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Delimiting the urban growth boundary (UGB) is important for limiting urban sprawl and improving urban sustainability. However, the future UGB delimitation for the entire China is still lacking. Here, we delimited China's UGBs before 2100 under localized shared socioeconomic pathways and 11 urban expansion modes (i.e., spontaneous growth, organic growth, and nine modes integrating both) and evaluated the urban shrinkage pressure and the effects on other land use/cover types and ecosystem services. The results revealed that China's urban land demand was projected to increase first and then decrease under five scenarios before 2100. The extent of UGBs was projected to be 121,199–142,982 km2, 34.14–58.25% higher than the urban area in 2020. As a result of urban population decline, China's urban land demand in 2100 was projected to be 20.83–53.41% lower than the extent of UGBs, implying that China, especially the three provinces of Heilongjiang, Jilin, and Liaoning, will face remarkable urban shrinkage pressure. Future urban expansion in China will mainly occupy cropland, and lead to a simultaneous decline in habitat quality, food production and carbon sequestration. Spontaneous growth will cause greater losses of ecosystem services than organic growth at the national scale, while in some provinces, such a difference will be reversed. To address the urban shrinkage pressure, China needs to control urban area and optimize urban spatial patterns based on UGBs. In addition, the place‐based optimal urban expansion mode is also required to reduce the negative impacts of future urban expansion on ecosystem services and promote sustainable development. Plain Language Summary: Urban expansion has caused a series of ecological and social problems. Therefore, setting urban growth boundaries around cities to limit urban sprawl within such boundaries and reduce its negative impacts has been a critical way for sustainable development. This study delimited China's urban growth boundaries before 2100 under five scenarios of localized shared socioeconomic pathways and 11 urban expansion modes (i.e., spontaneous growth, organic growth, and nine modes integrating both) and evaluated the potential effects of future urban expansion on urban shrinkage pressure, other land use/cover types and ecosystem services. The results showed that China's urban land demand was projected to show an increasing trend followed by a decrease under five scenarios from 2021 to 2100, leading to a nationwide urban shrinkage pressure, and the effects of future urban expansion on ecosystem services varied with urban expansion modes. This study suggests that China, especially the three provinces of Heilongjiang, Jilin, and Liaoning, should take measures to optimize urban spatial patterns and address urban shrinkage pressure, and each province needs to take the place‐based optimal urban expansion mode based on the environmental, social, and economic characteristics to improve urban sustainability. Key Points: The extent of China's urban growth boundary was projected to be 34.14–58.25% higher than the urban area in 2020China's urban land demand in 2100 would be lower than the extent of UGBs, implying China will face remarkable urban shrinkage pressureChina should take effective measures to address the urban shrinkage pressure and reduce the negative impacts from urban expansion [ABSTRACT FROM AUTHOR]

Urbanization and climate change are together exacerbating water scarcity—where water demand exceeds availability—for the world's cities. We quantify global urban water scarcity in 2016 and 2050 under four socioeconomic and climate change scenarios, and explored potential solutions. Here we show the global urban population facing water scarcity is projected to increase from 933 million (one third of global urban population) in 2016 to 1.693–2.373 billion people (one third to nearly half of global urban population) in 2050, with India projected to be most severely affected in terms of growth in water-scarce urban population (increase of 153–422 million people). The number of large cities exposed to water scarcity is projected to increase from 193 to 193–284, including 10–20 megacities. More than two thirds of water-scarce cities can relieve water scarcity by infrastructure investment, but the potentially significant environmental trade-offs associated with large-scale water scarcity solutions must be guarded against. This paper quantifies global urban water scarcity in 2016 and 2050 and explores potential solutions. One third to nearly half of the global urban population is projected to face water scarcity problems. [ABSTRACT FROM AUTHOR]

Accurately simulating urban expansion is of great significance for promoting sustainable urban development. The calculation of neighborhood effects is an important factor that affects the accuracy of urban expansion models. The purpose of this study is to improve the calculation of neighborhood effects in an urban expansion model, i.e., the land-use scenario dynamics-urban (LUSD-urban) model, by integrating the trend-adjusted neighborhood algorithm and the automatic rule detection procedure. Taking eight sample cities in China as examples, we evaluated the accuracies of the original model and the improved model. We found that the improved model can increase the accuracy of simulated urban expansion in terms of both the degree of spatial matching and the similarity of urban form. The increase of accuracy can be attributed to such integration comprehensively considers the effects of historical urban expansion trends and the influences of neighborhoods at different scales. Therefore, the improved model in this study can be widely used to simulate the process of urban expansion in different regions. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is an important area that affects global sustainable development. Quantifying spatiotemporal patterns of urbanization is crucial for maintaining the sustainability on the TP. This study took Xining City, the largest city on the TP, as an example to understand the urban expansion in this region in the past 50 years. We combined the high-resolution spy satellite data and China's long-term urban land dataset (CULD) to quantify the urban expansion of Xining City. The object-oriented random forest classification was performed to extract urban land from spy satellite data in 1969, and the inter-annual correction was used to combine urban land information from 1969 to 2017. We found that the proposed approach can accurately quantify the urban expansion of Xining City over the past half century with an overall accuracy of 91% and a kappa coefficient of 0.86. Such high accuracy benefits from the fine resolution of spy satellite data and the consistency of CULD. We also found that Xining City experienced accelerated and fragmented urban sprawl to higher altitude areas, as a result of socioeconomic development and topographical limitations. The acceleration of urban expansion was more obvious, and the urban landscape fragmentation was more serious at high altitude areas. Such urban expansion encroached on cropland and grassland, and caused increased risks of landslides and other geological disasters. Therefore, Xining City urgently needs to promote the development of compact cities to control urban sprawl at higher altitude areas and provide a reference for improving urban sustainability across the TP. In this study, we analyzed the urban expansion of Xining city from 1969 to 2017, and provided a reliable way to understand the long-term spatiotemporal urbanization based on remote sensing, which has the potential for wide applications. In addition, the extracted urban information can help to improve the urban sustainability of Xining City and the entire TP. [ABSTRACT FROM AUTHOR]