Call for Papers Uncertainty and Context in Geography and GIScience

For updates and modifications for this call.

Uncertainty and Context in Geography and GIScience

AAG Annual Meeting, Boston, April 5-9, 2017

Uncertainty and context pose fundamental challenges in geographic research and GIScience. Geospatial data are imbued with error (e.g., measurement and sampling error), and understanding of the effects of contextual influences on human behavior and experience are often obfuscated by various types of uncertainty (e.g., contextual uncertainties, algorithmic uncertainties, and uncertainty arising from different spatial scales and zonal schemes). Identifying the “true causally relevant” spatial and temporal contexts that influence people’s behavior and experience is thus also challenging, since people move around in their daily lives and over their life courses and experience the influences of many different contexts. To generate reliable geographic knowledge, these uncertainties and contextual issues need to be addressed.

This theme within the 2017 AAG Annual Meeting will explore research frontiers and advances in theory, method, and research practice that address the challenges of uncertainty and context in geography and GIScience. We welcome papers from all disciplines, subfields and perspectives (e.g., geography, public health, sociology, transportation, urban studies, etc.). Topics may include but are not limited to:

– uncertainty and context: advances in theory and methods

– uncertainty and error assessment

– error propagation and modeling

– quality of geospatial data

– big data, algorithmic uncertainties, and algorithmic geographies

– the uncertain geographic context problem (UGCoP)

– the modifiable areal unit problem (MAUP)

– advances in the conceptualization and assessment of the neighborhood effect

– improving assessments of exposures to physical and social environments and health

– exposure monitoring utilizing real-time interactive GPS/GIS methods

– relational understanding of context and uncertainty

– human mobility and contextual uncertainties

– cumulative contextual influences over the life course

– social networks as individual and social context

– uncertainty in spatial pattern detection

– incorporating uncertainty in spatial modeling

To participate in this theme, please submit your abstract at When you receive confirmation of a successful abstract submission, please then forward this confirmation to: GeoContext [at] aag [dot] org. The abstract deadline is October 27, 2016.

For more information, please visit, or contact members of the theme’s organizing committee at GeoContext [at] aag [dot] org.

Scientific Committee


Mei-Po Kwan (University of Illinois at Urbana-Champaign), Daniel Griffith (University of Texas at Dallas), Michael Goodchild (University of California, Santa Barbara), Tim Schwanen (University of Oxford)

Committee members:

Ling Bian (University of Buffalo)

Xiang Chen (Arkansas Tech University)

Yongwan Chun (University of Texas at Dallas)

Eric Delmelle (University of North Carolina at Charlotte)

Michael Emch (University of North Carolina at Chapel Hill)

Nina Lam (University of Louisiana)

Jing Ma (Beijing Normal University)

Jeremy Mennis (Temple University)

Douglas Richardson (American Association of Geographers)

John Shi (Hong Kong Polytechnic University)

Xun Shi (Dartmouth University)

Kathleen Stewart (University of Maryland)

Yonette Thomas (American Association of Geographers)

Paul Torrens (New York University)

Shaowen Wang (University of Illinois at Urbana-Champaign)

Michael Widener (University of Cincinnati)

David Wong (George Mason University)

Chaowei Yang (George Mason University)

Eun-Hye Enki Yoo (University at Buffalo, State University of New York)

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