Land take futures under divergent urban growth scenarios: Cellular automata-based stress-testing for No Net Land Take targets

Anasua Chakraborty , Ahmed Mustafa, Lien Poelmans, Jacques Teller

Land take, the conversion of greenfield land into built-up areas, poses critical planning challenges for sustainable urban development, particularly as the EU Soil Strategy 2030 sets No Net Land Take (NNLT) by 2050 as a long-term objective for member states across Europe. Addressing this issue requires understanding the balance between outward urban expansion and inward urban densification. This study employs a Multinomial Logistic Regression-based Cellular Automata (MNL-CA) model to simulate two future scenarios of urban development until 2050 in Wallonia, Belgium, a region where, despite planning interventions promoting densification, land take rates remain persistently high, challenging conventional Business-As-Usual (BAU) projections. The model simulates two contrasting built-up demand scenarios. BAU follows a linear extrapolation of historical trends, representing a gradual slowdown of urban expansion and shift to densification. The second, Growth-As-Usual (GAU), applies a stress-test where urban expansion continues steadily through 2050. Under BAU, expansion rates decrease, stabilising at approximately 0 hectares per day by 2040, with total built-up area growing by 8,861 hectares (2.87%) by 2050, reflecting a progressive shift toward compact forms. By contrast, GAU produces ongoing expansion at 2.51 hectares per day in 2050, adding 27,347 hectares (8.87%) of built-up area, highlighting the risks of uncontrolled land consumption. Spatial metrics demonstrate that BAU fosters compact and contiguous development, whereas GAU results in fragmented urban forms that challenge the resilience of spatial planning policies. By evaluating both scenarios, our model provides a framework for stress-testing development strategies, enabling more robust assessments for regional NNLT commitments and sustainable land-use policy.