alexa Quantitating Non-Zero Autocorrelation to Determine Moran's I Coefficients for Mapping Clustering Tendencies of Fast Food Restaurants in Lower SES Neighborhoods in Hillsborough County, Florida
ISSN: 2469-4134

Journal of Remote Sensing & GIS
Open Access

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Research Article

Quantitating Non-Zero Autocorrelation to Determine Moran's I Coefficients for Mapping Clustering Tendencies of Fast Food Restaurants in Lower SES Neighborhoods in Hillsborough County, Florida

Nathanael Stanley, Samuel Alao and Benjamin Jacob*

Department of Global Health, College of Public Health, University of South Florida, Tampa, FL, USA

*Corresponding Author:
Benjamin Jacob
Department of Global Health, College of Public Health
University of South Florida, Tampa, FL, USA
Tel: 8139749784
E-mail: [email protected]

Received Date: November 04, 2016; Accepted Date: November 17, 2016; Published Date: November 21, 2016

Citation: Stanley N, Alao S, Jacob B (2016) Quantitating Non-Zero Autocorrelation to Determine Moran's I Coefficients for Mapping Clustering Tendencies of Fast Food Restaurants in Lower SES Neighborhoods in Hillsborough County, Florida. J Remote Sensing & GIS 5:179. doi: 10.4179/2469-4134.1000179

Copyright: © 2016 Stanley N, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

This research utilizes a similar method, using what may prove to be more precise spatial statistics to determine clustering tendencies and economic data to assess their location in relation to low income areas. It is also important to note that race/ethnicity is not included in this research; rather it focuses on designation of population density and persons living at or below poverty level. This research provides a way to spatially determine if fast food restaurants are more prominent in low socioeconomic areas.

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