Title :
Identifying high amenity zones in the U.S. and China with advanced GIS techniques
Author :
Greene, Richard P. ; Wang, Siqin
Author_Institution :
Dept. of Geogr., Northern Illinois Univ., DeKalb, IL, USA
Abstract :
This paper applies a variety of GIS techniques to examine the spatial pattern and extent of high amenity zones (HAZ) in selected cities of the U.S. and Guangzhou, China. HAZs are adjacent to downtowns and represent high density upscale residential areas whose residents support neighborhood retailing and service employment that can often result in the misclassification of the areas as employment centers. To define the HAZ consistently across U.S. cities, we first develop a weighted median job density measure for the census tracts of each city and include census tracts that are in the upper quartile in job density and have an employment residence ratio below 1.25, the critical value used to define job centers. In the absence of employment data for China at a census tract scale, Starbucks coffee houses are mapped as they were found in an earlier study to be spatially coincident with high amenity zones in the U.S. Google Earth and GPS field work allowed us to locate each Starbucks for Guangzhou China. Preliminary findings from Guangzhou and the designation of its Tian He District as an HAZ allows for some cross cultural comparisons of the HAZ concept.
Keywords :
Global Positioning System; employment; geographic information systems; China; GPS; Google earth; Starbuck coffee house; U.S; advanced GIS technique; census tract; down town; employment residence ratio; high amenity zone identification; high density upscale residential area; neighborhood retailing; service employment; weighted median job density measure; Business; Cities and towns; Cultural differences; Employment; Global Positioning System; Urban areas; employment residence ratio; high amenity zone; weighted median job density;
Conference_Titel :
Geoinformatics, 2010 18th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-7301-4
DOI :
10.1109/GEOINFORMATICS.2010.5567587