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Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods

DU Huishi,  JIANG Hailing,  ZHANG Lifu,  MAO Dehua,  WANG Zongming

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文章导航 > Chinese Geographical Science  > 2016 >  26(6): 731-744
DU Huishi, JIANG Hailing, ZHANG Lifu, MAO Dehua, WANG Zongming. Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods[J]. 中国地理科学, 2016, 26(6): 731-744. doi: 10.1007/s11769-016-0833-y
引用本文: DU Huishi, JIANG Hailing, ZHANG Lifu, MAO Dehua, WANG Zongming. Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods[J]. 中国地理科学, 2016, 26(6): 731-744. doi: 10.1007/s11769-016-0833-y
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DU Huishi, JIANG Hailing, ZHANG Lifu, MAO Dehua, WANG Zongming. Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods[J]. Chinese Geographical Science, 2016, 26(6): 731-744. doi: 10.1007/s11769-016-0833-y
Citation: DU Huishi, JIANG Hailing, ZHANG Lifu, MAO Dehua, WANG Zongming. Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods[J]. Chinese Geographical Science, 2016, 26(6): 731-744. doi: 10.1007/s11769-016-0833-y
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Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods

doi: 10.1007/s11769-016-0833-y
  • 1.

    Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;

  • 2.

    College of Tourism and Geographical Science, Jilin Normal University, Siping 136000, China;

  • 3.

    Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

基金项目: Under the auspices of National Natural Science Foundation of China (No.41401002), Jilin Province Science Foundation for Youths (No. 20160520077JH)
详细信息
    通讯作者:

    WANG Zongming.E-mail:zongmingwang@iga.ac.cn

Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods

  • 1.

    Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;

  • 2.

    College of Tourism and Geographical Science, Jilin Normal University, Siping 136000, China;

  • 3.

    Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

Funds: Under the auspices of National Natural Science Foundation of China (No.41401002), Jilin Province Science Foundation for Youths (No. 20160520077JH)
More Information
    Corresponding author: WANG Zongming.E-mail:zongmingwang@iga.ac.cn

  • 摘要: Spectral index methodology has been widely used in Leaf Area Index (LAI) retrieval at different spatial scales. There are differences in the spectral response of different remote sensors and thus spectral scale effect generated during the use of spectral indices to retrieve LAI. In this study, PROSPECT, leaf optical properties model and Scattering by Arbitrarily Inclined Layers (SAIL) model, were used to simulate canopy spectral reflectance with a bandwidth of 5 nm and a Gaussian spectral response function was employed to simulate the spectral data at six bandwidths ranging from 10 to 35 nm. Additionally, for bandwidths from 5 to 35 nm, the correlation between the spectral index and LAI, and the sensitivities of the spectral index to changes in LAI and bandwidth were analyzed. Finally, the reflectance data at six bandwidths ranging from 40 to 65 nm were used to verify the spectral scale effect generated during the use of the spectral index to retrieve LAI. Results indicate that Vegetation Index of the Universal Pattern Decomposition (VIUPD) had the highest accuracy during LAI retrieval. Followed by Normalized Difference Vegetation Index (NDVI), Modified Simple Ratio Indices (MSRI) and Triangle Vegetation Index (TVI), although the coefficient of determination R2 was higher than 0.96, the retrieved LAI values were less than the actual value and thus lacked validity. Other spectral indices were significantly affected by the spectral scale effect with poor retrieval results. In this study, VIUPD, which exhibited a relatively good correlation and sensitivity to LAI, was less affected by the spectral scale effect and had a relatively good retrieval capability. This conclusion supports a purported feature independent of the sensor of this model and also confirms the great potential of VIUPD for retrieval of physicochemical parameters of vegetation using multi-source remote sensing data.
    Abstract: Spectral index methodology has been widely used in Leaf Area Index (LAI) retrieval at different spatial scales. There are differences in the spectral response of different remote sensors and thus spectral scale effect generated during the use of spectral indices to retrieve LAI. In this study, PROSPECT, leaf optical properties model and Scattering by Arbitrarily Inclined Layers (SAIL) model, were used to simulate canopy spectral reflectance with a bandwidth of 5 nm and a Gaussian spectral response function was employed to simulate the spectral data at six bandwidths ranging from 10 to 35 nm. Additionally, for bandwidths from 5 to 35 nm, the correlation between the spectral index and LAI, and the sensitivities of the spectral index to changes in LAI and bandwidth were analyzed. Finally, the reflectance data at six bandwidths ranging from 40 to 65 nm were used to verify the spectral scale effect generated during the use of the spectral index to retrieve LAI. Results indicate that Vegetation Index of the Universal Pattern Decomposition (VIUPD) had the highest accuracy during LAI retrieval. Followed by Normalized Difference Vegetation Index (NDVI), Modified Simple Ratio Indices (MSRI) and Triangle Vegetation Index (TVI), although the coefficient of determination R2 was higher than 0.96, the retrieved LAI values were less than the actual value and thus lacked validity. Other spectral indices were significantly affected by the spectral scale effect with poor retrieval results. In this study, VIUPD, which exhibited a relatively good correlation and sensitivity to LAI, was less affected by the spectral scale effect and had a relatively good retrieval capability. This conclusion supports a purported feature independent of the sensor of this model and also confirms the great potential of VIUPD for retrieval of physicochemical parameters of vegetation using multi-source remote sensing data.
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出版历程
  • 收稿日期:  2016-05-05
  • 修回日期:  2016-09-01
  • 刊出日期:  2016-12-27

Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods

doi: 10.1007/s11769-016-0833-y
  • 1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;
  • 2. College of Tourism and Geographical Science, Jilin Normal University, Siping 136000, China;
  • 3. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
    • 基金项目:  Under the auspices of National Natural Science Foundation of China (No.41401002), Jilin Province Science Foundation for Youths (No. 20160520077JH)
    通讯作者: WANG Zongming.E-mail:zongmingwang@iga.ac.cn
  • 收稿日期: 2016-05-05
  • 修回日期: 2016-09-01
  • 刊出日期: 2016-12-27

摘要: Spectral index methodology has been widely used in Leaf Area Index (LAI) retrieval at different spatial scales. There are differences in the spectral response of different remote sensors and thus spectral scale effect generated during the use of spectral indices to retrieve LAI. In this study, PROSPECT, leaf optical properties model and Scattering by Arbitrarily Inclined Layers (SAIL) model, were used to simulate canopy spectral reflectance with a bandwidth of 5 nm and a Gaussian spectral response function was employed to simulate the spectral data at six bandwidths ranging from 10 to 35 nm. Additionally, for bandwidths from 5 to 35 nm, the correlation between the spectral index and LAI, and the sensitivities of the spectral index to changes in LAI and bandwidth were analyzed. Finally, the reflectance data at six bandwidths ranging from 40 to 65 nm were used to verify the spectral scale effect generated during the use of the spectral index to retrieve LAI. Results indicate that Vegetation Index of the Universal Pattern Decomposition (VIUPD) had the highest accuracy during LAI retrieval. Followed by Normalized Difference Vegetation Index (NDVI), Modified Simple Ratio Indices (MSRI) and Triangle Vegetation Index (TVI), although the coefficient of determination R2 was higher than 0.96, the retrieved LAI values were less than the actual value and thus lacked validity. Other spectral indices were significantly affected by the spectral scale effect with poor retrieval results. In this study, VIUPD, which exhibited a relatively good correlation and sensitivity to LAI, was less affected by the spectral scale effect and had a relatively good retrieval capability. This conclusion supports a purported feature independent of the sensor of this model and also confirms the great potential of VIUPD for retrieval of physicochemical parameters of vegetation using multi-source remote sensing data.

English Abstract

DU Huishi, JIANG Hailing, ZHANG Lifu, MAO Dehua, WANG Zongming. Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods[J]. 中国地理科学, 2016, 26(6): 731-744. doi: 10.1007/s11769-016-0833-y
引用本文: DU Huishi, JIANG Hailing, ZHANG Lifu, MAO Dehua, WANG Zongming. Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods[J]. 中国地理科学, 2016, 26(6): 731-744. doi: 10.1007/s11769-016-0833-y
shu
DU Huishi, JIANG Hailing, ZHANG Lifu, MAO Dehua, WANG Zongming. Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods[J]. Chinese Geographical Science, 2016, 26(6): 731-744. doi: 10.1007/s11769-016-0833-y
Citation: DU Huishi, JIANG Hailing, ZHANG Lifu, MAO Dehua, WANG Zongming. Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods[J]. Chinese Geographical Science, 2016, 26(6): 731-744. doi: 10.1007/s11769-016-0833-y
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