The impact of climate change in recent years has caused considerable risks to both urban and rural systems. How to mitigate the damage caused by extreme weather events has attracted much attention from countries in recent years. However, most of the previous studies on resilience focused on either urban areas or rural areas, and failed to clearly identify the difference between urban and rural resilience. In fact, the exploration of the difference between the resilience characteristics of cities and villages under climate change can help to improve the planning strategy and the allocation of resources. In this study, the indicators of resilience were firstly built through a literature review, and then a Principal Component Analysis was conducted to construct an evaluation system involving indicators such as “greenland resilience”, “community age structure resilience”, “traditional knowledge resilience”, “infrastructure resilience” and “residents economic independence resilience”. Then the analysis of Local Indicators of Spatial Association showed some resilience abilities are concentrated in either urban or rural. Binary logistic regression was performed, and the results showed urban areas have more prominent abilities in infrastructure resilience (the coefficient value is 1.339), community age structure resilience (0.694), and greenland resilience (0.3), while rural areas are more prominent in terms of the residents economic independence resilience (−0.398) and traditional knowledge resilience (−0.422). It can be seen that urban areas rely more on the resilience of the socio-economic structure, while rural areas are more dependent on their own knowledge and economic independence. This result can be used as a reference for developing strategies to improve urban and rural resilience.

The increasing demand of humankind has caused a large number of land use changes, which pose a direct or indirect threat to the environment while promoting economic growth. The lack of risk-oriented land use changes may increase the disaster risk in the region. Therefore, how to study the relationship between land use change and disaster risk deserves attention. In this study, a research framework with quantitative relationship between land use change and disaster risk was constructed from the perspective of efficiency. The framework integrated land use change, disaster losses and environment variable (runoff increment) into a three-stage data envelopment analysis (DEA) assessment model to dynamically evaluate the impact of land use changes on disasters. The main conclusions include: (I) after the influence of runoff increment and random error was excluded, the overall risk score of counties and cities in Taiwan is 0.643, which represents a relatively high level, indicating that land use changes have caused high disaster risk; and (II) the vulnerability of land development in each county and city can be obtained through the comprehensive score of disaster risk the amount of unused input. The results of this study can help government agencies to rank various types of land development and then determine the acceptable risk level and incorporate disaster risk into land development.

Whether the new type of urbanization implemented in China in the past decade has been effective in regulating urbanization and balancing human development and environmental protection remains to be verified. Therefore, this study develops a framework for assessing population-urbanization–ecological environment interactions by combining the coupling coordination degree model and the decoupling index. Firstly, the proposed framework establishes an indicator system of population, economy, society, space, environmental pressure, ecological governance, ecological status, and ecological services based on two sets of national census data; secondly, this study combines the coupling coordination degree model and decoupling index to comprehensively understand the coupling coordination relationship and the decoupling relationship of the population–urbanization–ecological environment across time and space. Overall, this study contributes to a deepened understanding of coupled population–urbanization–ecological environment interactions and provides a scientific basis for effective guidance on urban–rural management and the balance between human development and environmental protection.