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基于植被指数、叶绿素荧光和碳通量的华北山地人工林物候对比研究

张静茹 同小娟 孟平 张劲松 刘沛荣

张静茹, 同小娟, 孟平, 张劲松, 刘沛荣. 基于植被指数、叶绿素荧光和碳通量的华北山地人工林物候对比研究[J]. 北京林业大学学报, 2020, 42(11): 17-26. doi: 10.12171/j.1000-1522.20200113
引用本文: 张静茹, 同小娟, 孟平, 张劲松, 刘沛荣. 基于植被指数、叶绿素荧光和碳通量的华北山地人工林物候对比研究[J]. 北京林业大学学报, 2020, 42(11): 17-26. doi: 10.12171/j.1000-1522.20200113
Zhang Jingru, Tong Xiaojuan, Meng Ping, Zhang Jinsong, Liu Peirong. Comparative study on phenology in a mountainous plantation in northern China based on vegetation index, chlorophyll fluorescence and carbon flux[J]. Journal of Beijing Forestry University, 2020, 42(11): 17-26. doi: 10.12171/j.1000-1522.20200113
Citation: Zhang Jingru, Tong Xiaojuan, Meng Ping, Zhang Jinsong, Liu Peirong. Comparative study on phenology in a mountainous plantation in northern China based on vegetation index, chlorophyll fluorescence and carbon flux[J]. Journal of Beijing Forestry University, 2020, 42(11): 17-26. doi: 10.12171/j.1000-1522.20200113

基于植被指数、叶绿素荧光和碳通量的华北山地人工林物候对比研究

doi: 10.12171/j.1000-1522.20200113
基金项目: 国家自然科学基金项目(31872703、31570617)
详细信息
    作者简介:

    张静茹。主要研究方向:植被遥感。Email:jrzhang1994@163.com 地址:100083 北京市海淀区清华东路35号北京林业大学生态与自然保护学院

    责任作者:

    同小娟,教授,博士生导师。主要研究方向:气候变化与生态过程。Email:tongxj@bjfu.edu.cn 地址:同上

  • 中图分类号: S771.8;S718.55+6

Comparative study on phenology in a mountainous plantation in northern China based on vegetation index, chlorophyll fluorescence and carbon flux

  • 摘要:   目的  物候指植被生长发育的节律性变化,是对气候和环境变化长期适应的结果。本文通过研究植被指数(NDVI、EVI)和日光诱导叶绿素荧光(SIF)与总初级生产力(GPP)之间关系,探究各指数在研究区反映植被动态变化的能力,为深入了解人工林对气候变化的响应提供参考。  方法  利用Timesat 3.3软件对2007—2011年MODIS NDVI、EVI、GOME-2 SIF、通量塔GPP数据分别进行滤波。采用双逻辑斯蒂方程对4种指数时间序列进行拟合并根据曲线最大变化速率提取生长季开始期(SOS)和生长季结束期(EOS)。利用相关性分析、均方根误差分析研究NDVI、EVI、SIF反映植被动态特征的能力。  结果  (1)2007—2011年MODIS NDVI、EVI、GOME-2 SIF、通量塔GPP这4种时间序列曲线变化特征基本一致,NDVI、EVI、SIF月均值均与GPP月均值呈现显著正相关关系。(2)GPP月均值与NDVI、EVI之间决定系数R2在春季、秋季均大于SIF。然而,在夏季GPP月均值与NDVI呈现显著相关性,与EVI和SIF并无明显线性关系。(3)NDVI、EVI、SIF与GPP提取物候参数的均方根误差结果显示:利用EVI提取物候参数结果与GPP最为接近,其次为NDVI,最后为SIF。  结论  在本研究区内,MODIS NDVI、EVI能够更好地反映植被动态变化特征。由于NDVI、EVI数据是依据植被冠层结构光谱特性和叶片反射率提取的物候信息,因此会导致植被指数(NDVI、EVI)提取物候期比GPP提取物候开始期提前和物候结束期滞后。利用SIF数据提取物候参数SOS和EOS均提前于GPP数据提取物候参数S0S和EOS。SIF数据由于像元覆盖面积与通量塔GPP数据不完全吻合影响了GPP与SIF之间的相关关系。

     

  • 图  1  物候参数提取方法

    Figure  1.  Extracted methods of phenological parameters

    图  2  2007–2011年GPP和SIF日时间序列曲线(a)、NDVI和EVI日时间序列曲线(b)和月平均温度和月降水量变化图(c)

    Figure  2.  Seasonal variations of daily GPP and SIF time series (a), seasonal variations of daily NDVI and EVI time series (b) and monthly variations of mean temperature and precipitation (c) from 2007 to 2011

    图  3  GPP和SIF(a)、NDVI和EVI(b)、以及平均温度和降水量(c)的月变化(2007—2011)

    Figure  3.  Monthly variations of 5-year mean GPP and SIF time series (a), monthly variations of 5-year mean NDVI and EVI time series (b) and monthly variations of 5-year mean temperature and precipitation (c) (2007−2011)

    图  4  2007—2011年NDVI、EVI、SIF月均值与GPP月均值之间的关系

    Figure  4.  Relationships between monthly mean GPP and NDVI, EVI, SIF from 2007 to 2011

    图  5  2007—2011年NDVI、EVI、SIF与GPP不同季节月均值之间的关系

    Figure  5.  Relationships between monthly mean GPP and NDVI, EVI, SIF in different seasons from 2007 to 2011

    图  6  NDVI、EVI、SIF提取物候参数与GPP提取物候参数之间均方根误差

    Figure  6.  RMSE between phenological parameters extracted by GPP and those extracted by NDVI, EVI and SIF

    表  1  GPP、NDVI、EVI、SIF物候参数结果对比

    Table  1.   Comparison of phenological parameters of GPP, NDVI, EVI and SIF d

    年份 YearGPPEVINDVISIF
    SOSEOSLOSSOSEOSLOSSOSEOSLOSSOSEOSLOS
    2007 90 302 212 84 311 227 81 324 243 82 287 205
    2008 95 301 206 82 321 239 79 326 247 68 300 232
    2009 78 311 233 78 321 243 79 331 252 84 270 186
    2010 97 311 214 93 310 217 92 319 227 82 279 197
    2011 94 318 224 94 316 222 91 325 234 86 291 205
    均值±标准差 Mean±SD 91 ± 7 309 ± 6 218 ± 10 86 ± 6 316 ± 5 230 ± 10 84 ± 6 325 ± 4 241 ± 9 80 ± 6 285 ± 10 205 ± 15
    注:SOS. 生长季开始期;EOS. 生长季结束期;LOS. 生长季长度。Notes: SOS, the start of growing season; EOS, the end of growing season; LOS, the length of growing season.
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  • 收稿日期:  2020-04-23
  • 修回日期:  2020-05-11
  • 网络出版日期:  2020-11-12
  • 刊出日期:  2020-12-14

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