Land use mix (LUM) has long been employed as one of the key methods to improve urban vibrancy and optimize built-up areas. Within the urban studies discipline, LUM is usually defined as a functional compatible but diverse land use pattern. However, its quantitative methodological approaches thereby heavily rely on the diversity of land use and fail to consider functional compatibility as another critical defining characteristic, providing only a partial picture of land use pattern. Thus, reviewing LUM’s concepts and definitions, this paper develops a new index to describe functional compatibility according to the spatial segregation measurements. To evaluate and provide empirical evidence of the proposed index, this paper selects the medium-sized city of Xiangtan as a case study. The findings demonstrate that Xiangtan exhibits a quite compatible land use pattern to a certain extent. In addition, particular clusters with relatively incompatible land use patterns are observed, which are closely linked to a special historical working unit, the ‘Danwei’ compounds, and a special rural planning authority, ‘Township-Village-Enterprise’, in China. Finally, an integrated evaluation is conducted based on the proposed index and Shannon entropy index, which can be regarded as a useful tool in future land use planning while contributing to shaping a sustainable form of urban development.

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The stay areas in walking tours are the service and management unit of recreational walking in metropolitan areas. The rational characterization of stay areas in walking tours is of great significance for developing local tourism, constructing appropriate public facilities, optimizing the configuration of tourist elements, and improving facility efficiency. The existing research focuses mainly on functional, top-down classifications of tourism, tourist behavior patterns, and route designs, but it has left tourists’ stay areas largely unaddressed. To fill this gap, we propose a new framework for the interpretation of stay areas in walking tours based on GPS trajectory data and accompanying photos uploaded by users. Taking the Zhuhai–Macao metropolitan area as an example, we first captured the stay points and clustered them to the walking tour stay areas using DBSCAN. The characteristics of the stay areas were then collected, and a hierarchical analysis was conducted in terms of spatial features and geotagged photos. The results show that the stay areas can be grouped into six categories displaying obvious differences in spatial distribution, landscape features, and tourist activities. We also found the connections between Zhuhai City and the Macao Special Administrative Region (SAR) to be relatively weak. In conclusion, our results can contribute to tourism planning as well as the further management and allocation of recreational service facilities in the area researched.