Abstract

Beijing is among the first cities in China to implement a greenbelt policy to improve urban vegetation, which plays a crucial role in enhancing the urban ecological environment. The policies have shown remarkable results. However, long-term evaluation of the performance of the greenbelt policies in Beijing has not been carried out in order to quantitatively evaluate their effectiveness. In this study, long-term satellite observations of the normalized difference vegetation index (NDVI), land surface temperature, precipitation, and night-light from 2000 to 2020 are used to investigate the spatio-temporal variabilities in NDVI and explore the mechanisms of the impacts of the greenbelt policies in Beijing. The main results are as follows: (1) From 2000 to 2020, the overall NDVI in Beijing exhibited an upward trend, with the proportion of high-NDVI (>0.8) areas increasing from 26.18% in 2000 to 53.64% in 2020. The proportion of low-NDVI (<0.2) areas continued to decrease from 0.64% in 2000 to 0.2% in 2020. (2) The 1st Greenbelt Zone shows a significant increase in its NDVI (with an average increase of 0.296 units in the NDVI at district level), indicating that the policy’s implementation had a notable effect, while the 2nd Greenbelt Zone was mainly in a degraded state and a declining trend, indicating that its performance fell short of expectations. (3) During the preparation for the 2008 Summer Olympics, while the 1st Greenbelt Zone had a slightly negative effect on NDVI improvement, probably due to urban re-construction, the 2nd Greenbelt Zone showed a significant positive effect, leading to an increase of 0.013 units in the NDVI at district level. In addition, the correlation analysis shows that an increase in annual average land surface temperature leads to a decrease in the NDVI, while annual precipitation has a positive relationship with NDVI changes. This study highlights the importance of long-term satellite observations in evaluating the performance of greenbelt policies in Beijing. The evaluation approach developed in this study can be readily applied to similar cities globally.

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