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Integrating satellite optical and thermal infrared observations for improving daily ecosystem functioning estimations during a drought episode
Remote Sensing of Environment ( IF 11.1 ) Pub Date : 2018-05-01 , DOI: 10.1016/j.rse.2018.02.027
Bagher Bayat , Christiaan van der Tol , Wouter Verhoef

Abstract Satellite optical and thermal infrared (TIR) spectra are linked to vegetation properties and, therefore, carry valuable information needed for estimating vegetation functioning as expressed in canopy photosynthesis [gross primary production (GPP)] and evapotranspiration (ET). The joint effort is required to fully exploit this satellite spectral information and to demonstrate its capability to reveal ecosystem functioning in various environmental conditions. We investigated the relationship between Landsat (TM5 and ETM7) optical/thermal data and canopy daily functioning of annual C3 grasses at a Fluxnet site (US-Var) during a prolonged drought episode. By using the ‘Soil-Canopy Observation of Photosynthesis and Energy fluxes’ (SCOPE) model, reference GPP and ET were simulated via locally measured weather data, and then actual GPP and ET were simulated twice: first using the vegetation properties retrieved only from the optical bands, and second using information from both the optical and thermal bands. The outputs of last two simulations were compared to flux tower measurements. For the first simulation, we used the MODTRAN atmospheric model and the optical radiative transfer (RT) routine in SCOPE, RTMo, to perform atmospheric correction and retrieve vegetation properties [notably Leaf Area Index (LAI), leaf chlorophyll content (Cab), leaf water content (Cw), leaf dry matter content (Cdm), the leaf inclination distribution function (LIDF) and the senescent material content (Cs)] by model inversion through optimization. We used the optical bands of 20 Landsat images covering the period from January to August 2004. The model inversion performance was assessed by R2 (0.86) and RMSE (0.13) between the retrieved and ground-measured LAI. All the retrieved vegetation properties were linearly interpolated over time and were used, together with locally measured weather variables, to simulate GPP and ET at half-hourly time steps with SCOPE. For the second simulation, we additionally used TIR information to retrieve the maximum carboxylation capacity (Vcmax), the Ball-Berry stomatal conductance parameter (m) and soil surface and boundary resistances (rss and rbs) by inversion of the energy balance and thermal radiative transfer routines of SCOPE, RTMt, through separate look-up tables. The comparison between simulations and measurements shows that most drought effects on ET, GPP and transpiration are “visible” in the Landsat optical bands. However, the accurate simulation of soil evaporation requires TIR information. The results from this study indicate that the integration of optical and TIR information has a great potential to capture the drought effects on the grass canopy in terms of reductions in daily GPP and ET.

中文翻译:

整合卫星光学和热红外观测以改善干旱期间的日常生态系统功能估计

摘要 卫星光学和热红外 (TIR) 光谱与植被特性相关联,因此携带评估植被功能所需的宝贵信息,如冠层光合作用 [总初级生产 (GPP)] 和蒸散量 (ET)。需要共同努力以充分利用这些卫星光谱信息并展示其在各种环境条件下揭示生态系统功能的能力。我们调查了在长期干旱期间,Fluxnet 站点 (US-Var) 的 Landsat(TM5 和 ETM7)光学/热数据与一年生 C3 草的冠层日常功能之间的关系。通过使用“光合作用和能量通量的土壤冠层观测”(SCOPE)模型,参考 GPP 和 ET 通过当地测量的天气数据进行模拟,然后对实际的 GPP 和 ET 进行了两次模拟:第一次使用仅从光带中检索到的植被特性,第二次使用来自光带和热带的信息。将最后两次模拟的输出与通量塔测量值进行比较。对于第一次模拟,我们使用 MODTRAN 大气模型和 SCOPE、RTMo 中的光学辐射传输 (RT) 程序来执行大气校正并检索植被属性 [特别是叶面积指数 (LAI)、叶叶绿素含量 (Cab)、叶水分含量 (Cw)、叶片干物质含量 (Cdm)、叶片倾斜度分布函数 (LIDF) 和衰老物质含量 (Cs)] 通过优化模型反演。我们使用了 2004 年 1 月至 8 月期间的 20 张 Landsat 图像的光带。模型反演性能通过 R2 (0.86) 和 RMSE (0.13) 在检索和地面测量的 LAI 之间进行评估。所有检索到的植被特性均随时间线性插值,并与当地测量的天气变量一起使用 SCOPE 以半小时时间步长模拟 GPP 和 ET。对于第二次模拟,我们还使用 TIR 信息通过能量平衡和热辐射的反演来检索最大羧化能力 (Vcmax)、Ball-Berry 气孔传导参数 (m) 以及土壤表面和边界电阻 (rss 和 rbs)。通过单独的查找表传输 SCOPE、RTMt 的例程。模拟和测量之间的比较表明,大多数干旱对 ET、GPP 和蒸腾作用的影响在 Landsat 光学波段中是“可见的”。然而,土壤蒸发的准确模拟需要 TIR 信息。这项研究的结果表明,光学和 TIR 信息的整合在捕捉每日 GPP 和 ET 减少方面对草冠的干旱影响方面具有巨大潜力。
更新日期:2018-05-01
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