应用科学学报 ›› 2015, Vol. 33 ›› Issue (1): 59-69.doi: 10.3969/j.issn.0255-8297.2015.01.007

• 信号与信息处理 • 上一篇    下一篇

19982012 年艾比湖流域NDVI 变化及其气候因子驱动分析

  

  1. 武汉大学遥感信息工程学院,武汉430079
  • 收稿日期:2014-06-05 修回日期:2014-09-10 出版日期:2015-01-30 发布日期:2014-09-18
  • 通信作者: 周军其,博士,副教授,研究方向:遥感图像处理,E-mail: junqi_zhou@163.com

Analysis of NDVI Changes and Its Climate Factor Drivers in Ebinur Lake Basin from 1998 to 2012

  1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
  • Received:2014-06-05 Revised:2014-09-10 Online:2015-01-30 Published:2014-09-18

摘要: 为探究艾比湖流域气候变化对植被覆盖的影响,基于19982012 年艾比湖流域SPOT VEGETATION 数据集,运用最大化合成法及一元线性回归研究其间15 年来流域内归一化差分植被指数(normalized difference vegetation index, NDVI)的变化趋势及空间布局,并结合该地区同期降水量和温度数据,利用偏相关分析和复相关分析对研究区域植被覆盖变化的气候驱动力进行了分析与探讨. 结果表明,流域内NDVI 在15 年间显著性增长,植被呈现出较好的发展趋势,自然因素中降水量对植被的影响在力度和范围上均大于温度对植被的影响. 流域内植被覆盖变化主要以非气候因子驱动型为主,所占比例为88.9%,基本覆盖整个流域,而受气候影响的区域占整个流域面积的11.1%,主要呈片状分布于流域东部.

关键词: 归一化差分植被指数, 艾比湖流域, 气候因子, 偏相关分析, 复相关分析

Abstract: To explore the impact of climate change on vegetation cover in Ebinur Lake Basin, we apply the data set SPOT VEGETATION to study the trend of normalized difference vegetation index (NDVI) and spatial pattern in this area, using a maximum synthesis and linear regression method. Combining the annual precipitation and annual average temperature in the same period, the vegetation cover driving force of climate change is discussed through partial correlation and multiple correlation analyses. The results indicate that NDVI increases significantly, showing a good development trend. Among various natural factors, precipitation has a deeper and more widespread effect on vegetation than temperature during 15 years in Ebinur Lake Basin. In addition, about 88.9% of the studyarea is impacted by non-climate factor drivers, while 11.1% is driven by climate factors and mainly distributes in the eastern basin.
 

Key words: normalized difference vegetation index (NDVI), Ebinur Lake Basin, climate factors, partial correlation analysis, multiple correlation analysis

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