Chin J Plant Ecol ›› 2012, Vol. 36 ›› Issue (6): 511-521.DOI: 10.3724/SP.J.1258.2012.00511

• Research Articles • Previous Articles     Next Articles

Normalized difference vegetation index dynamic change and its driving factor analysis with long time series in the Jinghe River watershed on the Loess Plateau of China

SUN Xiao-Peng, WANG Tian-Ming*(), KOU Xiao-Jun, GE Jian-Ping   

  1. State Key Laboratory of Earth Surface Processes and Resource Ecology and College of Life Sciences, Beijing Normal University, Beijing 100875, China
  • Received:2012-02-13 Accepted:2012-04-11 Online:2012-02-13 Published:2012-06-04
  • Contact: WANG Tian-Ming

Abstract:

Aims As a typical region of soil erosion on the Loess Plateau, the Jinghe River watershed has had long-term land exploitation and soil erosion. Our objective was to study trends in the change of vegetation cover and to explore driving factors, including both climatic and anthropogenic aspects.
Methods We calculated normalized difference vegetation index (NDVI) trends using GIMMS NDVI data from 1982 to 2005 in the Jinghe River watershed. Its trends were compared with precipitation and air temperature trends calculated from climate data from the 19 meteorological stations in the watershed. A 3 × 3 pixel buffer area centered on each station was used to analyze relationships between climate and vegetation. Anthropogenic factors were represented by land use data obtained from the Resource-Environment Database of the Chinese Academy of Sciences. We analyzed the proportion of each land type in areas of different NDVI trends to illustrate the effects of human activities.
Important findings NDVI had no significant trends in 79.64% of the Jinghe River watershed in the 24-year period. NDVI had significant positive trends in 16.33% of the area, located in the middle and southern parts of the watershed. NDVI had significant negative trends in 4.03% of the area, located in the northern part of the watershed. Precipitation had no significant trends, and temperature had significant positive trends forall of the 19 weather stations. The spatial differences of NDVI trends could not explained by changes in precipitation and air temperature. The anthropogenic factors seemed more important. Land use analysis indicated that the percentages of land use types in areas of different NDVI trends changed little. Plantation was dominant in the area where NDVI had significant positive trends, and grassland was dominant in the area where NDVI had significant negative trends. Results suggest that the changes in plantations resulted in the significant positive trends of NDVI, and woodland loss and grassland degeneration resulted in the significant negative trends of NDVI.

Key words: climate, land use, Jinghe River watershed, normalized difference vegetation index (NDVI), trend analysis, vegetation cover