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Proceedings Paper

Analysis of acid rain effects on vegetation in eco-regions in China based on AVHRR/NDVI
Author(s): Jiaxin Jin; Hong Jiang; Xiuying Zhang; Xiaobin Xu
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Paper Abstract

The vegetation, as the main component of the ecosystems, is the main receptor of acid rain pollution. Because of the discrepancy of the vegetation characteristics and environment, the responses of the different types of vegetation to acid rain in different regions are different. In this paper, we chose 9 eco-regions in southern China as study area, based on the acid rain and NOAA/NDVI data from 1992 to 2006, and revealed the impact of acid rain on the vegetation by using spatial interpolation, cluster analysis and curve fitting. The result shows that the most tropical and subtropical moist broadleaf forests were positively correlated with the acidity of precipitation and the growth was inhibited obviously. On the contrary, the growth of temperate coniferous forests was promoted by acid rain to some extent. In generally, the vegetation in the condition of the weak acid rain grew better, especially the Qin Ling Mountains deciduous forests and the Changjiang Plain evergreen forests. For South China-Vietnam subtropical evergreen forest, Yunnan Plateau subtropical evergreen forests and Qionglai-Minshan conifer forests, the significant difference of NDVI between the different gradients of acid rain lasted almost the whole year, while that of the other eco-regions only appeared most obviously in Winter.

Paper Details

Date Published: 15 August 2011
PDF: 8 pages
Proc. SPIE 8203, Remote Sensing of the Environment: The 17th China Conference on Remote Sensing, 82030Z (15 August 2011); doi: 10.1117/12.910415
Show Author Affiliations
Jiaxin Jin, Nanjing Univ. (China)
Hong Jiang, Nanjing Univ. (China)
Zhejiang Agriculture and Forestry Univ. (China)
Xiuying Zhang, Nanjing Univ. (China)
Xiaobin Xu, China Meteorological Administration (China)


Published in SPIE Proceedings Vol. 8203:
Remote Sensing of the Environment: The 17th China Conference on Remote Sensing
Qingxi Tong; Xingfa Gu; Boqin Zhu, Editor(s)

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