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Parameterization of an ecosystem light-use-efficiency model for predicting savanna GPP using MODIS EVI

机译:使用MODIS EVI预测大草原GPP的生态系统光利用效率模型的参数化

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Accurate estimation of carbon fluxes across space and time is of great importance for quantifying global carbon balances. Current production efficiency models for calculation of gross primary production (GPP) depend on estimates of light-use-efficiency (LUE) obtained from look-up tables based on biome type and coarse-resolution meteorological inputs that can introduce uncertainties. Plant function is especially difficult to parameterize in the savanna biome due to the presence of varying mixtures of multiple plant functional types (PFTs)with distinct phenologies and responses to environmental factors. The objective of this study was to find a simple and robust method to accurately up-scale savanna GPP fromlocal, eddy covariance (EC) flux tower GPP measures to regional scales utilizing entirely remote sensing oservations. Here we assessed seasonal patterns of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation productswith seasonal EC tower GPP (GPP_(EC)) at four sites along an ecological rainfall gradient (the North Australian Tropical Transect, NATT) encompassing tropical wet to dry savannas. The enhanced vegetation index (EVI) tracked the seasonal variations of GPP_(EC) well at both site- and cross-site levels (R~2= 0.84). The EVI relationship with GPPEC was further strengthened through coupling with ecosystem light-use-efficiency (eLUE), defined as the ratio of GPP to photosynthetically active radiation (PAR). Two savanna landscape eLUEmodels, driven by top-of-canopy incident PAR (PARTOC) or top-of-atmosphere incident PAR (PAR_(TOA)) were parameterized and investigated. GPP predicted using the eLUE models correlated well with GPP_(EC), with R~2 of 0.85 (RMSE = 0.76 g C m~(?2) d~(?1)) and 0.88 (RMSE = 0.70 g C m~(?2) d~(?1)) for PAR_(TOC) and PARTOA, respectively, and were significantly improved compared to the MOD17 GPP product (R~2 = 0.58, RMSE= 1.43 g C m?2 d?1). The eLUE model also minimized the seasonal hysteresis observed between greenup and brown-down in GPP_(EC) and MODIS satellite product relationships, resulting in a consistent estimation of GPP across phenophases. The eLUE model effectively integrated the effects of variations in canopy photosynthetic capacity and environmental stress on photosynthesis, thus simplifying the up-scaling of carbon fluxes from tower to regional scale. The results fromthis study demonstrated that region-wide savanna GPP can be accurately estimated entirely with remote sensing observations without dependency on coarse-resolution ground meteorology or estimation of light-use-efficiency parameters.
机译:准确估算跨时空分布的碳通量对于量化全球碳平衡非常重要。当前用于计算初级生产总值(GPP)的生产效率模型取决于从查找表获得的光使用效率(LUE)估算值,该表基于生物群系类型和可能引入不确定性的粗分辨率气象输入。由于存在具有不同物候和对环境因素的响应的多种植物功能类型(PFT)的不同混合物的存在,在热带稀树草原生物群系中特别难以设置植物功能的参数。这项研究的目的是找到一种简单而强大的方法,以利用本地遥感技术,将热带稀树草原GPP从局部涡动协方差(EC)通量塔GPP度量准确地按比例放大到区域尺度。在这里,我们评估了沿生态降雨梯度(北澳大利亚热带样带,NATT)的四个站点(包括热带干湿热带稀树草原)中带有季节性EC塔GPP(GPP_(EC))的中​​分辨率成像光谱仪(MODIS)植被产品的季节性模式。增强植被指数(EVI)在站点和跨站点水平上都很好地跟踪了GPP_(EC)的季节变化(R〜2 = 0.84)。通过与生态系统光使用效率(eLUE)耦合来进一步加强EVI与GPPEC的关系,生态系统的光使用效率定义为GPP与光合有效辐射(PAR)的比率。对由顶篷入射PAR(PARTOC)或大气顶入射PAR(PAR_(TOA))驱动的两个热带草原景观eLUE模型进行了参数化和研究。使用eLUE模型预测的GPP与GPP_(EC)密切相关,R〜2为0.85(RMSE = 0.76 g C m〜(?2)d〜(?1))和0.88(RMSE = 0.70 g C m〜( PAR_(TOC)和PARTOA分别为?2)d〜(?1)),与MOD17 GPP产品(R〜2 = 0.58,RMSE = 1.43 g C m?2 d?1)相比有明显改善。 eLUE模型还最小化了GPP_(EC)和MODIS卫星产品关系中绿色上升和下降之间观察到的季节性滞后,从而在整个表相期间对GPP进行了一致的估计。 eLUE模型有效地整合了冠层光合能力和环境胁迫的变化对光合作用的影响,从而简化了碳流量从塔架向区域尺度的放大。这项研究的结果表明,利用遥感观测可以完全准确地估计出整个热带稀树草原GPP,而无需依赖于高分辨率的地面气象学或光利用效率参数的估计。

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