Measuring urban sprawl using land use data

Digital land use data, generally derived by remote sensing operations, 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. A variant on Moran's I index does a better job at measuring scatteredness than entropy metrics. A problem that has not yet been discussed in the literature is that the grid structure of land use data can inflate the boundary of the measured area. This is particularly a problem when measuring urban compactness. 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 (EuropeanEnvironment: Agency, 2010).