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Scientific and practical identification and analysis of the differences in the spatial structure of metropolitan areas are of great significance to the long-term development of metropolitan areas and urban agglomerations. Because the current research focuses more on the external spatial structure of the metropolitan area and less on the internal spatial differences, this study is based on remote sensing data, POI data, and road vector data combined with a spatial clustering algorithm with location constraints. Multi-level analysis of spatial clustering and differences within the circle. Theresearch results show that compared with the traditional algorithm, spatial clustering with location constraints can identify the group structure within the metropolitan area to a large extent. At the same time, the single-factor and multi- factorclustering results show that the Changsha-Zhuzhou-Xiangtan metropolitan area currently has large internal spatial differences; Except for Changsha, Zhuzhou, and Xiangtan core urban areas, no apparent cluster structure has been formed. This study can well reflect the current heterogeneity of the internal spatial structure of the Chang-Zhu-Tan metropolitan area and provide a solid reference for the future developmentof the metropolitan area