Application conditions and impact factors for various vegetation indices in constructing the LAI seasonal trajectory over different vegetation types
•Application conditions for VIs in constructing the LAI seasonal trajectory were assessed.•The optimal VI for different ranges of LAI is suggested for LAI estimation.•The VIRE have the potential to develop a universe model for estimating LAI. Leaf area index (LAI) is a required input for various eco...
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Published in | Ecological indicators Vol. 112; p. 106153 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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01.05.2020
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Abstract | •Application conditions for VIs in constructing the LAI seasonal trajectory were assessed.•The optimal VI for different ranges of LAI is suggested for LAI estimation.•The VIRE have the potential to develop a universe model for estimating LAI.
Leaf area index (LAI) is a required input for various ecological and crop models. To investigate the application conditions of various vegetation indices (VIs), especially the VIs constructed by red-edge band (VIRE) for estimating LAI, six VIs derived from Medium Resolution Imaging Spectrometer (MERIS) data were used to construct LAI seasonal trajectory for different vegetation types at 15 sites. The PROSAIL model combined with the Extended Fourier Amplitude Sensitivity Test (EFAST) method was adopted to explore the influences and physical basis of canopy biophysical and non-canopy variables on the construction of LAI seasonal trajectory using VIs. For deciduous forests, the normalized difference vegetation index (NDVI) had the highest sensitivity to LAI when LAI < 2, while the RE normalized difference vegetation index (NDVIRE) had the highest sensitivity when LAI > 2. For evergreen forests, there were no obvious differences among the sensitivities of six VIs to LAI when LAI < 5, while the RE chlorophyll index (CIRE) had the highest sensitivities when LAI > 5. For crops, all the VIs had the similar sensitivities at LAI < 3, while the CIRE and MERIS terrestrial chlorophyll index (MTCI) were most sensitive to LAI variations at LAI > 3. For all three types of vegetation, the VIRE maintained relatively high sensitivity to LAI over the whole range of LAI, especially at high LAI values. The VIs were most affected by chlorophyll content (Cab) and average leaf inclination angle (ALA); their total contribution was about 85%. However, the influence of ALA on VIRE was relatively weak, implying that the VIRE had the potential to establish a universal model for LAI estimation among different vegetation types. Therefore, the optimal VIs over different ranges of LAI were suggested to estimate LAI. In addition, the VIRE should be a preferred choice for estimating LAI to reduce the simulation errors of seasonal LAI, if the RE band is available. |
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AbstractList | •Application conditions for VIs in constructing the LAI seasonal trajectory were assessed.•The optimal VI for different ranges of LAI is suggested for LAI estimation.•The VIRE have the potential to develop a universe model for estimating LAI.
Leaf area index (LAI) is a required input for various ecological and crop models. To investigate the application conditions of various vegetation indices (VIs), especially the VIs constructed by red-edge band (VIRE) for estimating LAI, six VIs derived from Medium Resolution Imaging Spectrometer (MERIS) data were used to construct LAI seasonal trajectory for different vegetation types at 15 sites. The PROSAIL model combined with the Extended Fourier Amplitude Sensitivity Test (EFAST) method was adopted to explore the influences and physical basis of canopy biophysical and non-canopy variables on the construction of LAI seasonal trajectory using VIs. For deciduous forests, the normalized difference vegetation index (NDVI) had the highest sensitivity to LAI when LAI < 2, while the RE normalized difference vegetation index (NDVIRE) had the highest sensitivity when LAI > 2. For evergreen forests, there were no obvious differences among the sensitivities of six VIs to LAI when LAI < 5, while the RE chlorophyll index (CIRE) had the highest sensitivities when LAI > 5. For crops, all the VIs had the similar sensitivities at LAI < 3, while the CIRE and MERIS terrestrial chlorophyll index (MTCI) were most sensitive to LAI variations at LAI > 3. For all three types of vegetation, the VIRE maintained relatively high sensitivity to LAI over the whole range of LAI, especially at high LAI values. The VIs were most affected by chlorophyll content (Cab) and average leaf inclination angle (ALA); their total contribution was about 85%. However, the influence of ALA on VIRE was relatively weak, implying that the VIRE had the potential to establish a universal model for LAI estimation among different vegetation types. Therefore, the optimal VIs over different ranges of LAI were suggested to estimate LAI. In addition, the VIRE should be a preferred choice for estimating LAI to reduce the simulation errors of seasonal LAI, if the RE band is available. Leaf area index (LAI) is a required input for various ecological and crop models. To investigate the application conditions of various vegetation indices (VIs), especially the VIs constructed by red-edge band (VIRE) for estimating LAI, six VIs derived from Medium Resolution Imaging Spectrometer (MERIS) data were used to construct LAI seasonal trajectory for different vegetation types at 15 sites. The PROSAIL model combined with the Extended Fourier Amplitude Sensitivity Test (EFAST) method was adopted to explore the influences and physical basis of canopy biophysical and non-canopy variables on the construction of LAI seasonal trajectory using VIs. For deciduous forests, the normalized difference vegetation index (NDVI) had the highest sensitivity to LAI when LAI < 2, while the RE normalized difference vegetation index (NDVIRE) had the highest sensitivity when LAI > 2. For evergreen forests, there were no obvious differences among the sensitivities of six VIs to LAI when LAI < 5, while the RE chlorophyll index (CIRE) had the highest sensitivities when LAI > 5. For crops, all the VIs had the similar sensitivities at LAI < 3, while the CIRE and MERIS terrestrial chlorophyll index (MTCI) were most sensitive to LAI variations at LAI > 3. For all three types of vegetation, the VIRE maintained relatively high sensitivity to LAI over the whole range of LAI, especially at high LAI values. The VIs were most affected by chlorophyll content (Cab) and average leaf inclination angle (ALA); their total contribution was about 85%. However, the influence of ALA on VIRE was relatively weak, implying that the VIRE had the potential to establish a universal model for LAI estimation among different vegetation types. Therefore, the optimal VIs over different ranges of LAI were suggested to estimate LAI. In addition, the VIRE should be a preferred choice for estimating LAI to reduce the simulation errors of seasonal LAI, if the RE band is available. |
ArticleNumber | 106153 |
Author | Xie, Zhiying Zhu, Wenquan Qiao, Kun |
Author_xml | – sequence: 1 givenname: Kun surname: Qiao fullname: Qiao, Kun organization: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China – sequence: 2 givenname: Wenquan surname: Zhu fullname: Zhu, Wenquan email: zhuwq75@bnu.edu.cn organization: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China – sequence: 3 givenname: Zhiying surname: Xie fullname: Xie, Zhiying organization: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China |
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Keywords | Global sensitivity analysis Red-edge Vegetation types Whole growing season Vegetation indices Leaf area index |
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Snippet | •Application conditions for VIs in constructing the LAI seasonal trajectory were assessed.•The optimal VI for different ranges of LAI is suggested for LAI... Leaf area index (LAI) is a required input for various ecological and crop models. To investigate the application conditions of various vegetation indices... |
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SubjectTerms | canopy chlorophyll Global sensitivity analysis leaf angle Leaf area index normalized difference vegetation index Red-edge spectrometers Vegetation indices Vegetation types Whole growing season |
Title | Application conditions and impact factors for various vegetation indices in constructing the LAI seasonal trajectory over different vegetation types |
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