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The polycentric spatial structure is the most common spatial form of urban agglomerations, so exploring the evolution of this structure and analyzing its influencing factors is of great significance for the optimization of the spatial structure of urban agglomerations. However, there are relatively few studies on the topic that fuse multisource big data analysis, especially in the urban agglomeration of Western China. Therefore, this study uses a fusion of nighttime light (NTL) data, point of interest (POI) data and LandScan data to identify the polycentric spatial structure and its evolution in the Kunming–Yuxi (Kunyu) urban agglomeration and analyzes the factors that have dominated its evolution at different periods using geographic detectors. Results show that the fusion of multisource big data are more in line with the actual development process of the Kunyu urban agglomeration and the factors that have dominated the spatial evolution at different periods vary but the government and sectors have gradually become increasingly important. This study provides a feasible path for exploring urban spatial evolution through the fusion analysis of multisource big data in the Kunyu urban agglomeration and provides a reference for the key directions of urban agglomeration planning and development at different periods. [ABSTRACT FROM AUTHOR]