Evolution of land use/cover in a typical robustly developing medium-sized city and its impact on spatial and temporal changes of climatic factors: Wuxi City 1990–2020

Abstract Land use/cover change (LUCC) is recognized as one of the key drivers of global warming and extreme weather events. Most current articles on urban LUCC focus on megacities or regional urban clusters, while fewer studies have been conducted on medium-sized cities growing steadily and rapidly. Wuxi, the center of the Yangtze River Delta (YRD) region in China, has been experiencing rapid and sustained economic growth since 1981, with its per capita GDP approaching the level of moderately developed cities worldwide. By analyzing the characteristics of land use type, temperature, and precipitation in the sample of this typical rapidly urbanizing medium-sized city, we can reveal the quantitative relationship between the impacts of different land use cover types on the natural factors. It also provides new data and analytical perspectives to understand how land use/cover changes in urbanization affect climate change. Based on the remote sensing and meteorological data of Wuxi City from 1990 to 2020, we quantitatively calculate the single land use dynamic index, land use intensity index, and land use transfer matrix. In addition, we dynamically analyze the spatial and temporal trends of LUCC and natural factors by using the center of gravity model and standard deviation ellipse model to find out whether there is any correlation and consistency between them. Based on this, the gravity center model is combined with statistical methods to obtain the equilibrium equations composed of the center of gravity shifts of different land use types and natural factors, to clarify the quantitative influence of different land use types on the changes of various natural factors. The study shows that cultivated and construction land areas changed drastically from 1990 to 2020. The simulation results of the center of gravity model indicate that all types of land use correlate with climatic factors, and that water area has the greatest positive influence on precipitation. Grassland has the greatest positive influence on temperature.