The future of cities to 2030 and better urban planning

PLoS One – A Meta-Analysis of Global Urban Land Expansion

The conversion of Earth’s land surface to urban uses is one of the most irreversible human impacts on the global biosphere. It drives the loss of farmland, affects local climate, fragments habitats, and threatens biodiversity. Here we present a meta-analysis of 326 studies that have used remotely sensed images to map urban land conversion. We report a worldwide observed increase in urban land area of 58,000 km2 from 1970 to 2000. India, China, and Africa have experienced the highest rates of urban land expansion, and the largest change in total urban extent has occurred in North America. Across all regions and for all three decades, urban land expansion rates are higher than or equal to urban population growth rates, suggesting that urban growth is becoming more expansive than compact. Annual growth in GDP per capita drives approximately half of the observed urban land expansion in China but only moderately affects urban expansion in India and Africa, where urban land expansion is driven more by urban population growth. In high income countries, rates of urban land expansion are slower and increasingly related to GDP growth. However, in North America, population growth contributes more to urban expansion than it does in Europe. Much of the observed variation in urban expansion was not captured by either population, GDP, or other variables in the model. This suggests that contemporary urban expansion is related to a variety of factors difficult to observe comprehensively at the global level, including international capital flows, the informal economy, land use policy, and generalized transport costs. Using the results from the global model, we develop forecasts for new urban land cover using SRES Scenarios. Our results show that by 2030, global urban land cover will increase between 430,000 km2 and 12,568,000 km2, with an estimate of 1,527,000 km2 more likely.

The range of the forecasts is largely due to the range of estimates of contemporary urban land cover. On the low end, the forecast of 430,000 km2 of new urban land by 2030—an area about the size of Iraq—is generated with the A2 storyline using the GLC00 data set, which is one of the more conservative global estimates of urban land cover. Under this scenario, both population and economic growth rates in the next two decades will need to decline and become lower than current rates of growth. Under the UN low population growth scenario, global population in 2050 will be 8 billion. This is a less likely scenario given that world population is currently 6.88 billion and expected to reach 7 billion by 2011. Similarly, the high end forecast of 12,568,000 km2 of new urban land by 2030—an area about the size of the United States and Argentina combined—is generated by using the GRUMP data set with an A1 storyline, a scenario that is also unlikely unless population and economic growth rates both significantly increase.

The more likely forecast of new urban extent is the one generated with the MODIS estimate of contemporary urban land cover using the B2 scenario. The B2 scenario assumes intermediate levels of economic development and continued population increase, albeit at a slower rate than in the A2 scenario. Of the three estimates of contemporary urban land cover, the MODIS-derived estimate is the most up-to-date and internally consistent. Using this combination, our forecast shows an increase of 1,527,000 km2 of new urban land area by 2030, an area nearly equal to that of the country of Mongolia. Although there is large uncertainty surrounding the range of population growth estimates, our results show that it is not only population growth that drives urban land expansion. Indeed, for many fast growing regions, population growth explains only a small fraction of the urban land expansion. Other factors such as economic growth, the informal economy, land use policies, and foreign investment will also affect the growth of urban areas.

The collection of urban areas in the meta-study is neither a random nor representative sample of the world’s urban settlements. For example, both the largest and smallest cities are underrepresented in the meta-study. Such biases can influence model parameters and projections.

Despite these limitations, the meta-analysis shows four trends that have implications for climate change adaptation, biodiversity, and human well-being. First, the total urban area as reported by the meta-analysis case studies quadrupled over the thirty years while urban population at national levels doubled. Although the meta-analysis does not include all urban areas worldwide, it provides a snapshot of patterns and rates of urban land expansion for 292 case study locations, and the results show that urban areas are expanding faster than urban population growth. Second, urban land expansion is growing faster in low elevation coastal zones than in other areas. This is likely to put millions of people at risk to climate change impacts such as storm surges and sea level rise. Third, rates of urban land expansion near protected areas are as high as in other regions. This will challenge conservation strategies because future urban expansion is expected to be both significant in total area extent and also as likely to occur near protected areas as other regions. Fourth, urban population growth and GDP explain only a percentage of urban land expansion; non-demographic factors and economic dynamics not captured by GDP also play a large role. Although global urban population is expected to increase to 5 billion by 2030 from 3.1 billion in 2010, the results indicate that many non-demographic factors, including land use policies, transportation costs, and income will shape the size of global urban extent in the coming decades


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