Abstract
Global climate change has led to more frequent occurrences of extreme, dangerous events; therefore, it is urgent to enhance cities’ adaptation to climate change. Focusing on the impact of high temperature, low temperature, drought, and flooding, we established multi-dimensional assessment systems covering natural, economic, and social elements for cities’ climate change adaptations. Based on the assessment systems, studies on adaptation to climate change were conducted in 248 cities in China using the entropy weight method, coefficient of variation method, and exploratory spatial data analysis; with the help of geographically weighted regression (GWR), the relationships between four types of urbanization and cities’ adaptation to climate events were explored. The results showed the following: (1) High-administrative-level cities had higher adaptation than ordinary prefecture-level cities. (2) The differences in adaptation to the four types of climate events between cities within each of the seven regions in China presented significantly different spatial patterns. (3) Under the four types of climate events, the global spatial correlations of cities’ adaptations in China were positive. The agglomeration characteristics of adaptation were mainly H–H and L–L agglomerations. (4) When analyzing the impacts of four types of urbanization on cities’ adaptation to climate events, the fitting effects of GWR models were far better than those of OLS models. Population urbanization, economic urbanization, land urbanization, and industrial urbanization had different impacts on adaptation. Under the influence of social and economic development, the urbanization regression coefficients of different cities had significant spatial differences.
Funder
National Natural Science Foundation of China
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development
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