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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

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

      摘要
    • 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。

       

      Abstract:
        Objective  Phenology is the rhythmic variation of vegetation development. It is a long adapting result to climatic and environmental changes. In this study, we investigated the relationships between MODIS NDVI, EVI, GOME-2 SIF and gross primary productivity (GPP) in order to explore the ability of reflecting dynamic variation of the vegetation. This study can provide some suggestions for deep understanding the reaction of the plantation to climatic changes.
        Method  The time series of NDVI, EVI, SIF and GPP from 2007 to 2011 were filtered using Timasat 3.3 software. Four types of index curves were fitted using double logistic functions and phenological parameters were extracted based on the maximum rate of change. Linear regression and root mean squared error (RMSE) between NDVI, EVI, SIF and GPP were used to compare the ability of reflecting the dynamic variations of the vegetation.
        Result  (1) The time series of MODIS NDVI, EVI and GOME-2 SIF were consistent with GPP. Monthly mean NDVI, EVI and SIF were positively correlated with monthly mean GPP from 2007 to 2011. (2) The determination coefficient (R2) values between monthly mean GPP and NDVI, EVI in spring and autumn were better than that between monthly mean SIF and GPP. However, GPP was strongly correlated with NDVI in summer. The relationships between GPP and EVI, SIF were not obvious. (3) RMSE between GPP-based phenological parameters and EVI-based phenological parameters was less than that between GPP and NDVI, SIF-based phenological parameters. The order of the RMSE value was EVI, NDVI and SIF.
        Conclusion  NDVI and EVI can better reflect the dynamic variation of the plantation in this site. The start of the growing season (SOS) extracted by MODIS NDVI and EVI advanced in comparison with the GPP-based SOS. The end of growing season (EOS) extracted by MODIS NDVI and EVI delayed in comparison with the GPP-based EOS. The main reason was that phenological information based on MODIS NDVI and EVI was extracted according to spectral characteristics of canopy structure and leaf reflectance. The SOS and EOS extracted by SIF advanced compared with the GPP-based SOS and EOS. The footprint of GOME-2 SIF mismatched with the footprint of flux tower GPP, thus impacting the relationship between SIF and GPP.

       

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