Abstract
To estimate global gross primary production (GPP), which is an important parameter for studies of vegetation productivity and the carbon cycle, satellite data are useful. In 2014, the Japan Aerospace Exploration Agency (JAXA) plans to launch the Global Change Observation Mission-Climate (GCOM-C) satellite carrying the second-generation global imager (SGLI). The data obtained will be used to estimate global GPP. The rate of photosynthesis depends on photosynthesis reduction and photosynthetic capacity, which is the maximum photosynthetic velocity at light saturation under adequate environmental conditions. Photosynthesis reduction is influenced by weather conditions, and photosynthetic capacity is influenced by chlorophyll and RuBisCo content. To develop the GPP estimation algorithm, we focus on photosynthetic capacity because chlorophyll content can be detected by optical sensors. We hypothesized that the maximum rate of low-stress GPP (called “GPP capacity”) is mainly dependent on the chlorophyll content that can be detected by a vegetation index (VI). The objective of this study was to select an appropriate VI with which to estimate global GPP capacity with the GCOM-C/SGLI. We analyzed reflectance data to select the VI that has the best linear correlation with chlorophyll content at the leaf scale and with GPP capacity at canopy and satellite scales. At the satellite scale, flux data of seven dominant plant functional types and reflectance data obtained by the Moderate-resolution Imaging Spectroradiometer (MODIS) were used because SGLI data were not available. The results indicated that the green chlorophyll index, CIgreen(ρNIR/ρgreen-1), had a strong linear correlation with chlorophyll content at the leaf scale (R2 = 0.87, p < 0.001) and with GPP capacity at the canopy (R2 = 0.78, p < 0.001) and satellite scales (R2 = 0.72, p < 0.01). Therefore, CIgreen is a robust and suitable vegetation index for estimating global GPP capacity.
Highlights
Terrestrial ecosystems are major sinks in the global carbon cycle, sequestering carbon and slowing the increase in CO2 concentration in the atmosphere [1]
To determine Pmax_capacity and αslope, the relationships between GPPcapacity and PAR were examined for broadleaf deciduous temperate trees at JP-TKY in 2003 and 2004, as shown in Figure 6, which illustrates the light-response curve of GPPcapacity
The results show that CIgreen has a strong correlation with variation in leaf chlorophyll content from a wide range of species and leaf development stages (Figure 4)
Summary
Terrestrial ecosystems are major sinks in the global carbon cycle, sequestering carbon and slowing the increase in CO2 concentration in the atmosphere [1]. The amount of carbon removed from the atmosphere by vegetation via photosynthesis is the gross primary production (GPP). Highly accurate estimation of GPP is important, and satellite remote sensing offers an efficient approach to estimate GPP globally. Plans to launch the Global Change Observation Mission-Climate (GCOM-C) satellite carrying the second-generation global imager (SGLI) sensor in 2014 [2]. The SGLI sensor will observe seven spectral bands from the visible to the near infrared (NIR) with a spatial resolution 250 m for land area observations. The obtained data are planned to be used to estimate global GPP
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