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| Home > Publications database > Systematic Assessment Of Airborne Sun-Induced Fluorescence Maps By The Application Of Quality Criteria |
| Home > Publications database > Systematic Assessment Of Airborne Sun-Induced Fluorescence Maps By The Application Of Quality Criteria |
| Conference Presentation (Other) | FZJ-2020-00156 |
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2019
Abstract: When plants absorb light, not all energy is converted by photosynthesis, but excess energy is released as heat or emitted as sun-induced chlorophyll fluorescence (F). This signal, related to the photosynthetic efficiency of plants, has been intensively studied and measured from ground, airborne and satellite. However, retrieving sun-induced fluorescence (F) from remote sensing data is challenging because accurate modeling of atmospheric influences is required.. The advent of the airborne imaging spectrometer HyPlant made possible to produce F maps in high-spatial resolution (1-3 meters), which is a valuable tool to better understand F at relevant ecosystem scale. Currently, two different algorithms are used routinely to retrieve red and far-red F from HyPlant. Both methods are based on the O 2 absorption bands, but while iFLD method employs a semi-empirical atmospheric correction (i.e., bare-soils), the SFM makes use of a physically-based atmospheric modeling (MODTRAN5 code). A common method of testing the reliability of a remotely sensed F product (in this study airborne F maps) is the comparison with “ground truth” data where the atmosphere can be neglected. In this work we tested another possibility of assessing the quality of the airborne F maps, which does not require ground reference measurements. For this purpose we have developed so-called ’quality criteria’, which should help to find errors and artefacts that have arisen during F retrieval. This method was used to test the quality of the airborne F maps of 2016 campaign. By applying the quality criteria, clear differences in the performance of two retrievals were found. Although it was shown that both retrievals performed well in F 760 retrieval, even at places with changes from vegetated to non-vegetated sites on pixel scale, iFLD was more robust for retrieving correct absolute values for F 760 and F 687 , while SFM performed less accurate in this term, over- and underestimating F values. Furthermore, previously reported problems with image pre-processing (deconvolution for correcting PSF) of SFM became clear here. This was causing strong artefacts in F 687 retrievals from SFM. However, SFM proved to be the more suitable method for identifying small differences on pixel scale. Moreover, this algorithm did not show systematic variations over entire flight lines as observed by the use of iFLD. The physically-based approach of atmospheric correction used with SFM thus provided more interference-free F maps than the semi-empirical correction using non-fluorescent surfaces as in iFLD retrieval. Testing F retrievals on vegetation under different illumination conditions showed the necessity to calculate F yield for quantification of photosynthesis rates. The application of the proposed quality features proved to be a valuable tool for assessing the performance of F retrieval on airborne maps. Therefore we propose to use the quality criteria even when sufficient ground references are available, because even if the quality criteria do not replace ground-truth data, they provide important additional information about the quality of the F product of the respective retrieval method.
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