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

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 Geograp...

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Bibliographic Details
Published inAnnals of the American Association of Geographers Vol. 108; no. 6; pp. 1499 - 1505
Main Author Griffith, Daniel A.
Format Journal Article
LanguageEnglish
Published Washington Routledge 02.11.2018
Taylor & Francis Ltd
Subjects
Autocorrelation
Data processing
error
error, datos de salud, autocorrelación espacial, muestreo espacial, incertidumbre
Frameworks
Geographers
Geography
health data
Health information
Medical geography
Modelling
Public health
Sampling
Spatial analysis
spatial autocorrelation
Spatial data
Spatial distribution
spatial sampling
Uncertainty
误差, 健康数据, 空间自相关, 空间抽样, 不确定性
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Summary: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.
ISSN:2469-4452
2469-4460
DOI:10.1080/24694452.2017.1416282