Development of a 'Water-Relevant Typology' of Urban Neighborhoods
|Authors:||Douglas Jackson-Smith · Martin Buchert · Philip Stoker|
|Owners:||iUTAH Data Manager · Douglas Jackson-Smith|
|Created:||July 18, 2016, 9:35 p.m.|
|Last updated:||Nov. 17, 2016, 3:52 p.m. by Douglas Jackson-Smith|
This dataset and technical report summarizes the methodology and results of a project to develop a water-relevant typology of urban neighborhoods for the greater Wasatch Range Metropolitan Area in northern Utah.
The technical report provides details about the original sources of data and analytic methodology deployed to create the typology. The work is also summarized in a peer-reviewed open-access article published in Cities and the Environment (Available at: http://digitalcommons.lmu.edu/cate/vol9/iss1/5 and copied below).
For users who wish to see copies of the underlying datasets (all aggregated at the census block group scale) for the study area, we have included a text file codebook and files in various formats (.csv, .xlsx, and .sav) for public use.
The effort was supported by the NSF-funded iUTAH project, and has been used to guide the design and implementation of an urban water observatory that captures social, built, and natural system characteristics.
Urban typology,neighborhood,urban water systems,urbanization,WRMA,iUTAH
How to cite
This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/
|Coordinate System/Geographic Projection:||WGS 84 EPSG:4326|
|Coordinate Units:||Decimal degrees|
|Douglas Jackson-Smith||The Ohio State University||Ohio, US||330-202-3540|
|Martin Buchert||University of Utah|
|Philip Stoker||University of Utah|
|Observed Variables||Neighborhood Type (group), Neighborhood Type (specific), factor scores used to construct typology, component variables used in factor analysis|
|Variable Description||Neighborhood Types|
|Data Processing Method||Data from various sources were aggregated at the census block group (CBG) level to create indicators of 49 characteristics of each CBG. Variables were collapsed into 8 distinct dimensions using factor analysis. The factors were used in a cluster analysis to identify groups of CBGs that shared similar characteristics along the 8 dimensions.|
|Data Collection Method||Analysis of secondary data from various sources (U.S. Census of Population, American Community Survey, Utah Water Related Land Use Dataset, MODIS and LandSat imagery, etc.).|
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|National Science Foundation||iUTAH-innovative Urban Transitions and Aridregion Hydro-sustainability||1208732|
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