Abstract
Measuring chlorophyll fluorescence is a direct and non-destructive way to monitor vegetation. In this paper, the fluorescence retrieval methods from multiple scales, ranging from near the ground to the use of space-borne sensors, are analyzed and summarized in detail. At the leaf-scale, the chlorophyll fluorescence is measured using active and passive technology. Active remote sensing technology uses a fluorimeter to measure the chlorophyll fluorescence, and passive remote sensing technology mainly depends on the sun-induced chlorophyll fluorescence filling in the Fraunhofer lines or oxygen absorptions bands. Based on these retrieval principles, many retrieval methods have been developed, including the radiance-based methods and the reflectance-based methods near the ground, as well as physically and statistically-based methods that make use of satellite data. The advantages and disadvantages of different approaches for sun-induced chlorophyll fluorescence retrieval are compared and the key issues of the current sun-induced chlorophyll fluorescence retrieval algorithms are discussed. Finally, conclusions and key problems are proposed for the future research.
Highlights
Since the 1980s, vegetation chlorophyll fluorescence has been an effective, non-destructive, and direct way to monitor changes in the physiological state of vegetation [1,2]
To extend the near-surface Solar-induced fluorescence (SIF) inversion algorithm to the satellite platform, accurate atmospheric correction information is required in order to obtain fluorescence radiance values
F-spectral fitting method (SFM) method, the reflectance is written as a first-order linear expression, and the basis spectra of the SIF spectrum is generated by principal components analysis (PCA)
Summary
Since the 1980s, vegetation chlorophyll fluorescence has been an effective, non-destructive, and direct way to monitor changes in the physiological state of vegetation [1,2]. Since the first global SIF map was produced [33,34,35], many researchers have developed SIF inversion methods from satellite data and have successfully extracted SIF from GOSAT, GOME-2, OCO-2, SCIAMACHY, and TanSat data [36,37,38,39,40,41,42,43]. Meroni et al summarized the sun-induced chlorophyll fluorescence (SIF) retrieval methods including the radiance-based methods and reflectance-based methods and its application at different scales [5]. We summarize the existing problems and conclusions in future research
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