Radial analysis and scaling of urban land use.

We determine the functional form and scaling law of radial artificial land use profiles in 300 European functional urban areas (FUAs). These profiles, starting from a fully artificial surface in the city center, decrease exponentially, the faster the smaller the city. More precisely, the characteristic decrease distance scales like the square root of total population, meaning that the artificial surface of cities is proportional to their population. This also means that the amount of artificial land per capita is independent of city size, and that larger cities are not more or less parsimonious in terms of land use than smaller ones.

The provision of urban green space and its accessibility: Spatial data effects in Brussels.

Urban green space (UGS) has many environmental and social benefits. UGS provision and access are increasingly considered in urban policies and must rely on data and indicators that can capture variations in the distribution of UGS within cities. There is no consensus about how UGS, and their provision and access, must be defined from different land use data types. Here we identify four spatial dimensions of UGS and critically examine how different data sources affect these dimensions and our understanding of their variation within a city region (Brussels). We compare UGS indicators measured from an imagery source (NDVI from Landsat), an official cadastre-based map, and the voluntary geographical information provided by OpenStreetMap (OSM). We compare aggregate values of provision and access to UGS as well as their spatial distribution along a centrality gradient and at neighbourhood scale. We find that there are strong differences in the value of indicators when using the different datasets, especially due to their ability to capture private and public green space. However we find that the interpretation of intra-urban spatial variations is not affected by changes in data source. Centrality in particular is a strong determinant of the relative values of UGS availability, fragmentation and accessibility, irrespective of datasets.

Housing land transaction data and structural econometric estimation of preference parameters for urban economic simulation models.

This paper describes a dataset of 6284 land transactions prices and plot surfaces in 3 medium-sized cities in France (Besançon, Dijon and Brest). The dataset includes road accessibility as obtained from a minimization algorithm, and the amount of green space available to households in the neighborhood of the transactions, as evaluated from a land cover dataset. Further to the data presentation, the paper describes how these variables can be used to estimate the non-observable parameters of a residential choice function explicitly derived from a microeconomic model. The estimates are used by Caruso et al. (2015) to run a calibrated microeconomic urban growth simulation model where households are assumed to trade-off accessibility and local green space amenities.