The scale of urbanization is well-acknowledged and future projections outline severe sustainability concerns. Existing studies acknowledge that several environmental, hydroclimatic, socioeconomic, policy, and institutional factors control urban growth, yet key information about its detailed spatial and temporal dynamics is still missing. The ability to reproduce observed patterns of urban expansion is essential for projecting reliable scenarios for the near future. Here we develop a spatially explicit probabilistic modeling framework to describe observed urban expansion dynamics at a regional scale. As a proof of concept, we test our methodology in North-East China, as it experienced a rapid and sizable urbanization in the last 30 years. We infer the rate of urbanization from urban data and consider 128 different model combinations, aimed at exploring the role played by geomorphic and hydroclimatic drivers, together with the proximity to existing urban areas, in controlling spatial dynamics of urban expansion. Our results show that elevation, terrain slope, distance from rivers and from the sea are the most relevant factors in the considered study area. The fractal size distribution of urban clusters is satisfactorily reproduced by our model, which further confirms its validity. We discuss how our methodology could be a key contribution for analyzing and predicting the spatial dynamics of urban expansion in different regions of the globe. Valuable information on where human settlements will be located and how urban expansion will evolve can effectively support future planning strategies toward a more sustainable development.
Ceola, S., Grandi, G., Bertuzzo, E. (2025). Geomorphology and Hydroclimate Control Regional Urban Expansion. EARTH'S FUTURE, 13(4), 1-14 [10.1029/2024EF005652].
Geomorphology and Hydroclimate Control Regional Urban Expansion
Serena Ceola
Primo
;
2025
Abstract
The scale of urbanization is well-acknowledged and future projections outline severe sustainability concerns. Existing studies acknowledge that several environmental, hydroclimatic, socioeconomic, policy, and institutional factors control urban growth, yet key information about its detailed spatial and temporal dynamics is still missing. The ability to reproduce observed patterns of urban expansion is essential for projecting reliable scenarios for the near future. Here we develop a spatially explicit probabilistic modeling framework to describe observed urban expansion dynamics at a regional scale. As a proof of concept, we test our methodology in North-East China, as it experienced a rapid and sizable urbanization in the last 30 years. We infer the rate of urbanization from urban data and consider 128 different model combinations, aimed at exploring the role played by geomorphic and hydroclimatic drivers, together with the proximity to existing urban areas, in controlling spatial dynamics of urban expansion. Our results show that elevation, terrain slope, distance from rivers and from the sea are the most relevant factors in the considered study area. The fractal size distribution of urban clusters is satisfactorily reproduced by our model, which further confirms its validity. We discuss how our methodology could be a key contribution for analyzing and predicting the spatial dynamics of urban expansion in different regions of the globe. Valuable information on where human settlements will be located and how urban expansion will evolve can effectively support future planning strategies toward a more sustainable development.File | Dimensione | Formato | |
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