黄土高原泾河流域长时间序列的归一化植被指数动态变化及其驱动因素分析

泾河流域土地开发历史悠久, 是黄土高原水土流失的典型区域。研究气候变化和人类活动影响下泾河流域的植被覆盖变化及其原因, 对黄土高原的植被恢复、水土保持和景观管理等都具有重要意义。该研究应用GIMMS归一化植被指数NDVI、土地覆盖分类数据和气候数据, 采用趋势分析和相关分析方法, 研究了泾河流域1982-2005年植被覆盖变化趋势及其驱动因素。研究表明: 泾河流域24年间79.64%的区域NDVI无显著变化趋势, NDVI趋势显著增加的区域占16.33%, 主要集中在流域中部和南部, NDVI趋势显著减小的区域占4.03%, 主要集中在流域北部。流域所有气象站点的降水量均无显著变化趋势, 气温均呈显著升高趋势。分析发现气候变化不能很好地解释NDVI趋势的空间分异, 人为因素更为重要。从土地利用分析结果来看, NDVI不同趋势下各土地利用类型比例无明显变化, 但NDVI显著增加区以耕地为主, 显著减小区以草地为主, 由此推断NDVI的显著增加趋势主要由耕地NDVI增加引起, 显著减小趋势可能与林地减少和草地退化有关。通过分析不同分区的土地利用数据和社会经济资料, 着重探讨了造成植被覆盖显著变化趋势的人为因素。

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

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.