The non-grain production rate (NGPR) of cropland is a grave threat to global grain and food supply, and has been a hot issue across the world. However, few scholars explored the impacts of the NGPRs of different cropland types, such as those of paddy land and irrigated land in the same region. Thus, according to the third land survey data, this research first estimated the NGPRs of cropland, paddy land, irrigated land, and dry land at different scales in Shandong Province, China in 2019. Then, their spatial characteristics at a county scale were identified by combining the standard deviation ellipse model and spatial autocorrelation analysis. Finally, the potential driving factors of the NGPR of cropland were explored with the geographical weight regression model. Results are as follows: (1) The NGPR of cropland is at relatively lower level in Shandong Province and is dominated by that of irrigated land, and the NGPR of dry land is higher than those of other cropland types; (2) Significant regional differences exist in the NGPR of cropland, with profound severity in the southeast and much lower in the northwest; (3) At the provincial scale, the total power of agricultural machinery per capita and utilization degree of cropland factors can relieve the NGPR of cropland in nearly the entire research area. The proportion of GDP of the primary industry in GDP, urban population rate, and DEM are the main obstacles for NGPR decrease. At the county scale, the influences of driving factors varied across regions. This research can provide targeted and regional differentiated references for policy improvement and NGPR management.

Land use intensity (LUI) reflects the utilization status of land use. However, traditional LUI assessments have been conducted for land space governance with a primary focus on surface land. Thus far, the explicit variation and spatiotemporal characteristics of land use of underground space (LUUS), particularly the quantization of LUUS-related intensity, are not well understood. Using the case of Wuhan in China, this study takes the main urban area of Wuhan as the research area, based on the time series data of the underground space information survey of analysis units from 2002 to 2018. This reflected the distribution pattern and evolution characteristics of underground space in terms of the intensity, the concentration and spatial hot-spots by using the spatiotemporal analysis framework. The results show that: (1) The LUUS exhibits spatial characteristics of global dispersion, and local aggregation increased and expanded along the northwest–southeast direction; (2) The global spatial dependency of LUUS is strong and the degree decreases with the expansion of the scope; (3) The LUUS is mainly developed in a relatively concentrated mode, and the concentration degree decreases with time; (4) The main development area of the LUUS is gradually expanding from within the inner ring line outside the second ring road in different periods, and the spatial difference is more obvious and increasing. Our study renews the indicators of quantitative LUI evaluation based on underground spatial data. The findings refreshed the knowledge base concerning the spatiotemporal heterogeneity in terms of underground space intensity and provided new insights into spatial governance.

Insomnia is a prevalent sleep disorder that causes serious harm to individuals and society. There is growing evidence that environmental factors may be associated with sleep disorders, but few studies have explored the relationship between insomnia and urban functional structure from a spatial perspective. This study collected multi-source big data (e.g., insomnia posts on Weibo, locations of urban facilities on Baidu) and explored the effects of different urban spatial element configurations on residents’ insomnia. The ordinary least squares (OLS) and geographically weighted regression (GWR) models were used to quantify the global and local effects of urban functional categories on residents’ insomnia. The results showed that the quantity of catering service facilities accounted for the largest proportion, and the consumer function was the most consistent with the distribution of insomnia. There is a domain relationship between the incidence of insomnia and urban functional zones. It has the strongest correlation with employment mixed functional zones and the weakest with residential mixed functional zones. These findings could serve as references for the functional structure and layout of urban space for improving the sleep health of residents and benefit for urban health.