps in displaying spatial data. Students will also learn how to refer to the spatial location of environmental features on the earth¿s surface, understand how references systems translate geographical locations on a flat map and learn how to work with data from a range of spatial reference systems.

• GEG331 Dissertation Report: Geography

  The dissertation is an original, substantive and independent research project in an aspect of Geography. It is typically based on approximately 20 - 25 days of primary research and several weeks of analysis and write-up. The end result must be less than 7,500 words of text. The dissertation offers you the chance to follow your personal interests and to demonstrate your capabilities as a Geographer. During the course of your dissertation you will be supported by a student-led discussion group and a staff supervisor, and you will also provide constructive criticism to fellow students undertaking related research projects, learning from their research problems and subsequent solutions. This support and supervision is delivered through the 'Dissertation Support' module, which is a co-requisite.

• GEGM22 Geographical Information Systems

  This module will provide students from a range of disciplines including Geography, Bioscience and Health Science with a comprehensive understanding of Geographic Information Systems, and key practical skills in the market-leading open-source GIS software tool Quantum GIS (QGIS). At the end of the module students will know how and where to acquire geospatial data, how to combine and analyse these data for specific objectives, and how to visualise primary and derived data in the form of maps.

Guest Editor of ISPRS International Journal of Geo-Information
Special Issue "Geovisualization and Social Media" (https://www.mdpi.com/journal/ijgi/special_issues/gsm)

Invited presentation at Royal Statistical Society (RSS) 2017 Annual Conference in the session "Data Science of urban movement" (https://www.youtube.com/watch?v=W1RMWZU9J2Y)

• 4th Sustainable Urban Policy Futures

  July 2017

  Old Royal Naval College, Greenwich Campus, University of Greenwich