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We present an algorithm for estimating gross primary production (GPP) capacity based on chlorophyll indexes and light-response curves. Leaf chlorophyll content is a major determinant of GPP capacity. The initial slope of light-response curves and maximum GPP capacity under light saturation were determined using flux and Moderate Resolution Imaging Spectroradiometer (MODIS) data. The initial slope values were fixed for seven plant types. In a previous study, maximum GPP capacity under light saturation was determined based on the linear relationship between chlorophyll index-green CIgreen and GPP capacity at 2000 μmolm-2 s-1(GPPcapacity(2000)). In the relationship, vegetation was divided into three types: open shrubland, savannah, grassland, and cropland (rice paddy); deciduous and evergreen woody forest except for tropical evergreen forest; and tropical evergreen forest. Open shrublands and grasslands had higher slope values in the relation between CIgreen and GPPcapacity(2000) than deciduous and evergreen woody forest except for tropical evergreen forest. Global classification results in vegetation types may have errors, and the error may propagate to GPP capacity estimation when the estimation formula is not general in vegetation types. For estimating GPP capacity globally, generic formulae in different vegetation types is better to estimate GPP capacity. Peng et al. (2017) analyzed the relationship between canopy chlorophyll content and vegetation index for maize and soybean using hyperspectral radiometer data, and found that the relationships were the same among crops with different canopy structures under a CI of 740 nm, but not when CIgreen was used. We examined differences in GPP capacity estimations between CIgreen and the red-edge band chlorophyll index (CIred-edge) derived from flux and Sentinal-2/MSI sensor data. CIred-edge at 705 nm had a stronger relationship with GPPcapacity(2000) than did CIgreen.
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