基于日光诱导叶绿素荧光的陆地生态系统GPP估算研究

为了更加精确全面地掌握全球陆地生态系统固碳情况,基于GUANTER提出的简单线性模型,利用FLUXNET2015通量数据、GOME-2叶绿素荧光数据、MODIS植被指数产品以及土地覆盖数据,将温度胁迫因子和饱和水汽压胁迫因子加入模型中,估算结果与传统简单线性模型的估算结果相比,13个通量站点中有10个通量站点的估算精度得到了提升。此外,本研究还在考虑环境影响因素模型的基础上,利用植被指数来模拟叶绿素荧光的冠层逃逸率fesc,进一步提升模型的估算精度。结果显示,与传统简单线性模型和只加入环境影响因子的模型估算结果相比,13个通量站点的估算精度都有所提升。

Estimation of Terrestrial Ecosystem GPP Based on Sun-induced Chlorophyll Fluorescence

The gross primary productivity (GPP) of terrestrial ecosystems is an important component of the carbon cycle of terrestrial ecosystems. Accurate calculation of GPP helps to understand the response of terrestrial ecosystems to climate change and human activity. In order to more accurately and comprehensively grasp the carbon sequestration of global terrestrial ecosystems, the simple linear model proposed by GUANTER was improved. Using FLUXNET2015 flux data, GOME-2 chlorophyll fluorescence data, MODIS vegetation index products and land cover data, temperature stress factors and saturated water vapor stress factors were added to the model. The estimated results of the simulation were improved compared with the estimates of traditional simple linear model. Among the 13 flux sites, the estimation accuracy of 10 flux sites was improved. In addition, in order to further improve the estimation accuracy of the model, canopy escape rate of chlorophyll fluorescence was also simulated based on the model incorporating environmental impact factors. The results showed that the estimation accuracy of all 13 flux sites was improved compared with the estimates of traditional simple linear models and models incorporating environmental impact factors. In conclusion, the addition of environmental impact factors and vegetation indices to traditional linear models improved the estimation accuracy of the model.