《Scale consistency for investigating urbanization level, vegetation coverage, and their correlation》
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- 作者
- Man Wang;Jian Peng;Yi’na Hu;Yueyue Du;Sijing Qiu;Mingyue Zhao
- 来源
- URBAN FORESTRY & URBAN GREENING,Vol.59,Issue1,Article 126998
- 语言
- 英文
- 关键字
- Appropriate analysis scale;Scale effect;LAI;NTL;Pearl River Delta,;China
- 作者单位
- Original article"}]},{"#name":"title","$":{"id":"tit0005"},"_":"Scale consistency for investigating urbanization level, vegetation coverage, and their correlation"}],"floats":[],"footnotes":[],"attachments":[]},"vol-first":"59","vol-iss-suppl-text":"Volume 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- 摘要
- Accurate quantification of the relationship between urbanization level and vegetation coverage can provide scientific support for urban sustainable development. However, the interaction between them across multi-scales is under-researched because of its complexity. Based on climate change (i.e. precipitation, temperature and solar radiation), partial correlation relationship between urbanization level (nighttime light, NTL) and vegetation coverage (leaf area index, LAI) at different scales (1–20 km) in the Pearl River Delta (PRD) was explored. Mean local variance was used to determine the appropriate scale of the relationship, at which these metrics could have the minimum information missing. The consistency in appropriate analysis scales of NTL, LAI, and NTL-LAI, was quantified to identify which factor more influenced the appropriate analysis scale of NTL-LAI correlation. The results showed from 2000 to 2012, the urbanization level increased at the rate of 0.58/yr and the average LAI increased slowly at the rate of 0.02 m2/m2/yr. The partial correlation between NTL and LAI depicted that urbanization promoted vegetation coverage in the PRD. Meanwhile, the appropriate analysis scale of NTL-LAI correlation was more determined by the analysis scale of urbanization level, than that of vegetation coverage. This study revealed the scale effect of the relationship between urbanization level and vegetation coverage, and identified the determine factor of appropriate analysis scale of the relationship, which could help for the scale selection in related studies.