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.

Food self-sufficiency has long been regarded as essential for understanding and managing urban and regional food systems; however, few studies have examined the food self-sufficiency of megacity regions within a comprehensive framework that distinguishes different types of agricultural land (i.e., arable land, horticultural landscapes, and waters). To fill these gaps, we took the Pearl River Delta as a case study and quantified the foodsheds of different types of agricultural land by calculating the land footprint of food consumption. On this basis, food self-sufficiency is defined as the ratio of available and required agricultural area for regional food demand. The results indicated that the self-sufficiency level provided by the arable land in the Pearl River Delta is low and cannot realize self-sufficiency at the regional and urban levels. The horticultural landscapes can provide self-sufficiency at the regional level, whereas the regions with water cannot, as their foodsheds extend over the boundary of the Pearl River Delta. For arable land, establishing a localized regional food system requires expanding the foodshed size. These findings provide evidence that megacity regions may face increasing difficulties in achieving self-sufficiency in the near future. This research can improve policymakers’ understanding of the sustainability and resilience of regional food systems in megacity regions.

This article applies open source data of public facilities through data mining, not only to evaluate the public facilities from an objective dimension, but also to reflect the sensory opinions of the group factually, eventually realizing the evaluation measurement of urban public facilities. The research takes Shenzhen city as an empirical case and chooses typical public facilities to mine data, resolve address and weight to explore the application of public facilities evaluation under dimension reduction of open source data. The empirical study consists of three parts. First, as the objective evaluation, we estimate the density distribution and per capita of public facility through data mining and address resolution. Second, as the subjective evaluation, we carry on the location analysis to high-score public facility through attention and satisfaction data of Internet evaluation. Finally, as mentioned above, we calculate the weight of objective and subjective evaluation of public facility, eventually formatting the comprehensive evaluation of public facilities.

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.

There is a huge amount of data in the opportunity of “turning waste into treasure” with the arrival of the big data age. Urban layout is very important for the development of urban transportation and building system. Once the layout of the city is finalized, it will be difficult to start again. Therefore, the urban architectural layout planning and design have a very important impact. This paper uses the urban architecture layout big data for building layout optimization using advanced computation techniques. Firstly, a big data collection and storage system based on the Hadoop platform is established. Then, the evaluation model of urban building planning based on improved logit and PSO algorithm is established. The PSO algorithm is used to find the suitable area for this kind of building layout, and then through five impact indicators: land prices, rail transit, historical protection, road traffic capacity, and commercial potential have been established by using the following logit linear regression model. Then, the bridge between logit and PSO algorithm is established by the fitness value of particle. The particle in the particle swarm is assigned to the index parameter of logit model, and then the logit model in the evaluation system is run. The performance index corresponding to the set of parameters is obtained. The performance index is passed to the PSO as the fitness value of the particle to search for the best adaptive position. The reasonable degree of regional architectural planning is obtained, and the rationality of urban architectural planning layout is determined.