2016Unpublished venueRequires access

Analyzing the potential of different fractions of photosynthetically active radiation (FPARS) to estimate gross primary production

Zhengjia Liu, Chaoyang Wu, Shiguang Xu

Open publisher page 3 citations

Abstract

The fraction of photosynthetically active radiation (FPAR) as a key biophysical variable plays an important role in gross primary production (GPP) modeling. In this study, we employed six different FPAR derived from MODIS FPAR, leaf area index (LAI), normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), respectively, which were widely used for modeling GPP in previous studies. Flux GPP was collected from ChinaFLUX, covering four forest sites and four non-forest sites. Correlation analysis was used to evaluate the potential of different FPAR to model GPP. Our results showed that FPAR derived from EVI had the stronger correlation with flux GPP than MOD15 FPAR and FPAR derived from LAI, but FPAR derived from NDVI was not observed. This study highlights the potential of FPAR derived from EVI in GPP modeling.

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The fraction of photosynthetically active radiation (FPAR) as a key biophysical variable plays an important role in gross primary production (GPP) modeling. In this study, we employed six different FPAR derived from MODIS FPAR, leaf area index (LAI), normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), respectively, which were widely used for modeling GPP in previous studies. Flux GPP was collected from ChinaFLUX, covering four forest sites and four non-forest sites. Correlation analysis was used to evaluate the potential of different FPAR to model GPP. Our results showed that FPAR derived from EVI had the stronger correlation with flux GPP than MOD15 FPAR and FPAR derived from LAI, but FPAR derived from NDVI was not observed. This study highlights the potential of FPAR derived from EVI in GPP modeling.

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Available abstract

The fraction of photosynthetically active radiation (FPAR) as a key biophysical variable plays an important role in gross primary production (GPP) modeling. In this study, we employed six different FPAR derived from MODIS FPAR, leaf area index (LAI), normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), respectively, which were widely used for modeling GPP in previous studies. Flux GPP was collected from ChinaFLUX, covering four forest sites and four non-forest sites. Correlation analysis was used to evaluate the potential of different FPAR to model GPP. Our results showed that FPAR derived from EVI had the stronger correlation with flux GPP than MOD15 FPAR and FPAR derived from LAI, but FPAR derived from NDVI was not observed. This study highlights the potential of FPAR derived from EVI in GPP modeling.

Key concepts: Photosynthetically active radiation, Primary production, Normalized Difference Vegetation Index, Leaf area index, Environmental science, Enhanced vegetation index, Vegetation (pathology), Flux (metallurgy)

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