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Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data

机译:利用卫星图像和气候数据模拟温带落叶阔叶林的初级生产总值

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Net ecosystem exchange (NEE) of CO{sub}2 between the atmosphere and forest ecosystems is determined by gross primary production (GPP) of vegetation and ecosystem respiration. CO{sub}2 flux measurements at individual CO{sub}2 eddy flux sites provide valuable information on the seasonal dynamics of GPP. In this paper, we developed and validated the satellite-based Vegetation Photosynthesis Model (VPM), using site-specific CO{sub}2 flux and climate data from a temperate deciduous broadleaf forest at Harvard Forest, Massachusetts, USA. The VPM model is built upon the conceptual partitioning of photosynthetically active vegetation and non-photosynthetic vegetation (NPV) within the leaf and canopy. It estimates GPP, using satellite-derived Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI), air temperature and photosynthetically active radiation (PAR). Multi-year (1998-2001) data analyses have shown that EVI had a stronger linear relationship with GPP than did the Normalized Difference Vegetation Index (NDVI). Two simulations of the VPM model were conducted, using vegetation indices from the VEGETATION (VGT) sensor onboard the SPOT-4 satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite, The predicted GPP values agreed reasonably well with observed GPP of the deciduous broadleaf forest at Harvard Forest, Massachusetts. This study highlighted the biophysical performance of improved vegetation indices in relation to GPP and demonstrated the potential of the VPM model for scaling-up of GPP of deciduous broadleaf forests.
机译:大气与森林生态系统之间的CO {sub} 2的净生态系统交换(NEE)由植被和生态系统呼吸的初级总产值(GPP)决定。在各个CO {sub} 2涡流通量站点处的CO {sub} 2通量测量提供了有关GPP季节性动态的有价值的信息。在本文中,我们使用来自美国马萨诸塞州哈佛森林的温带落叶阔叶林的特定地点CO {sub} 2通量和气候数据,开发并验证了基于卫星的植被光合作用模型(VPM)。 VPM模型建立在叶片和冠层内光合活性植被和非光合植被(NPV)的概念划分上。它使用卫星衍生的增强植被指数(EVI),地表水指数(LSWI),气温和光合有效辐射(PAR)估算GPP。多年(1998-2001)的数据分析表明,EVI与GPP的线性关系比归一化植被指数(NDVI)强。使用来自SPOT-4卫星上的VEGETATION(VGT)传感器和Terra卫星上的中分辨率成像光谱仪(MODIS)传感器的植被指数对VPM模型进行了两次仿真,预测的GPP值与观察到的GPP相当吻合马萨诸塞州哈佛森林的落叶阔叶林。这项研究强调了与GPP相关的改善的植被指数的生物物理性能,并证明了VPM模型对于落叶阔叶林GPP放大的潜力。

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