People explosion and fast economic growth are bringing a more serious land resource shortage crisis. Rational land-use allocation can effectively reduce this burden. Existing land-use allocation models may deal with a lot of challenges of land-use planning. This study proposed a hybrid quantitative and spatial optimization land-use allocation model that could enrich the land-use allocation method system. This model has three advantages compared to former methods: (1) this model can simultaneously solve the quantitative land area optimization problem and spatial allocation problem, which are the two core aspects of land-use allocation; (2) the land suitability assessment method considers various geographical, economic and environmental factors which are essential to land-use allocation; (3) this model used an interval stochastic fuzzy programming land-use allocation model to solve the quantitative land area optimization problem. This model not only considers three uncertainties in the natural system but also involves various economic, social, ecological and environmental constraints—most of which are specifically put into the optimization process. The proposed model has been applied to a real case study in Liannan county, Guangdong province, China. The results could help land managers and decision makers to conduct sound land-use planning/policy and could help scientists understand the inner contradiction among economic development, environmental protection, and land use.

The major grain-producing areas will be the key areas of future China fallow. It is important to explore the influence of farmers’ value perceptions on their fallow willingness in these areas. We analyzed this impact of value perception by using an ordered PROBIT model and survey data from the major grain-producing areas of Hubei and Hunan, China. The conclusions of this study are as follows: (1) A considerable proportion of farmers are willing to participate in farmland fallow, while a considerable proportion of farmers are neutral; (2) farmers’ value perceptions of farmland fallow have a significant positive impact on their fallow willingness; (3) farmers’ ages and education levels have a positive impact on farmers’ willingness to directly participate in farmland fallow, while per capita farmland area has a negative impact; (4) the key factors for successful fallow are solving the problem of non-agricultural employment of farmers and appropriately formulating fallow mode, scale, and subsidy standards. This study proposes that the government can develop farmers’ good value perceptions of fallow through appropriate subsidies and adequate publicity to strengthen their fallow consciousness.

As China’s economy advances into a new stage of high-quality development driven by scientific and technological innovation, it is of great practical importance to probe what effects land disposition, which underpinned the previous round of rapid economic growth, and may have an exertion on developing innovation. Based on a deep exploration of the potential positive and negative influences of land disposition in relation to the effects of land finance on urban innovation, we employed a dynamic spatial Durbin model, along with panel data from 266 Chinese prefecture-level cities over the period 2004–2017. The empirical results show that the development of China’s urban innovation has had significant path dependence, spatial agglomeration, and inhibiting effects on neighboring cities, and these effects are attributed to inter-governmental competition and the Matthew effect. Overall, the combined impacts of land disposition modes on urban innovation have changed, from facilitative in the early stage to inhibitory at present. In the developed cities of east China, the facilitative effect of land disposition has weakened gradually, and tends to disappear entirely, while the change in impact over time in less developed mid-western cities is consistent with the national sample. This study broadens our understanding of the role of land disposition in China’s urban innovative development and has meaningful direct implications for policymakers.

COVID-19 is threatening the whole world. This paper aims to explore the correlation between climatic factors and the morbidity of COVID-19 in Wuhan, China, mainly by using a geographic detector and GWR model. It was found that the response of the morbidity of COVID-19 to meteorological factors in Wuhan is different at different stages. On the whole, the morbidity of COVID-19 has a strong spatial aggregation, mainly concentrated in the central area of Wuhan City. There is a positive correlation between wind speed and the spread of COVID-19, while temperature has a negative correlation. There is a positive correlation between air pressure and the number of COVID-19 cases. Rainfall is not significantly correlated with the spread of COVID-19. It is concluded that wind speed, relative humidity, temperature, and air pressure are important meteorological factors affecting the spread of COVID-19 in Wuhan. Any two variables have greater interaction with the spatial distribution of the incidence rate of COVID-19 than any one factor alone. Those findings not only provide a new insight for the key intervention measures and the optimal allocation of health care resources accordingly but also lay a theoretical foundation for disease prevention, disease intervention and health services.

Land-use allocation models can effectively support sustainable land use. A large number of studies solve the problems of land-use planning by constructing models, such as mathematical models and spatial analysis models. However, these models fail to fully and comprehensively consider three uncertain factors of land-use systems: randomness, interval and fuzziness. 33Therefore, through the study of the watershed land-use system, this paper develops a land-use allocation model considering the regional land–society–economy–environment system under uncertain conditions. On the basis of this model, an interval fuzzy two-stage random land-use allocation model (IFTSP-LUAM) combining social, economic and ecological factors is proposed to provide sustainable development strategies at the basin level. In addition, the proposed IFTSP-LUAM takes into account the above three uncertainties and multistage, multiobjective, dynamic, systematic and complex characteristics of typical land-use planning systems. The results showed that the model considers more socioeconomic and ecological factors and can effectively reflect the quantitative relationship between the increase in economic benefits and the decrease in environmental costs of a land-use system. The model was applied to land-use planning of Nansihu River Basin in Shandong Province. The results provided a series of suitable land-use patterns and environmental emission scenarios under uncertain conditions, which can help the watershed environmental protection bureau and watershed land-use decision-makers to formulate appropriate land-use policies, so as to balance social and economic development and ecological protection. The simulation results can provide support for an in-depth analysis of land-use patterns and the trade-off between economic development and ecological environment protection.