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14 October 2015 Algorithm developing of gross primary production from its capacity and a canopy conductance index using flux and global observing satellite data
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We plan to estimate gross primary production (GPP) using the SGLI sensor on-board the GCOM-C1 satellite after it is launched in 2017 by the Japan Aerospace Exploration Agency, as we have developed a GPP estimation algorithm that uses SGLI sensor data. The characteristics of this GPP estimation method correspond to photosynthesis. The rate of plant photosynthesis depends on the plant's photosynthesis capacity and the degree to which photosynthesis is suppressed. The photosynthesis capacity depends on the chlorophyll content of leaves, which is a plant physiological parameter, and the degree of suppression of photosynthesis depends on weather conditions. The framework of the estimation method to determine the light-response curve parameters was developed using ux and satellite data in a previous study[1]. We estimated one of the light-response curve parameters based on the linear relationship between GPP capacity at 2000 (μmolm-2s-1) of photosynthetically active radiation and a chlorophyll index (CIgreen [2;3] ). The relationship was determined for seven plant functional types. Decreases in the photosynthetic rate are controlled by stomatal opening and closing. Leaf stomatal conductance is maximal during the morning and decreases in the afternoon. We focused on daily changes in leaf stomatal conductance. We used open shrub flux data and MODIS reflectance data to develop an algorithm for a canopy. We first evaluated the daily changes in GPP capacity estimated from CIgreen and photosynthesis active radiation using light response curves, and GPP observed during a flux experiment. Next, we estimated the canopy conductance using flux data and a big-leaf model using the Penman-Monteith equation[4]. We estimated GPP by multiplying GPP capacity by the normalized canopy conductance at 10:30, the time of satellite observations. The results showed that the estimated daily change in GPP was almost the same as the observed GPP. From this result, we defined a normalized canopy conductance index based on the satellite value taken at 10:30 as the canopy conductance factor. The method of scaling-up the canopy conductance index and the availability of data from the global observing satellite project are discussed herein.
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Kanako Muramatsu, Shinobu Furumi, and Motomasa Daigo "Algorithm developing of gross primary production from its capacity and a canopy conductance index using flux and global observing satellite data", Proc. SPIE 9637, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII, 96371A (14 October 2015);

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