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Global warming has led to significant vegetation changes in recent years. It is necessary to investigate the effects of climatic variations(temperature and precipitation) on vegetation changes for a better understanding of acclimation to climatic change. In this paper, we focused on the integration and application of multi-methods and spatial analysis techniques in GIS to study the spatio-temporal variation of vegetation dynamics and to explore the vegetation change mechanism. The correlations between EVI and climate factors at different time scales were calculated for each pixel including monthly, seasonal and annual scales respectively in Qinghai Lake Basin from the year of 2001 to 2012. The primary objectives of this study are to reveal when, where and why the vegetation change so as to support better understanding of terrestrial response to global change as well as the useful information and techniques for wise regional ecosystem management practices. The main conclusions are as follows:(1) Overall vegetation EVI in the region increased 6% during recent 12 years. The EVI value in growing seasons(i.e. spring and summer) exhibited very significant improving trend, accounted for 12.8% and 9.3% respectively. The spatial pattern of EVI showed obvious spatial heterogeneity which was consistent with hydrothermal condition. In general, the vegetation coverage improved in most parts of the area since nearly 78% pixel of the whole basin showed increasing trend, while degraded slightly in a small part of the area only.(2) The EVI change was positively correlated with average temperature and precipitation. Generally speaking, in Qinghai Lake Basin, precipitation was the dominant driving factor for vegetation growth; however, at different time scale its weight to vegetation has differences.(3) Based on geo-statistical analysis, the autumn precipitation has a strong correlation with the next spring EVI values in the whole region. This findings explore the autumn precipitation is an important indicator, and then, limits the plant growth of next spring. 相似文献
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陕北风沙过渡带植被净初级生产力变化特征及原因 总被引：2，自引：2，他引：0
基于光能利用率原理,采用CASA（Carnegie-Ames-Stanford-Approach）模型,实现了2000—2014年陕北风沙过渡带地区植被净初级生产力（NPP）估算,对该地区NPP时空变化以及驱动机制进行了定量化分析。结果表明：（1） 2000—2014年陕北风沙过渡带NPP为6.71×1012gC·a-1,单位面积值为202.57gC·m-2·a-1,受地貌和气候特征影响,植被空间异质性强,黄土区植被明显优于风沙区;（2）近十几年来该区域植被得到明显改善,NPP总体增速为10.98gC·m-2·a-1（R=0.85,P<0.01）,植被增速存在空间差异,东南部的黄土区植被增长较快,西北风沙区植被增长较慢;（3）2000—2014年,降水、气温和辐射与NPP的相关系数分别为0.54（P<0.05）、-0.25、0.35,三者对植被增长的贡献量分别为3.95、0.71、2.75gC·m-2·a-1。这说明降水是气候因素中影响陕北风沙过渡带植被变化的主要因素;（4）近15年的植被恢复过程中,气候和人类活动都是重要的驱动因素,气候因子对植被增长的贡献更大,相对作用达到67.49%。区域内部,不同地区植被的主要驱动源存在差异,东部地区植被受气候因子主导,西部地区植被受人类活动主导。 相似文献
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