Climate change threatens agricultural production across sub-Saharan Africa, where most farmers rely on rainfall. A study by researchers at the University of Göttingen and the European Commission’s Joint Research Centre shows that Ghanaian cocoa farmers who cultivate cocoa under shade trees – a practice known as agroforestry – are better able to withstand periods of reduced rainfall. However, the study also finds that these benefits are confined to Ghana’s wetter regions, which have a climate that better suits growing cocoa. In drier regions, where water is already scarce, the researchers find no significant advantages of agroforestry in maintaining yields during times of less rainfall. The results were published in the journal Agricultural Systems.

Cross-city transfer learning (CCTL) has emerged as a crucial approach for managing the growing complexity of urban data and addressing the challenges posed by rapid urbanization. This paper provides a comprehensive review of recent advances in CCTL, with a focus on its applications in urban computing tasks, including prediction, detection, and deployment. We examine the role of CCTL in facilitating policy adaptation and influencing behavioral change. Specifically, we provide a systematic overview of widely used datasets, including traffic sensor data, GPS trajectory data, online social network data, and map data. Furthermore, we conduct an in-depth analysis of methods and evaluation metrics employed across different CCTL-based urban computing tasks. Finally, we emphasize the potential of cross-city policy transfer in promoting low-carbon and sustainable urban development. This review aims to serve as a reference for future urban development research and promote the practical implementation of CCTL.