Assessing the contribution of understory sun-induced chlorophyll fluorescence through 3-D radiative transfer modelling and field data

下层林 遥感 环境科学 天蓬 大气辐射传输码 光辉 辐射传输 多光谱图像 树冠 叶绿素荧光 图像分辨率 叶面积指数 大气科学 物理 地理 生态学 光学 荧光 考古 生物
作者
A. Hornero,Peter North,Pablo J. Zarco‐Tejada,Uwe Rascher,M. Pilar Martín,Mirco Migliavacca,Hernandez-Clemente Rocio
出处
期刊:Remote Sensing of Environment [Elsevier BV]
卷期号:253: 112195-112195 被引量:27
标识
DOI:10.1016/j.rse.2020.112195
摘要

A major international effort has been made to monitor sun-induced chlorophyll fluorescence (SIF) from space as a proxy for the photosynthetic activity of terrestrial vegetation. However, the effect of spatial heterogeneity on the SIF retrievals from canopy radiance derived from images with medium and low spatial resolution remains uncharacterised. In images from forest and agricultural landscapes, the background comprises a mixture of soil and understory and can generate confounding effects that limit the interpretation of the SIF at the canopy level. This paper aims to improve the understanding of SIF from coarse spatial resolutions in heterogeneous canopies by considering the separated contribution of tree crowns, understory and background components, using a modified version of the FluorFLIGHT radiative transfer model (RTM). The new model is compared with others through the RAMI model intercomparison framework and is validated with airborne data. The airborne campaign includes high-resolution data collected over a tree-grass ecosystem with the HyPlant imaging spectrometer within the FLuorescence EXplorer (FLEX) preparatory missions. Field data measurements were collected from plots with a varying fraction of tree and understory vegetation cover. The relationship between airborne SIF calculated from pure tree crowns and aggregated pixels shows the effect of the understory at different resolutions. For a pixel size smaller than the mean crown size, the impact of the background was low (R2 > 0.99; NRMSE < 0.01). By contrast, for a pixel size larger than the crown size, the goodness of fit decreased (R2 < 0.6; NRMSE > 0.2). This study demonstrates that using a 3D RTM model improves the calculation of SIF significantly (R2 = 0.83, RMSE = 0.03 mW m−2 sr−1 nm−1) when the specific contribution of the soil and understory layers are accounted for, in comparison with the SIF calculated from mixed pixels that considers only one layer as background (R2 = 0.4, RMSE = 0.28 mW m−2 sr−1 nm−1). These results demonstrate the need to account for the contribution of SIF emitted by the understory in the quantification of SIF within tree crowns and within the canopy from aggregated pixels in heterogeneous forest canopies.
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