Integrated Spatial Simulation of Population and Urban Land Use: a Pan-European Model Validation

Spatial models jointly simulating population and land-use change provide support for policy-making, by allowing to explore territorial developments under alternative scenarios and resulting impacts in the environment, economy and society. However, their ability to reproduce observed spatial patterns is rarely evaluated through model validation. This lack of insight prevents researchers and policy-makers of fully grasping the ability of existing models to provide sensible projections of future land use and population density. In this article, we address this gap by performing a model validation of the LUISA Territorial Modelling Platform, a spatial model jointly simulating population and land use at a fine resolution (100 m) in the European Union and United Kingdom. In particular, we compare observed and simulated patterns of population and urban residential land-use change for the period of 1990-2015, and evaluate the model performance according to different degrees of urbanisation. The results show that model performance can vary depending on the context, even when the same data and methods are uniformly applied. The model performed consistently well in urban areas characterized by compact urban growth, but poorly where residential development occurred predominantly in scattered patterns across rural areas. Overall, the model tends to favour the formation of densely populated, highly accessible urban conglomerations, which often do not entirely correspond to the observed patterns. Based on the validation results, we propose directions for further model improvement and development. Model validation should be regarded as a critical step, and an integral part, in the process of developing models for policy support.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12061-023-09518-x.

Modelling agricultural land abandonment in a fine spatial resolution multi-level land-use model: An application for the EU

In the majority of EU Member States, agricultural land is expected to decrease not only due to land-use changes in favour of urban expansion and afforestation but also to land abandonment processes. The knowledge on location and extent of agricultural land abandonment is relevant for estimating local external effects and adapting policy interventions. Currently, multi-level land-use models are able to capture determined processes of demand-driven redevelopment. However, land abandonment is much more difficult to capture because of its more ambiguous definition and the lack of data on its spatial distribution. This paper presents a method to explicitly model agricultural abandonment as a choice of disinvestment, which in turn is embedded in a utility-based land-use modelling framework that projects land-use changes for the EU and the UK. Validation exercises using observed spatial distribution of abandoned farmland show that the proposed method allows to model abandonment with acceptable accuracy.

Population growth, accessibility spillovers and persistent borders: Historical growth in West-European municipalities

Lack of cross-border transport supply has repeatedly been blamed for the fact that national borders limit spatial interaction and, consequently, the growth of border regions. This study applies an accessibility approach to investigate for most municipalities in ten countries in mainland West Europe if foreign transport supply is lagging behind, and if population growth in these municipalities has been affected by the limits that national borders have imposed on market access. To do so, data describing historical population changes and road networks between 1961 and 2011 have been used. The results show that in the study area, cross-border transport accessibility was not at a disadvantage in 1961 and has since then grown even more than domestic accessibility. However, municipal population growth has depended almost exclusively on domestic market access. Processes of economic international integration in the study area are found to coincide with the growth of cross-border accessibility, but do not have a clear coincidence with the effects of cross-border accessibility on population growth.

Reducing the uncertainty induced by spatial aggregation in accessibility and spatial interaction applications

Analyses of spatial interaction are to some degree plagued by uncertainty regarding the impact of spatially dispersed interaction masses within zones on travel times. In this paper, interaction-weighted travel times are computed from a matrix between regularly distributed points at fine resolution, and used together with secondary data to improve estimates of interaction weighted travel time based on commonly applied methods. The paper proposes a method for computing intra-zonal, interaction weighted travel times that is considerably less sensitive to spatial aggregation than existing approaches, and demonstrates that population-weighted centroids are to be preferred over geographically-weighted centroids.

Assessing uncertainties in land cover projections

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.

More green infrastructure is required to maintain ecosystem services under current trends in land-use change in Europe

Green infrastructure (GI), a network of nature, semi-natural areas and green space, delivers essential ecosystem services which underpin human well-being and quality of life. Maintaining ecosystem services through the development of GI is therefore increasingly recognized by policies as a strategy to cope with potentially changing conditions in the future. This paper assessed how current trends of land-use change have an impact on the aggregated provision of eight ecosystem services at the regional scale of the European Union, measured by the Total Ecosystem Services Index (TESI8). Moreover, the paper reports how further implementation of GI across Europe can help maintain ecosystem services at baseline levels. Current demographic, economic and agricultural trends, which affect land use, were derived from the so called Reference Scenario. This scenario is established by the European Commission to assess the impact of energy and climate policy up to 2050. Under the Reference Scenario, economic growth, coupled with the total population, stimulates increasing urban and industrial expansion. TESI8 is expected to decrease across Europe between 0 and 5 % by 2020 and between 10 and 15 % by 2050 relative to the base year 2010. Based on regression analysis, we estimated that every additional percent increase of the proportion of artificial land needs to be compensated with an increase of 2.2 % of land that qualifies as green infrastructure in order to maintain ecosystem services at 2010 levels.