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Comparing with cities, rural communities especially those declining rural communities have become vulnerable to natural disasters owing to their backward socioeconomic conditions. Taking Xun County of China's Henan Province as the study area, the paper aims to evaluate rural community resilience to flood by unveiling the connection between individuals' cognition, follow-up actions and the community resilience. Research results show that: (1) The logic chain exists as individual's cognition to disaster leads to their constructive actions to cope with disaster, which contribute to community resilience. (2) At the cognition dimension, individual's knowledge reserve of disaster prevention and their recognition to local authority are playing an important role in their decision making and follow-up behaviors when disaster occurs. (3) At the action dimension, individual's familiarity with the disaster preparedness, efficient information transmission when disaster occurs and villagers' following order and their unity of action all contribute to community resilience to disaster. The paper proposes ways to improve rural community resilience to disasters based on the research findings. [ABSTRACT FROM AUTHOR]

Wildfire is essential in altering land ecosystems' structures, processes, and functions. As a critical disturbance in the China–Mongolia–Russia cross-border area, it is vital to understand the potential drivers of wildfires and predict where wildfires are more likely to occur. This study assessed factors affecting wildfire using the Random Forest (RF) model. No single factor played a decisive role in the incidence of wildfires. However, the climatic variables were most critical, dominating the occurrence of wildfires. The probability of wildfire occurrence was simulated and predicted using the Adaptive Network-based Fuzzy Inference System (ANFIS). The particle swarm optimization (PSO) model and genetic algorithm (GA) were used to optimize the ANFIS model. The hybrid ANFIS models performed better than single ANFIS for the training and validation datasets. The hybrid ANFIS models, such as PSO-ANFIS and GA-ANFIS, overcome the over-fitting problem of the single ANFIS model at the learning stage of the wildfire pattern. The high classification accuracy and good model performance suggest that PSO-ANFIS can be used to predict the probability of wildfire occurrence. The probability map illustrates that high-risk areas are mainly distributed in the northeast part of the study area, especially the grassland and forest area of Dornod Province of Mongolia, Buryatia, and Chita state of Russia, and the northeast part of Inner Mongolia, China. The findings can be used as reliable estimates of the relative likelihood of wildfire hazards for wildfire management in the region covered or vicinity. [ABSTRACT FROM AUTHOR]

China's rapid urbanization growth during the past decades which has highly promoted its affluence has induced various challenges for the countryside. The problem of rural decline of quite many villages which are suffering depopulation in turn challenges the urbanization sustainability in China. By way of in-depth historical and literature review, the paper finds distorted urban-rural relationship and the tendency of village decline owing to China's long time urban biased policy. By further investigating China's new-type urbanization strategy, the paper draws concerns about future rural development which is less mentioned in the plan. It calls for ruralization and actions to revitalize the countryside so as to be adapted to China's new-type urbanization plan. [ABSTRACT FROM AUTHOR]

The article discusses the Chinese government's emergency emissions reduction strategy which aims to reduce air pollution and mentions topics including a decline in the concentration of particulate matter and a study about the environmental effects of urban and rural development.

A letter to the editor is presented related to a study on geological implications of China's land creation projects, led by researcher Peiyue Li and others.