| Summary: | The research on the relationship between residents' daily activities and urban spatial structure is of considerable significance to urban planning engineering and the organization of urban functions. However, little research considers the perspective of micro-spatial scale or resident perception. The increasing user-generated activity check-in data in social networks provides a database for this research. In this study, we first divided the urban space into nine functions that satisfy the residents' activities, then used the small-scale grid to divide the city blocks and used information entropy to evaluate the mixed degree of land use functions. We then introduced the latent Dirichlet allocation (LDA) topic model to identify 15 mixed patterns of land use functions and each spatial unit's topic distribution. Moreover, the JS divergence index was employed to measure spatial units' similarity, fit the distance-activity intensity decay curve, and studied the influence of the individual spatial function distribution choice. We demonstrate that in urban space, residents' daily activities mold the blending of urban area functions and shift single-function urban planning to mixed-use, consisting of single-function dominant and multi-function mixed. Besides, the functional complementarity between the activity units weakens the distance attenuation effect of the activity-space interaction intensity to some extent. The research on the interaction between active space and spatial activities expect to support the combination of urban land use types, the layout of facilities, and the guidance of residents' activities.
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