Due to high-intensity human disturbance and rapid climate change, optimizing the spatial pattern of land use has become a pivotal path to restoring ecosystem functions and realizing the sustainable development of human–land relationships. This review uses the literature analysis method combined with CiteSpace to determine current research progress and frontiers, challenges, and directions for further improvement in this field. The main conclusions include the following: (a) research on the optimization of spatial pattern of land use has transformed from pattern description orientation to sustainable development orientation to ecological restoration orientation. Its research paradigm has changed from pattern to function to well-being; (b) the research frontier mainly includes spatial pattern of land use that takes into account the unity of spatial structure and functional attributes, the ecological mechanism and feedback effect of change in spatial pattern of land, the theoretical framework and model construction of land use simulation and prediction based on multiple disciplines and fields, and the adaptive management of sustainable land use in the context of climate change; (c) based on current research challenges, we integrate the research on landscape ecology and ecosystem service flows to develop an “element sets–network structure–system functions–human well-being” conceptual model. We also propose the strengthening of future research on theoretical innovation, spatiotemporal mechanism selection, causal emergence mechanism, the transformation threshold, and uncertainty. We provide innovative ideas for achieving sustainable management of land systems and territorial spatial planning with the aim of improving the adaptability of land use spatial optimization. This is expected to strengthen the ability of land systems to cope with ecological security and climate risks.

Land use conflicts induced by human activities cause accelerated soil erosion. The response of soil erosion to spatial conflict in production-living-ecological space (PLES) is not clearly understood. In this research, models such as PLES spatial conflict, revised universal soil loss equation, bivariate spatial autocorrelation, and an optimal parameter-based geographical detector were used to explore the characteristics and drivers of soil erosion in response to spatial conflict in the PLES of the Dongting Lake watershed. Results show that spatial changes of the PLES first increased and then decreased. Approximately 45% of the area was consistently in moderate or higher conflict levels throughout the study period. The average soil erosion rate showed a decreasing trend for each year except in the period 2000–2005, when moderate erosion increased. The spatial correlation between spatial conflict and soil erosion was found to be in the form of an inverted “U” for the high-high and low-high agglomeration patterns, and a decreasing trend for the high-low ones. Approximately 27% of the area must be traded off between the spatial conflict of the PLES and soil erosion. The influence of GDP and population density was significant. DEM interacted strongly with GDP, NDVI, precipitation, population density, and “return of farmland to forest” policy. Different patterns were formed among the factors through actions such as amplification, mitigation, catalysis, and dependence effects. We propose policy recommendations based on the differences in the driving mechanisms of the respective models.

Fine particulate matter (PM_2.5) pollution brings great negative impacts to human health and social development. From the perspective of heterogeneity and the combination of national and urban analysis, this study aims to investigate the variation patterns of PM_2.5 pollution and its determinants, using geographically and temporally weighted regression (GTWR) in 273 Chinese cities from 2015 to 2019. A comprehensive analytical framework was established, composed of 14 determinants from multi-dimensions, including population, economic development, technology, and natural conditions. The results indicated that: (1) PM_2.5 pollution was most severe in winter and the least severe in summer, while the monthly, daily, and hourly variations showed “U”-shaped, pulse-shaped and “W”-shaped patterns; (2) Coastal cities in southeast China have better air quality than other cities, and the interaction between determinants enhanced the spatial disequilibrium of PM_2.5 pollution; (3) The determinants showed significant heterogeneity on PM_2.5 pollution—specifically, population density, trade openness, the secondary industry, and invention patents exhibited the strongest positive impacts on PM_2.5 pollution in the North China Plain. Relative humidity, precipitation and per capita GDP were more effective in improving atmospheric quality in cities with serious PM_2.5 pollution. Altitude and the proportion of built-up areas showed strong effects in western China. These findings will be conductive to formulating targeted and differentiated prevention strategies for regional air pollution control.