Authors: Ryan Thomas*, Cornell University, Giuseppe Amatulli, Yale University School of Forestry & Environmental Studies; Center for Research Computing; Center for Science and Social Science Information, Ryan Powers, Yale University Department of Ecology and Evolutionary Biology
Topics: Urban Geography, Environmental Science, Geographic Information Science and Systems
Keywords: spatial modeling, urban-rural continuum, urban geography, unit of analysis
Session Type: Paper
Start / End Time: 9:55 AM / 11:35 AM
Room: Congressional B, Omni, West
Presentation File: No File Uploaded
Urban spatial studies are often based on units of analysis that are categorized according to an urban/non-urban binary or multiple land uses. Binary representations have drawn criticism from urban theorists and urban ecologists as exclusionary and simplistic, respectively. Even multiple land use classifications may represent breaks in urban areas that area functionally connected (satellite cities) or contained within urban areas (Central Park in Manhattan). While delimiting land areas into units is often essential for analysis, particularly for quantitative methods, there exist few data sources for analysts interested in empirically testing theories across the urban-rural continuum.
This paper describes a methodology for identifying units of analysis using a single variable of impervious surface that troubles classified and binary urban definitions. We present a data set that segments the land surface of the globe using a watershed algorithm applied to 1-km resolution impervious surface data. The algorithm produces two GIS layers representing units defined by similarity (“zones” of built-up intensity) and contiguity (city centers, analogous to “watersheds”), which can be used to identify units of analysis. We recommend three urban spatial units of analysis (1) zonal units; (2) city center units (analogous to watersheds); and (3) urban agglomerations resulting from the intersection of a given zonal unit with the city center units layer. Analysts interested in global urban areas or urban-rural linkages could use this data set to examine diverse phenomena across the rural-urban continuum. We illustrate usage through a novel methodology to calculate urban heat island.