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Algorithm developing of gross primary production from its capacity and a canopy conductance index using flux and global observing satellite data

机译:利用通量和全球观测卫星数据从能力和冠层电导率指数发展初级生产总值的算法

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We plan to estimate gross primary prodcution (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 flux and satellite data in a previous study. We estimated one of the light-response curve parameters based on the linear relationship between GPP capacity at 2000 (μmolm~(-2)s~(-1)) of photosynthetically active radiation and a chlorophyll index (C I_(green)). 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 C I_(green) 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. 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.
机译:由于我们已经开发了使用SGLI传感器数据的GPP估算算法,因此,我们计划在2017年日本航空航天局发射GCOM-C1卫星后使用SGLI传感器估算原始总生产量(GPP)。此GPP估算方法的特征与光合作用相对应。植物光合作用的速率取决于植物的光合作用能力和抑制光合作用的程度。光合作用的能力取决于叶片的叶绿素含量,这是植物的生理参数,而光合作用的抑制程度则取决于天气条件。在先前的研究中,使用通量和卫星数据开发了确定光响应曲线参数的估算方法的框架。我们基于2000年光合作用辐射的GPP容量(μmolm〜(-2)s〜(-1))和叶绿素指数(C I_(green))之间的线性关系,估算了光响应曲线参数之一。确定了七种植物功能类型的关系。光合速率的降低是通过气孔的开闭来控制的。叶片气孔导度在早晨最大,在下午减少。我们专注于叶片气孔导度的每日变化。我们使用开放灌木通量数据和MODIS反射率数据来开发冠层算法。我们首先使用光响应曲线评估了根据C I_(绿色)和光合作用活性辐射估算的GPP容量的每日变化,并在通量实验中观察到了GPP。接下来,我们使用流量数据估算树冠电导,并使用Penman-Monteith方程估算大叶模型。我们通过将GPP容量乘以卫星观测时间10:30的归一化冠层电导来估算GPP。结果表明,GPP的每日估计变化与观察到的GPP几乎相同。根据此结果,我们基于以10:30取的卫星值作为树冠电导系数,定义了归一化的树冠电导指数。本文讨论了按比例增加冠层电导率的方法和来自全球观测卫星项目的数据的可用性。

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