The relationship between urban human dynamics and land use types has always been an important issue in the study of urban problems in China. This paper used location data from Sina Location Microblog (commonly known as Weibo) users to study the human dynamics of the spatial-temporal characteristics of gender differences in Beijing’s Olympic Village in June 2014. We applied mathematical statistics and Local Moran’s I to analyze the spatial-temporal distribution of Sina Microblog users in 100 m × 100 m grids and land use patterns. The female users outnumbered male users, and the sex ratio ( $SR$ varied under different land use types at different times. Female users outnumbered male users regarding residential land and public green land, but male users outnumbered female users regarding workplace, especially on weekends, as the $SR$ on weekends ( $SR$ was 120.5) was greater than that on weekdays ( $SR$ was 118.8). After a Local Moran’s I analysis, we found that High–High grids are primarily distributed across education and scientific research land and residential land; these grids and their surrounding grids have more female users than male users. Low–Low grids are mainly distributed across sports centers and workplaces on weekdays; these grids and their surrounding grids have fewer female users than male users. The average number of users on Saturday was the highest value and, on weekends, the number of female and male users both increased in commercial land, but male users were more active than female users ( $SR$ was 110).

Long-term exposure to ozone pollution will cause severe threats to residents’ physical and mental health. Ground-level ozone is the most severe air pollutant in China’s Pearl River Delta Metropolitan Region (PRD). It is of great significance to accurately reveal the spatial–temporal distribution characteristics of ozone pollution exposure patterns. We used the daily maximum 8-h ozone concentration data from PRD’s 55 air quality monitoring stations in 2015 as input data. We used six models of STK and ordinary kriging (OK) for the simulation of ozone concentration. Then we chose a better ozone pollution prediction model to reveal the ozone exposure characteristics of the PRD in 2015. The results show that the Bilonick model (BM) model had the highest simulation precision for ozone in the six models for spatial–temporal kriging (STK) interpolation, and the STK model’s simulation prediction results are significantly better than the OK model. The annual average ozone concentrations in the PRD during 2015 showed a high spatial variation in the north and east and low in the south and west. Ozone concentrations were relatively high in summer and autumn and low in winter and spring. The center of gravity of ozone concentrations tended to migrate to the north and west before moving to the south and then finally migrating to the east. The ozone’s spatial autocorrelation was significant and showed a significant positive correlation, mainly showing high-high clustering and low-low clustering. The type of clustering undergoes temporal migration and conversion over the four seasons, with spatial autocorrelation during winter the most significant.

China’s grain production has been on a pathway parallel to urbanization in the last 30 years. When the balance between the grain supply and demand is considered, contradiction between farming suitability and actual deviation provides warning of a crisis regarding China’s food security. In this study, we constructed a set of topologic maps to summarize the basic distribution of the farming conditions in China, and Kernel density and Local Moran’s I analyses were con-ducted to investigate the spatial-temporal pattern of China’s regional grain production based on the grain output at the county level from 1985 to 2019. The results show that the high-output zones were concentrated in the regions with superior physical conditions in 1985, and by 2019, the high-output zones had increased in the northern regions (i.e., Northeast China Plain) and decreased in the southern regions (i.e., Southern China). The surplus zones of per capita grain output were concentrated in the regions with high total outputs during 1985–2019. The shortage zones were distributed in the regions with low total outputs and low total outputs or large populations. Based on the above three results, several typical commodity grain bases have lost their dominant role (i.e., the Pearl River Delta); furthermore, the qualified commodity grain bases were compiled at both the national and regional level based on overlay analysis (i.e., the Tarbagatay Prefecture as well as eastern and central Inner Mongolia).