Physical geography focuses on the Earth surface system and is dedicated to revealing how people affect the environment and how the environment reacts to people. Based on its characteristic spatial cognitive perspective, the inductive–deductive combined approach, and the comprehensive research paradigm that integrates multiple elements, processes, and scales, physical geography always provides an important scientific basis for understanding human–nature interactions and solving sustainable development issues in different eras. Putting theory into practice, physical geography plays a pivotal role in realizing the UN Sustainable Development Goals and China’s goal of ecological civilization. At present, China is in a stage of rapid socio-economic development and global conditions are changing more quickly than ever. Based on its disciplinary characteristics and traditional advantages, physical geography in China should always develop around social needs and play an increasing role in resource- and environment-related policies and outreach. Future development of physical geography as a discipline in China is expected, taking spatial cognition as the basic perspective and human–nature interaction as the core content, along with the combination of deductive and inductive approaches and the strengthening of interregional integration, all under the goal of sustainability. Considering the shared environmental challenges and the complexity of interconnections between countries in the context of globalization, the academic exploration and practice of physical geography in China have been providing scientific support for the sustainable development of China and beyond.

Landscape ecological risk assessment can effectively identify key elements for landscape sustainability, which directly improves human wellbeing. However, previous research has tended to apply risk probability, measured by overlaying landscape metrics to evaluate risk, generally lacking a quantitative assessment of loss and uncertainty of risk. This study, taking Liaoyuan City as a case area, explores landscape ecological risk assessment associated with mining cities, based on probability of risk and potential ecological loss. The assessment results show landscape ecological risk is lower in highly urbanized areas than those rural areas, suggesting that not only cities but also natural and semi-natural areas contribute to overall landscape-scale ecological risk. Our comparison of potential ecological risk in 58 watersheds in the region shows that ecological loss are moderate or high in the 10 high-risk watersheds. The 35 moderate-risk watersheds contain a large proportion of farmland, and the 13 low-risk watersheds are mainly distributed in flat terrain areas. Our uncertainty analyses result in a close range between simulated and calculated values, suggesting that our model is generally applicable. Our analysis has good potential in the fields of resource development, landscape planning and ecological restoration, and provides a quantitative method for achieving landscape sustainability in a mining city.

Timely and accurate information of cotton planting areas is essential for monitoring and managing cotton fields. However, there is no large-scale and high-resolution method suitable for mapping cotton fields, and the problems associated with low resolution and poor timeliness need to be solved. Here, we proposed a new framework for mapping cotton fields based on Sentinel-1/2 data for different phenological periods, random forest classifiers, and the multi-scale image segmentation method. A cotton field map for 2019 at a spatial resolution of 10 m was generated for northern Xinjiang, a dominant cotton planting region in China. The overall accuracy and kappa coefficient of the map were 0.932 and 0.813, respectively. The results showed that the boll opening stage was the best phenological phase for mapping cotton fields and the cotton fields was identified most accurately at the early boll opening stage, about 40 days before harvest. Additionally, Sentinel-1 and the red edge bands in Sentinel-2 are important for cotton field mapping, and there is great potential for the fusion of optical images and microwave images in crop mapping. This study provides an effective approach for high-resolution and high-accuracy cotton field mapping, which is vital for sustainable monitoring and management of cotton planting.

Rapid urbanization, while enhancing the living standards, posed significant challenges to food security (FS) and water quality security (WQS). Previous research mainly focused on assessing FS and WQS, remaining their trade‐off and driving pathway unclear. Taking Yangtze River Delta as study area, this study quantified FS and WQS from 2000 to 2020, and explored their trade‐off and driving pathways at both county and regional scales. The results indicated that FS and WQS showed opposite spatial patterns, while both of them experienced significant declining trends across county and regional scales. Although both synergy potential and trade‐off intensity showed increasing trends, the mitigation of FS‐WQS trade‐off remained challenging due to the substantially greater rise in trade‐off intensity compared to synergy potential. “Win‐win” combinations were identified with high FS, high WQS and the lowest opportunity cost. Urbanization, especially urban expansion and population growth, significantly intensified the trade‐off by reducing food production while increasing demands for both food and water quality. This study finally established a conceptual framework for characteristics and driving mechanisms of FS, WQS and their trade‐off at different urbanization stages, offering scientific insights for sustainable development in rapidly urbanizing regions.

There is global enthusiasm for payments for ecosystem services (PES) programs to solve environmental problems, including in China. However, PES programs in China go against the principle of ‘voluntary transaction’, which weakens the influences of economic factors on farmers’ participation decisions and makes it hard to reveal their influence on farmers’ participation willingness. Using household survey data and a logistic regression model, this study attempts to understand the influencing factors of farmers’ decision-making on involvement in PES projects for hypothetical voluntary participation and focuses on whether the farmer would reject the program if the payment stopped. A surprising but promising result is found in the case of the Paddy Landto-Dry Land (PLDL) program in Chicheng County, China, wherein, apart from the negative impact of education and the positive effect of off-farm income, two non-economic factors play a significant role in farmers’ participation. The one is basic cognition, which negatively affects farmers’ participation, and the other is inner altruistic motivation, which positively contributes to the participation. In addition, the high proportion of reconversion to paddy land after the payment period threatens the long-term sustainability of the PLDL program. Faced with the low education and environmental cognition statuses in remote agricultural areas, increasing educational quality and promoting the popular awareness of PES programs in rural areas should be highlighted in sustaining the efficiency and effectiveness of PES programs in the long run.