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First, GIS data quality is a concern in all GIS-based research; for example, sidewalk attributes may be less accurate in suburban environments.
The first GIs landed on Britain's shores in 1942 and brought with them candy, Coca-Cola, cigarettes and nylon.
The first GIs identified were in fact called pathogenicity islands (PAIs) [2], [14].
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Second, GIS allows the development of spatial statistics that rely on geographically-referenced data.
The second GIS analysis for adapting the results to more realistic levels also supports the estimation of the potentials of renewable energy sources by focusing on certain areas that local stakeholders have already classified as suitable.
Actually, questions about stress and stressful behavior have been asked to participants of the third GIS that took place during the 2005 2006 influenza season [ 8].
The output is a second GIS data point related to the reference point by the angle and distance specified by the user.
Second, GIS databases were used to identify neighborhoods that maximized variation in walkability, and Belgian census data were used to identify neighborhoods of low and high-SES.
The fourth GIS-derived measure was the Neighbourhood Destinations Accessibility Index (NDAI) (Witten et al. 2011)—a measure of walking access to 31 types of community service and amenity destinations to which proximity could plausibly encourage residents to walk more for leisure or transport.
We first use GIS data to automatically precompute a set of cost-optimal BMP configurations for each subwatershed, over its entire range of possible treatment levels.
Second, a GIS-based prediction methodology for four-dimensional analysis is described.
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