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Measuring Urban Sprawl using Land Use Data

Miriam Steurer () and Caroline Bayr ()
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Miriam Steurer: University of Graz, Austria
Caroline Bayr: Joanneum Research, Policies, Graz, Austria

No 2020-02, Graz Economics Papers from University of Graz, Department of Economics

Abstract: Digital land use data, generally derived by remote sensing and often organized in grid form, have become widely available for even the most remote areas of the globe. Here we investigate how to use land use data to measure three of the most characteristic aspects of urban sprawl: low density, low continuity of land use type (scatteredness), and low compactness of the shape of the city. For each of these categories we present multiple urban sprawl indicators. Some of these indicators have been used in the literature before, others we developed ourselves. For density measurements we illustrate how simple changes to common density indicators can improve their meaningfulness. With respect to scatteredness we show that the interpretation of entropy measures can be ambiguous. Using a variant on Moran’s I index does a better job at measuring scatteredness. When it comes to measuring compactness, the grid structure of land use data can inflate the boundary of the measured area. We introduce new compactness indices that correct for this problem. To illustrate the discussed indices, we apply them to Graz, the second largest city in Austria, using data from the CORINE Land Cover (CLC) Project [1].

Keywords: urban sprawl; density; entropy, GIS; remote sensing; urban dynamics; spatial analysis; compactness (search for similar items in EconPapers)
JEL-codes: R11 R52 (search for similar items in EconPapers)
Date: 2020-02
New Economics Papers: this item is included in nep-geo and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

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