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国土资源遥感  2019, Vol. 31 Issue (2): 89-95    DOI: 10.6046/gtzyyg.2019.02.13
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
从NDVI序列检测植被“绿化”或“褐化”变化趋势的新方法
唐亮1,2,赵忠明2,唐娉2()
1.海南热带海洋学院,三亚 572022
2.中国科学院遥感与数字地球研究所,北京 100101
A new method for detection “greening” or “browning” change trend in vegetation from NDVI sequences
Liang TANG1,2,Zhongming ZHAO2,Ping TANG2()
1.Hainan Tropical Ocean University, Sanya 572022, China
2.Institute of Remote Sensing and Digital Earth Applications, Chinese Academy of Sciences, Beijing 100101, China
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摘要 

归一化植被指数(normalized difference vegetation index,NDVI)变化趋势可近似表达植被“绿化(greening)”或“褐化(browning)”的趋势,体现植被对全球变化的适应过程。提出一种将经验模态分解(empirical mode decomposition,EMD)和Mann-Kendall(MK)检验相结合的NDVI变化趋势分析方法,主要包括2步: 首先,采用EMD对NDVI时间序列进行分解,分解成若干本征模函数的叠加,这些本征模函数分量包含了原信号不同时间尺度的局部特征信号,第一个分量是高频分量,随后的分量频率逐渐减小,残差分量若是单调函数,即为趋势分量; 然后,利用MK检验方法对趋势分量进行单调性变化的显著性检验,得到NDVI“绿化”或“褐化”的趋势结果。对研究区2006—2015年间NDVI序列的趋势进行分析,结果表明该方法是一种有效的时间序列变化趋势分析方法。

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唐亮
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关键词 EMDMK显著性检验NDVI绿化褐化    
Abstract

Normalized difference vegetation index (NDVI) trends can approximate the trend of “greening” or “browning” of vegetation and reflect the adaptation process of vegetation to global change. In this paper, an NDVI trend analysis method combining empirical mode decomposition (EMD) and Mann-Kendall (MK) significance test is proposed on vegetation monotone trend detection. The method includes mainly two steps: firstly, EMD is used to decompose NDVI time series into a finite number of intrinsic mode functions (IMF), and these components contain the local characteristic information of different time scales of the original signal. The first component is a high-frequency component, the subsequent component frequency gradually decreases, and the residual is a monotonic function, indicating the average trend. From the decomposition, the NDVI variation trend along with time is extracted naturally. Secondly, the MK significance test is used to detect the monotonicity of the trend varied, that is, to detect that the trend is monotonically increasing or monotonically decreasing, the monotonically increasing is corresponding to the trend of vegetation getting “greening”, and the monotonically decreasing is corresponding to the trend of vegetation getting “browning”. The test data are MODIS NDVI time series of 16 days from 2006 to 2015. The analysis of the trend detection of those NDVI time series shows that the method proposed in this paper is an effective method for time series trend analysis and has a wide application prospect.

Key wordsEMD    MK significance test    NDVI    greening of vegetation    browning of vegetation
收稿日期: 2018-04-10      出版日期: 2019-05-23
ZTFLH:  TP701  
基金资助:校级引进学科带头人和博士研究生科研启动项目“基于经验模态分解的遥感图像时间序列渐变趋势检测和异常检测研究”(RHDXB201804);中国科学院一三五培育方向项目“空间数据密集型科学与大数据技术”共同资助
通讯作者: 唐娉     E-mail: tangping@radi.ac.cn
作者简介: 唐 亮(1971-),男,博士,主要从事遥感图像时间序列分析的理论和应用研究。Email: tyh9977@163.com。
引用本文:   
唐亮,赵忠明,唐娉. 从NDVI序列检测植被“绿化”或“褐化”变化趋势的新方法[J]. 国土资源遥感, 2019, 31(2): 89-95.
Liang TANG,Zhongming ZHAO,Ping TANG. A new method for detection “greening” or “browning” change trend in vegetation from NDVI sequences. Remote Sensing for Land & Resources, 2019, 31(2): 89-95.
链接本文:  
http://www.gtzyyg.com/CN/10.6046/gtzyyg.2019.02.13      或      http://www.gtzyyg.com/CN/Y2019/V31/I2/89
Fig.1  原始NDVI时间序列和上、下包络线及其均值
Fig.2  第1次迭代后的上、下包络线及其均值
Fig.3  第4次迭代后的上、下包络线及其均值
Fig.4  EMD方法分解结果
Fig.5  原始时间序列、RESimf6+RES曲线
Fig.6  3个样区的卫星影像、NDVI中值和NDVI趋势图
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