The rapid development of urbanization and population growth in China has posed a major threat to the green sustainable development of the ecological environment. However, the impact of urbanization on the eco-environmental quality (EEQ) in China remains to be developed. Understanding their interactive coupling mechanism is of great significance to achieve the urban sustainable development goals. By using multi-source remote sensing data and the coupling coordination degree model (CCDM), we intended to answer the question “What are the temporal and spatial characteristics of urbanization and EEQ in China on the pixel scale during 2000–2013, and what is the coupling mechanism between the urbanization and the EEQ?”. To answer these questions, we explored the coupling mechanism between urbanization and the EEQ in China with a combined mathematical and graphics model. The results show that the urbanization and the coupling coordination degree (CCD) of the whole region continually increased from 2000 to 2013, especially in the three major urban agglomerations, with a spatial distribution pattern that was “high in the east and low in the west”. Most importantly, from 2000 to 2013, the CCD type of cities in China gradually evolved from uncoordinated cities to coordinated cities. Additionally, the decisive factor affecting the CCD from 2000 to 2013 was the development of urbanization, and the degree at which urbanization had an impact on CCD was about 8.4 times larger than that of the EEQ. At the same time, the rapid urbanization that has occurred in some areas has led to a significant decline in the EEQ, thus indicating that China needs to increase its protection of the ecological environment while pursuing social and economic development in the future. This study makes up for the deficiencies in the existing literature and investigates the long-term coupling of the EEQ and urbanization in China, thereby providing a new research perspective for the sustainable development of China and even the world in the future.

Hainan Island is one of China’s most ecologically diverse areas. Human activities and climate change have recently influenced Hainan Island’s ecosystem services. Therefore, scientific methods are urgently needed to investigate the characteristics of these services’ spatial and temporal variations and their driving mechanisms for maintaining Hainan Island’s biodiversity and high-quality ecological conservation. Based on multivariate remote sensing and reanalysis data, this study analysed the spatial and temporal variations in water retention, soil conservation, carbon sequestration, and oxygen release services on Hainan Island during 1980–2015 using various ecosystem service models such as INVEST, CASA and RULSE. Then, we analysed different ecosystem service drivers using a random forest model. The results indicated that (1) from 1980 to 2015, the change characteristics of different ecosystem types (arable, forest, and grassland) decreased, and the proportion of decrease was 0.98%, 0.55% and 0.36%, respectively. Built-up and water increased significantly, and the proportion of increase reached 1.46% and 0.51%, respectively. (2) Hainan Island’s functions of water retention, soil conservation, carbon sequestration, and oxygen release services decreased from 23.31 billion m3, 2.89 billion t, 9.68 million t and 56.05 million t in 1980 to 23.15 billion m3, 2.79 billion t, 9.42 million t and 55.53 million t in 2015, respectively. The high value area was mainly distributed in Hainan Island’s central mountainous area, and the low value area was mainly distributed in the lower-elevation coastal area. (3) In the past 35 years, urban expansion has been the leading factor in the reduction of Hainan Island’s ecosystem service capacity. However, its central nature reserve and other forms of ecological protection have improved its ecosystem service capacity, which has alleviated the overall declining trend of its amount of ecosystem service functions. (4) The driving forces for the spatial distribution of Hainan Island’s ecosystem services were analysed using a random forest algorithm, which indicated that its spatial distribution was mainly driven by rainfall, soil moisture, actual evapotranspiration, maximum temperature, and minimum temperature. This study is expected to help planners develop effective environmental policies to accommodate the potential ecological risks associated with urban expansion during the construction of Hainan Island’s future free trade port while filling the gaps in existing studies.