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探索森林生态系统中空气传播的红和远红太阳诱导荧光与基于过程的总初级生产力估计值之间的空间关系。

Exploring the spatial relationship between airborne-derived red and far-red sun-induced fluorescence and process-based GPP estimates in a forest ecosystem.

作者信息

Tagliabue Giulia, Panigada Cinzia, Dechant Benjamin, Baret Frédéric, Cogliati Sergio, Colombo Roberto, Migliavacca Mirco, Rademske Patrick, Schickling Anke, Schüttemeyer Dirk, Verrelst Jochem, Rascher Uwe, Ryu Youngryel, Rossini Micol

机构信息

Remote Sensing of Environmental Dynamics Laboratory, University of Milano - Bicocca, Milan, Italy.

Department of Landscape Architecture and Rural Systems Engineering, Seoul National University, Seoul, Republic of Korea.

出版信息

Remote Sens Environ. 2019 Sep;231:111272. doi: 10.1016/j.rse.2019.111272.

Abstract

Terrestrial gross primary productivity (GPP) plays an essential role in the global carbon cycle, but the quantification of the spatial and temporal variations in photosynthesis is still largely uncertain. Our work aimed to investigate the potential of remote sensing to provide new insights into plant photosynthesis at a fine spatial resolution. This goal was achieved by exploiting high-resolution images acquired with the FLuorescence EXplorer (FLEX) airborne demonstrator . The sensor was flown over a mixed forest, and the images collected were elaborated to obtain two independent indicators of plant photosynthesis. First, maps of sun-induced chlorophyll fluorescence (F), a novel indicator of plant photosynthetic activity, were successfully obtained at both the red and far-red peaks (r = 0.89 and < 0.01, r = 0.77 and p < 0.01, respectively, compared to top-of-canopy ground-based measurements acquired synchronously with the overflight) over the forested study area. Second, maps of GPP and absorbed photosynthetically active radiation (APAR) were derived using a customised version of the coupled biophysical model Breathing Earth System Simulator (BESS). The model was driven with airborne-derived maps of key forest traits (i.e., leaf chlorophyll content (LCC) and leaf area index (LAI)) and meteorological data providing a high-resolution snapshot of the variables of interest across the study site. The LCC and LAI were accurately estimated (RMSE = 5.66 μg cm and RMSE = 0.51 mm, respectively) through an optimised Look-Up-Table-based inversion of the PROSPECT-4-INFORM radiative transfer model, ensuring the accurate representation of the spatial variation of these determinants of the ecosystem's functionality. The spatial relationships between the measured F and modelled BESS outputs were then analysed to interpret the variability of ecosystem functioning at a regional scale. The results showed that far-red F is significantly correlated with the GPP (r = 0.46, < 0.001) and APAR (r = 0.43, p < 0.001) in the spatial domain and that this relationship is nonlinear. Conversely, no statistically significant relationships were found between the red F and the GPP or APAR ( > 0.05). The spatial relationships found at high resolution provide valuable insight into the critical role of spatial heterogeneity in controlling the relationship between the far-red F and the GPP, indicating the need to consider this heterogeneity at a coarser resolution.

摘要

陆地总初级生产力(GPP)在全球碳循环中起着至关重要的作用,但光合作用时空变化的量化仍存在很大不确定性。我们的工作旨在研究遥感技术在精细空间分辨率下为植物光合作用提供新见解的潜力。这一目标是通过利用搭载在荧光探测器(FLEX)机载演示器上获取的高分辨率图像来实现的。该传感器飞越一片混交林,并对采集的图像进行处理,以获得两个独立的植物光合作用指标。首先,成功获取了太阳诱导叶绿素荧光(F)图,这是一种植物光合活性的新指标,在森林研究区域的红色和远红色峰值处均得到了与同步进行的冠层顶部地面测量相比具有显著相关性的结果(红色峰值处r = 0.89,p < 0.01;远红色峰值处r = 0.77,p < 0.01)。其次,利用耦合生物物理模型呼吸地球系统模拟器(BESS)的定制版本推导了GPP和光合有效辐射吸收量(APAR)图。该模型由机载获取的关键森林特征(即叶片叶绿素含量(LCC)和叶面积指数(LAI))图以及气象数据驱动,提供了研究区域内感兴趣变量的高分辨率快照。通过基于PROSPECT - 4 - INFORM辐射传输模型的优化查找表反演,准确估计了LCC和LAI(RMSE分别为5.66 μg/cm和0.51 mm),确保了这些生态系统功能决定因素空间变化的准确表征。然后分析实测F与模型BESS输出之间的空间关系,以解释区域尺度上生态系统功能的变异性。结果表明,在空间域中,远红色F与GPP(r = 0.46,p < 0.001)和APAR(r = 0.43,p < 0.001)显著相关,且这种关系是非线性的。相反,在红色F与GPP或APAR之间未发现统计学上的显著关系(p > 0.05)。在高分辨率下发现的空间关系为空间异质性在控制远红色F与GPP之间关系中的关键作用提供了有价值的见解,表明需要在更粗的分辨率下考虑这种异质性。

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