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Uncertainty and Context in Geography and GIScience: Reflections on Spatial Autocorrelation, Spatial Sampling, and Health Data

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  • Daniel A. Griffith

Abstract

One of the conference themes for the 2017 American Association of Geographers (AAG) annual meeting was “Uncertainty and Context in Geography and GIScience.” It included a triplet of special sessions cosponsored by the Spatial Analysis and Modeling (SAM) and the Health & Medical Geography (HMG) specialty groups. One session dealt with spatial autocorrelation, another featured spatial sampling, and a third focused on public health data. A conceptual framework and overviews of these three sessions emphasize research frontiers and advances in theory, method, and research practice that address challenges of uncertainty and context in geography and GIScience. This article summarizes these three sessions.

Suggested Citation

  • Daniel A. Griffith, 2018. "Uncertainty and Context in Geography and GIScience: Reflections on Spatial Autocorrelation, Spatial Sampling, and Health Data," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 108(6), pages 1499-1505, November.
    • Handle: RePEc:taf:raagxx:v:108:y:2018:i:6:p:1499-1505
    DOI: 10.1080/24694452.2017.1416282
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    Cited by:

    1. Ellen J. Kinnee & Sheila Tripathy & Leah Schinasi & Jessie L. C. Shmool & Perry E. Sheffield & Fernando Holguin & Jane E. Clougherty, 2020. "Geocoding Error, Spatial Uncertainty, and Implications for Exposure Assessment and Environmental Epidemiology," IJERPH, MDPI, vol. 17(16), pages 1-23, August.

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