Abstract
As urban population is forecast to exceed 60% of the world’s population by 2050, urban growth can be expected. However, research on spatial projections of urban growth at a global scale are limited. We constructed a framework to project global urban growth based on the SLEUTH urban growth model and a database with a resolution of 30 arc-seconds containing urban growth probabilities from 2020 to 2050. Using the historical distribution of the global population from LandScanTM as a proxy for urban land cover, the SLEUTH model was calibrated for the period from 2000 to 2013. This model simulates urban growth using two layers of 50 arc-minutes grids encompassing global urban regions. While varying growth rates are observed in each urban area, the global urban cover is forecast to reach 1.7 × 106 km2 by 2050, which is approximately 1.4 times that of the year 2012. A global urban growth database is essential for future environmental planning and assessments, as well as numerical investigations of future urban climates.
Highlights
Background & SummaryGlobal urbanisation has significantly increased over the past few centuries
We found that three out of the five parameters were calibrated to the minimum value when the Urban Growth Index (UGI) fell below 1.5%
For modelling windows with UGIs between 0.25% and 1.5%, we applied a simplified SLEUTH model calibration mode by setting the values of the three aforementioned parameters to 1. We considered this simplification to be reasonable based on the pre-analysis, which we carried out for large urban agglomerations
Summary
Global urbanisation has significantly increased over the past few centuries. The United Nations (UN) has projected the global urban population to rise to 68% of the world’s population by 2050, up from the current value of 55%1. With the arrival of widely available satellite and GIS products in recent years, coupled by rapid advances in computational capabilities, we developed a global framework for calculating the global urban growth projection by multiple applications of the SLEUTH model (GUGPS). Modifications or improvements may be required during application, especially if the target region experiences significant social or economic events, or when the area of study is located mostly along the boundaries of the modelling windows. This can be achieved by following the framework used in this study and modifying the growth coefficients or surface inputs
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