Work

Co-designing geoprospective private and public urban greening scenarios: A data-driven workflow for planning decisions and research

Year: 2025

Type: article

Abstract: In the context of climate change, adapting cities to extreme heat is a key challenge for urban planning research. Evaluating how urban greening affects urban climate at the metropolitan scale is crucial for promoting sustainable land-use planning research and practice. Here, we present a co-designed, GIS-automated workflow grounded in geoprospective to quantify where and how much greening can be added, while preserving essential urban functions rather than simply replacing impervious surfaces with greenery. Applied to Dijon (France), the Green Scenario, anchored in local urban planning rules adds 46,000 new trees and over 9 km² of low vegetation within the city (130,000 trees and 20 km² metropolitan-wide), covering nearly one-quarter of Dijon with new greenery. To benchmark the added value of co-design, a normative baseline that applies uniform greening targets regardless of planning constraints was also generated. Compared with the baseline, the Green Scenario shifts vegetation towards the most feasible locations: industrial and commercial zones on the periphery receive about two-thirds of the added low vegetation, whereas the historic core shows limited potential beyond streets and squares. These findings identify priority areas for mitigating heat stress, guide private and public greening policies, and provide actionable datasets for integrating nature-based solutions into urban planning and climate adaptation strategies. The transferable methodology, available through open-access computational tools, also provides layers suitable for use in climate models to estimate cooling benefits.

Source: Urban forestry & urban greening

DOI: 10.1016/j.ufug.2025.129021