Developing accurate land cover projection to accelerate the realization of SDG 11 in urbanized cities: a comparative study

Author's Department

Architecture Department

Third Author's Department

Architecture Department

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https://doi.org/10.1007/s10098-025-03297-4

All Authors

Ahmed Marey Liangzhu Leon Wang Sherif Goubran

Document Type

Research Article

Publication Title

Clean Technologies and Environmental Policy

Publication Date

1-1-2025

doi

10.1007/s10098-025-03297-4

Abstract

Sustainable Development Goal (SDG) 11 aims to achieve inclusive, safe, resilient, and sustainable cities. Planners and policymakers can better understand the implications of rapid urbanization by evaluating the dynamic interactions between different land use types. The Patch-generating Land Use Simulation and Markov chain models are combined to study the compliance of land cover trajectory with SDG 11, specifically in terms of promoting sustainable urbanization, enhancing green spaces, and improving urban resilience. Additionally, the model is applied to three major cities in Canada to validate its applicability and to understand future territorial spatial patterns and their implications on the 2030 vision for sustainable cities. Findings reveal that a total decrease of 40.50 km2 in urban and built-up areas is expected by 2030, highlighting potential challenges for achieving SDG 11 targets related to sustainable urban expansion and land use efficiency. The simulation results showed a figure of merit ranging from 0.371 to 0.410, comparing simulation results to real-life historical data. The built-up area of Ottawa grew around the city outskirts and downtown, with small areas forming next to roads and highways. On the other hand, because they are largely covered in built-up regions, Toronto and Montreal have witnessed a uniform battle between urban areas and vegetation along the entire territory. Additionally, the influence of various driving factors on land use and land cover change was evaluated. The outcomes of this study can serve as a guide for future regional territorial spatial planning and policy formation.

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