京津冀地区NDVI变化及气候因子驱动分析

植被覆盖动态监测及与气候变化的响应,是陆地生态系统研究的重要内容。本文以2001-2013年间京津冀地区MOD13A 3月合成NDVI数据,结合生长季的降水和气温资料,运用偏相关和复相关分析、趋势分析方法,研究了该区域NDVI的变化特征和空间分布,以及其区域植被覆盖变化的气候驱动力。结果表明,该区域NDVI最大值在13a间缓慢增加,植被覆盖呈现改善趋势;NDVI和生长季降雨量及平均气温的平均偏相关系数分别为0.20和-0.14,表明在年际变化水平上,京津冀地区NDVI总体与降水量呈正相关,与平均气温呈负相关,且降水对NDVI的影响大于温度对NDVI的影响。对植被覆盖驱动分区得出,降水和气温驱动型占区域面积的5.68%;单独降水驱动型和气温驱动型分别占4.51%、0.18%;区域内植被覆盖变化主要受非气候因子驱动型为主,所占比例为89.63%,表明人类活动对植被变化的影响巨大。

Analysis of Spatial-Temporal Change of NDVI and Its Climatic Driving Factors in Beijing-Tianjin-Hebei Metropolis Circle from 2001 to 2013

Vegetation dynamics and their coupled relations with climate are current research hot spots in exploring how terrestrial ecosystems respond to climate systems. Beijing-Tianjin-Hebei Metropolis Circle, one of the three major economic circles located in the eastern part of China, has been experiencing a rapid development as well as a severe change in eco-environment. The analysis of NDVI’s (Normalized Difference Vegetation Index) spatial-temporal dynamics and the exploration of relevant key climatic driving factors have special significance in the research of ecological environment change in Beijing-Tianjin-Hebei Metropolis Circle. In order to explore the vegetation dynamics and the impact of climate change on vegetation cover in Beijing-Tianjin-Hebei Metropolis Circle from 2001 to 2013, we adopted NDVI data of MOD13A3 to study the trend and spatial pattern of this region using linear regression, with the assistance of precipitation and average temperature data from the growing season. The climatic driving forces of vegetation cover change were discussed using partial correlation analysis and multiple correlation analysis. The results indicate that NDVI had increased gradually during this period, which showed a good development trend for the vegetation cover in this region. The average partial correlation coefficients between NDVI and precipitation, and between NDVI and average temperature are 0.20 and -0.14 respectively, which indicate that NDVI is positively correlated with precipitation and negatively correlated with the average temperature during the growing season at the annual variation level. Furthermore, the impact of precipitation on NDVI is greater than temperature. Analysis of the driving factors on vegetation change shows that about 89.63% of the study area was impacted by non-climatic driving factor, while 5.68% was driven by a combined climatic factor of both precipitation and temperature, and 4.51% and 0.18% was driven by precipitation and temperature separately. As a result, it is evident to conclude that the vegetation change in this region is mainly affected by human activities.