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The results indicate multiple significant disparities. The most striking difference is that mobility-based measurements of exposure to green space are significantly higher than those of residence-based measurements, manifesting the uncertain geographic context problem (UGCoP).

The uncertain geographic context problem or UGCoP is a source of statistical bias that can significantly impact the results of spatial analysis when dealing with aggregate data. [1] [2] [3] The UGCoP is very closely related to the Modifiable areal unit problem (MAUP), and like the MAUP, arises from how we divide the land into areal units.[4] [5] It is caused by the difficulty, or impossibility ...

The uncertain geographic context problem (UGCoP) was first articulated in Kwan (2012a,b). It refers to the problem that findings about the effects of area-based attributes (e.g., land-use mix) on individual behaviors or outcomes (e.g., physical activity) could be affected by how contextual units or neighborhoods are geographically delineated.

Third, we are not able to control residential selfselection bias and avoid the uncertain geographic context problem (UGCoP) in our analysis (Kwan, 2012; Yang et al., 2021), and the relationship ...

delineated and theextent towhich these areal unitsdeviate fromthetruegeographic context. The problem arisesbecause ofthespatial uncertaintyintheactual areas thatexertthecontextual influencesunder study and thetemporal uncertaintyinthetimingand duration inwhich individuals experienced these contextual influences.

This article explains the UGCoP, a methodological problem that affects the findings of studies using area-based contextual attributes. It discusses the sources, effects, and solutions of the UGCoP, and reviews recent studies that illustrate its sensitivity to contextual unit delineations.

Using neighborhood effects and environmental health research as a point of departure, this article clarifies the nature and sources of this problem, which is referred to as the uncertain geographic context problem (UGCoP). It highlights some of the inferential errors that the UGCoP might cause and discusses some means for mitigating the problem.

It is the problem that results about these effects can. Any study that examines the effects of area-based attributes on individual behaviors or outcomes faces another fundamental methodological problem besides the modifiable areal unit problem (MAUP). It is the problem that results about these effects can ... The Uncertain Geographic Context ...

Abstract. Leveraging human mobility data has advanced the understanding of the effect of contextual factors on health and behaviors by mitigating the uncertain geographic context problem (UGCoP)––a source of inferential errors that occur due to the misspecification of a geographic context in which individuals interact with environmental factors and other people.

The uncertain geographic context problem (UGCoP) is one of the most important methodological issues that contribute to the inconsistent findings. This dissertation explores the methodological issues in environmental health research causing the uncertain findings and how the UGCoP influences research findings, proposes an activity space ...

Abstract. The uncertain geographic context problem (UGCoP), first articulated by Kwan (Citation 2012; The uncertain geographic context problem.Annals of the Association of American Geographers, 102 (5), 958–968), refers to the problem that findings about the effects of area-based contextual variables on individual behaviors or outcomes may be affected by how contextual units (e.g ...

Using neighborhood effects and environmental health research as a point of departure, this article clarifies the nature and sources of this problem, which is referred to as the uncertain geographic context problem (UGCoP). It highlights some of the inferential errors that the UGCoP might cause and discusses some means for mitigating the problem.

Keywords: contextual uncertainty, environmental health, neighborhood effects, uncertain geographic context problem, UGCoP

geographic context. I provided the first explicit discussion about this prob-lem in Kwan (2012) and referred to it as the uncertain geographic context problem (UGCoP). In that paper, I argued that the UGCoP arises because of the spatial uncer-tainty in the actual areas that exert relevant contextual

The “mobility turn” in environmental health studies promoted the integrated 3S (GIS, GPS, and remote sensing) approach in the study of urban residents’ exposure to green space and corresponding health outcomes.However, few studies have examined the uncertainty induced by contextual settings when measuring people’s exposure to green space using the conventional and integrated 3S approaches.

This problem has been articulated as the uncertain geographic context problem (UGCoP). This study investigates the UGCoP through exploring the relationships between the built environment and obesity based on individuals' activity space. First, a survey was conducted to collect individuals' daily activity and weight information in Guangzhou in ...

The emerging technologies for collection and analysis of massive spatiotemporal databases have largely benefitted the innovation of urban studies, and enabled us to revisit the traditional constructs in terms of space-time behavior. On specific case is the uncertain geographic context problem (UGCoP) was proposed by Kwan (2012), which refers to the spatial uncertainty in the actual areas that ...

Using neighborhood effects and environmental health research as a point of departure, this article clarifies the nature and sources of this problem, which is referred to as the uncertain geographic context problem (UGCoP). It highlights some of the inferential errors that the UGCoP might cause and discusses some means for mitigating the problem.

This challenge has been recently articulated as the uncertain geographic context problem (UGCoP), which is the problem that analytical results can be different for different delineations of contextual units, even if other factors are the same, due to the spatial and temporal uncertainty of the true geographic context [27,28].