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Spatial and temporal changes of vegetation net primary productivity and its relation with climatic factors in Guangxi, China
Author(s): Juan Li Jing; Yong Feng Wang
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Paper Abstract

MOD17A3 NPP datasets from 2000-2010 and meteorological data were used to quantitatively analyze the spatial and temporal variations of vegetation NPP and its correlation with meteorological factors by using linear regression and correlation analysis methods in Guangxi. Results show: (1) the annual NPP ranged from 626 to 715 g C·m-2·a-1, with an average of 663 g C·m-2·a-1. The average annual vegetation NPP was higher in the west and east while lower in the middle and north part of the study area. The highest NPP (> 900 g C·m-2·a-1) mainly distributed in Baise, Chongzuo, Fangchenggang and Wuzhou. While the lowest NPP (<450 g C·m-2·a-1) mainly located in cities of Guigang and Hezhou. (2) In recent 11 years, the linear changing trend of NPP in Guangxi was decreased slowly. The regions of NPP with no significant difference (P>0.05), increased significantly (P<0.05) and decreased significantly (P<0.05) were respectively about 93.15%, 0.80% and 6.05% of the total study area. The area with an annual NPP decreased rate lower than -10% occupied 26.96% of the total study area, and the area with more than 10% NPP increment was 8.37%, and an unchanged area (NPP variation from -10% to 10%) accounted for 64.68%. (3) At the annual time scale, the correlations between vegetation NPP and temperature/precipitation were spatially various in Guangxi. The correlation of vegetation NPP with temperature was positive in 58.41% of the total area, and negative in the rest 41.59%, while its correlation with precipitation was positive in 38.16% of the study area, and negative for the other 61.84%. The above analysis indicated that temperature affecting vegetation growth more remarkable than precipitation.

Paper Details

Date Published: 9 December 2015
PDF: 9 pages
Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 98080N (9 December 2015); doi: 10.1117/12.2207372
Show Author Affiliations
Juan Li Jing, Guilin Univ. of Technology (China)
Yong Feng Wang, Guilin Univ. of Technology (China)

Published in SPIE Proceedings Vol. 9808:
International Conference on Intelligent Earth Observing and Applications 2015
Guoqing Zhou; Chuanli Kang, Editor(s)

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