Back to Search Start Over

Double Effect of Urbanization on Vegetation Growth in China’s 35 Cities during 2000–2020

Authors :
Lijuan Miao
Yu He
Giri Raj Kattel
Yi Shang
Qianfeng Wang
Xin Zhang
Source :
Remote Sensing, Vol 14, Iss 14, p 3312 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

In recent decades, the trade-off between urbanization and vegetation dynamics has broken the balance between human activities and social-economic dimensions. Our understanding towards the complex human–nature interactions, particularly the gradient of vegetation growth pattern across different city size, is still limited. Here, we selected 35 typical cities in China and classified them into five categories according to their resident population (e.g., megacities, megapolis, big cities, medium cities, and small cities). The spatial-temporal dynamics of vegetation growth for all 35 cities were inferred from the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI). We found that averaged NDVI for all cities slightly decreased during 2000 and 2020, at a rate of 1.6 × 10−4 per year. Most cities were characterized with relatively lower NDVI in urban areas than its surrounding area (determined by a series of buffer zones, i.e., 1–25 km outside of the city boundary). The percentage of greening pixels increased from urban area to the 25 km buffer zone at a rate of 4.7 × 10−4 per km. We noticed that negative impact of urbanization on vegetation growth reduced as the distance to urban area increased, with an exception for megacities (e.g., Shanghai, Beijing, and Shenzhen). In megacities and megapolis, greening pixels were more concentrated at core urban area, implying that the positive urbanization effect on vegetation growth is much more apparent. We argue that urbanization in China might facilitate vegetation growth to a certain extent, for which an appropriate urban planning such as purposeful selection of city sizes could be a scientific guidance while targeting the city’s sustainable development goals in future.

Details

Language :
English
ISSN :
20724292
Volume :
14
Issue :
14
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.0b41335fe81646d38611c909cccd2393
Document Type :
article
Full Text :
https://doi.org/10.3390/rs14143312