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The optimal allocation of land‐use is an important technical means to solve the contradiction be‐ tween supply and demand of land resources and to coordinate social and economic development with eco‐ logical protection, and it is also one of the key issues that need to be solved for the sustainable use of land resources. With the development of spatial simulation and intelligent optimization technology, the theoretical basis and methodological system of land‐use optimization are constantly updated. Based on bibliometrics analysis, this paper systematically summarized the driving theories and methodology of land‐use optimal al‐ location at home and abroad, focused on the application of spatial simulation models and intelligent optimization models in land‐use optimization problems, discussed and prospected the challenges and the future development of optimal land‐use allocation, and put forward that: The coupling drive of natural and human processes, spatial collaboration of multiple models, embedding big data knowledge mining methods, and the support of digital twin technology, should be the research direction of the next stage in the field of optimal land‐use allocation. [ABSTRACT FROM AUTHOR]

With the development of China’s rail transit system, the transfer problem directly affects the convenience of hundreds of thousands of passengers day after day, and has become an important factor which affects the operation of public transportation systems. The problem of public transportation transfer should be “people-oriented” and analyzed from the time and space mode of passengers' transfer. Based on the smart card data (SCD) of Wuhan City in March 2015, this paper studies the time-space characteristics of passenger transfer, analyzes the current situation of rail transit development, and summarizes the transfor travel mode. The research results are as follows:① In the process of the development of rail transit in Wuhan, the imbalance of rail transit services has arisen and a single-center urban structure has emerged. ② The geographical characteristics of transfer behavior are related to the city’s own geographical pattern, and three factors which influence the transfer behavior are proposed. ③ Using intelligent bus card data, it can effectively identify the social behavior of passengers (transfer behavior) and the time and space mode of passengers traveling. This paper analyzes the spatiotemporal patterns of travel behaviors such as transfer behavior and urban planning and urban space utilization from the perspective of “people-oriented” based on the analysis of big data. [ABSTRACT FROM AUTHOR]