Do land policies make a difference? A data-driven approach to trace effects on urban form in France and Germany

Abstract

Against the backdrop of rapidly expanding urban structures, land policies in many countries have been adapted to contain and redirect growth to existing urban structures. However, obstacles remain to measure the effects of policies. In the meantime, geoinformation technologies have given rise to a wide range of approaches to measure and describe urban form. Nevertheless, its application for the assessment of land policy has a high, but not yet fully exploited, potential. It is thus the aim of this research to address and investigate the options of spatial analysis and machine learning in particular to analyse urban form from a land policy perspective. To do so, we develop urban metrics informed by urban planning and land readjustment policies of two countries describing urban form on different spatial levels. We therefore formulate hypotheses on causal relations between policy and form. Based on the metrics, we apply the random forest algorithm to classify the building stock of the region. We then extract the residential areas, those with single-family houses, as this is where the effects of the policy are considered most visible. In a next step, we use random forest to predict the nationality of a building. Through variable importance measures, we identify and discuss urban morphological differences between the two countries and test the hypotheses on effects of land policies. We develop and test the approach for the French-German city-region of Strasbourg using OpenStreetMap data. We identify significant differences in the building coverage ratios, which tend to be higher in Germany. This can be linked to differences in planning regulations. Furthermore, German residential areas appear to be more diverse in urban form. Differences in land readjustment policies have proven to be plausible here, as French policies favour strong actors that develop residential areas more uniformly. In Germany, policies favour fragmented ownership-oriented development of residential areas. The metrics and the applied algorithm for building classification have proven to be robust in terms of data heterogeneity and have shown high levels of accuracy. They could also be successfully used for tracing causal relations.

Comparing types and patterns: A context-oriented approach to densification in Switzerland and the Netherlands

“…The age distribution is measured per hectare and is expressed as shares of children, students and elderly (Jehling et al, 2018). Population density is also measured per hectare (following Jehling and Hecht, 2021). Furthermore, to measure possible effects of crowding (Burton, 2000), we include apartment sizes (relating to individual addresses) and living space per person, expressed as the sum of apartment sizes divided by the number of inhabitants per hectare.…”

“…Another concern regards the comparability of urban development in two regions with substantially different degrees of urbanisation, age distributions, building traditions and landscapes. As a possible solution to this issue, we proposed metrics that characterise densification types in relation to their direct surroundings (Jehling and Hecht, 2021). We expressed densification as deviations from average values in a circle of 1 km 2 around each new housing unit.…”

Making land available. Cultural legal comparison of the German Building Land Mobilisation Act and the partial revision of the Swiss Spatial Planning Act

“…On the other hand, controlling the ongoing sealing of green spaces is a traditional and more pressing planning challenge to combat climate change. Regardless of the exact definition and concrete measurement of this new land take ( Vrebos et al 2017) and also some Member States have added (more or less) concrete legal objectives to their policy goals in this regard (Schatz/Bovet/Lieder et al 2021), such as Belgium (Halleux/Marcinczak/van der Krabben 2012; Buitelaar/Leinfelder 2020), France (Jehling/Hecht 2022), Austria (Meinel/Schumacher/Behnisch et al 2019;Kanonier 2020), Poland (Stacherzak/Hełdak/Hájek et al 2019) and the Czech Republic (Vejchodská/Pelucha 2019).…”

Land policy conflict profiles for different densification types: A literature-based approach

“…Many municipalities in Europe and beyond are promoting densification through land policies in the name of sustainable development (e. g., OECD, 2012). Containing and redirecting growth to existing urban and suburban structures contributes to climate policy goals and supranational objectives of land cover change, such as the European Union's target of zero net land take (e.g., European Commission, 2016; Jehling and Hecht, 2021). As well as offering environmental advantages, densification brings a wide range of economic and social benefits at the municipal level, such as reduced infrastructure and service costs, better opportunities to maintain and facilitate public transportation, and prospects for revitalizing older neighborhoods and city centers (e.g., Bibri et al, 2020;Berghauser Pont et al, 2021).…”