The abandonment of cultivated land has profoundly affected the agroecological landscape, national food security, and farmer livelihoods, especially in China. Based on land use change survey data and national geoinformation survey data, this paper identified the distribution of abandoned cultivated land and analyzed the overall characteristics and spatial differentiation patterns of abandoned cultivated land in China. The results showed that: (1) In 2017, the abandoned area of cultivated land in China was approximately 9.10 million hectares, with an overall abandoned rate of approximately 5.57%. (2) The distribution of abandoned land in China had obvious spatial differences, and the trend of the area of abandoned land had an “inverted U” shape from east to west. (3) The pattern of abandonment showed a trend of spreading from a scattered distribution to a concentrated and continuous expansion from the edges of large cities and remote rural areas to the main grain-producing regions of fertile cultivated land. (4) The cultivated land abandonment has a great impact on grain production capacity, and there are differences among provinces. In 2017, China lost 40.89 million tons of grain yield due to cultivated land abandonment, accounting for 6.48% of the total grain yield, and the loss of potential grain yield reached 254.45 million tons. The cultivated land abandonment was driven not only by social effects under the dual structure of urban and rural areas but also by the rational choices of farmers under the overall balance of national policy, cultivated land income, and opportunity cost under the framework of urbanization. In the future, policy tools such as fallowing, land conversion, high farmland construction standards, and subsidies should be used to implement differentiated land use policies and optimize the spatial pattern of cultivated land use.

Simulating the future evolution of the internal land use structure of rural settlements (RSILUS) is vital for rural land management. However, previous simulation studies have mostly regarded rural settlements as a whole, thereby ignoring their internal structural variations. In this paper, as an example, we select Pinggu District, which has experienced the impact of rapid urbanization and has an unstable rural land use structure (LUS); then, we examine the driving factors of the changes in the RSILUS, construct a cellular automata (CA)–Markov simulation model specifying the RSILUS, and simulate its changes in 2025. The results indicate the following. (1) The influencing factors of various land use changes in rural settlements in Pinggu District differ significantly. Basic land, such as living functional land, is greatly influenced by natural resources, whereas production functional land is subject to socioeconomic factors. (2) The simulation results demonstrate that from 2015 to 2025, the production and living functional land areas of rural settlements will decrease as a whole. Accordingly, the distribution of rural public service land (RPSL) will tend to remain stable, and the trends of land use abandonment and functional degradation will continue as rural areas continue to recede. Our study enriches the research on rural land use systems by refining the simulation of rural settlements to focus on their internal structure. The differentiation and complexity of the changes in rural LUS types further suggests that rural planning and renewal should adapt to the changing conditions of the RSILUS, and the LUS should be adjusted to improve the constructed environment in human settlements and equalize urban and rural areas.

An urban heat island (UHI) is an urban area where temperatures are higher than they are in the surrounding suburban areas. UHIs are of great scientific concern in the context of global environmental change. As a result of rapid economic development over the past three decades, the urban area in China has increased significantly. In the present study, to objectively determine the spatiotemporal patterns of UHI effects in Nanjing, surface brightness temperatures of the urban areas of Nanjing, which originated from remote sensing imagery of Landsat TM/ETM+ from 1988 to 2011, were inversed, and then the UHIs were extracted and graded by choosing a stable forest area as the suburban reference. When the results were combined with the surface meteorological data, a good relationship was found between the brightness temperatures and the ground-truth temperatures. The results of contrast analysis indicated that, over time, most of the heat islands of Nanjing remained over the central portions. The area and the intensity of the heat islands have both increased remarkably over the past 20 years.