Intensity Simulation of a Fourier Transform Infrared Spectrometer.

This paper introduces an intensity simulation for the Fourier transform infrared spectrometer whose core element is the Michelson interferometer to provide support for the on-orbit monitoring of the instrument and to improve the data processing and application of the Fourier transform spectrometer. The Geostationary Interferometric Infrared Imager (GIIRS) aboard on Fengyun-4B (FY-4B) satellite, which will be launched in 2020, aims to provide hyperspectral infrared observations. An intensity simulation of the Michelson interferometer based on the GIIRS's instrument parameters is systematically analyzed in this paper. Off-axis effects and non-linearity response are two important factors to be considered in this simulation. Off-axis effects mainly cause the wavenumber shift to induce a large brightness temperature error compared with the input spectrum, and the non-linearity response reduces the energy received by the detector. Then, off-axis effects and a non-linearity response are added to the input spectrum successively to obtain the final spectrum. Off-axis correction and non-linearity correction are also developed to give a full simulation process. Comparing the corrected spectrum with the input spectrum, we can see that the brightness temperature errors have a magnitude of 10-3 K, and this fully proves the reliability and rationality of the whole simulation process.

Estimation of Chlorophyll Fluorescence at Different Scales: A Review.

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.

Retrieving the Diurnal FPAR of a Maize Canopy from the Jointing Stage to the Tasseling Stage with Vegetation Indices under Different Water Stresses and Light Conditions.

The fraction of absorbed photosynthetically active radiation (FPAR) is a key variable in the model of vegetation productivity. Vegetation indices (VIs) that were derived from instantaneous remote-sensing data have been successfully used to estimate the FPAR of a day or a longer period. However, it has not yet been verified whether continuous VIs can be used to accurately estimate the diurnal dynamics of a vegetation canopy FPAR, which may fluctuate dramatically within a day. In this study, we measured the high temporal resolution spectral data (480 to 850 nm) and FPAR data of a maize canopy from the jointing stage to the tasseling stage under different irrigation and illumination conditions using two automatic observation systems. To estimate the FPAR, we developed regression models based on a quadratic function using 13 kinds of VIs. The results show the following: (1) Under nondrought conditions, although the illumination condition (sunny or cloudy) influenced the trend of the canopy diurnal FPAR, it had only a slight effect on the model accuracies of the FPAR-VIs. The maximum coefficients of determination (R²) of the FPAR-VIs models generated for the sunny nondrought data, the cloudy nondrought data, and all of the nondrought data were 0.895, 0.88, and 0.828, respectively. The VIs-including normalized difference vegetation index (NDVI), green NDVI (GNDVI), red-edge simple ratio (SR705), modified simple ratio 2 (mSR2), red-edge normalized difference vegetation index (NDVI705), and enhanced vegetation index (EVI)-that were related to the canopy structure had higher estimation accuracies (R² > 0.8) than the other VIs that were related to the soil adjustment, chlorophyll, and physiology. The estimation accuracies of the GNDVI and some red-edge VIs (including NDVI705, SR705, and mSR2) were higher than the estimation accuracy of the NDVI. (2) Under drought stress, the FPAR decreased significantly because of leaf wilting and the effective leaf area index decrease around noon. When we included drought data in the model, accuracies were reduced dramatically and the R² value of the best model was only 0.59. When we built the regression models based only on drought data, the EVI, which can weaken the influence of soil, had the best estimate accuracy (R² = 0.68).

Investigation of Atmospheric Effects on Retrieval of Sun-Induced Fluorescence Using Hyperspectral Imagery.

Significant research progress has recently been made in estimating fluorescence in the oxygen absorption bands, however, quantitative retrieval of fluorescence data is still affected by factors such as atmospheric effects. In this paper, top-of-atmosphere (TOA) radiance is generated by the MODTRAN 4 and SCOPE models. Based on simulated data, sensitivity analysis is conducted to assess the sensitivities of four indicators-depth_absorption_band, depth_nofs-depth_withfs, radiance and Fs/radiance-to atmospheric parameters (sun zenith angle (SZA), sensor height, elevation, visibility (VIS) and water content) in the oxygen absorption bands. The results indicate that the SZA and sensor height are the most sensitive parameters and that variations in these two parameters result in large variations calculated as the variation value/the base value in the oxygen absorption depth in the O2-A and O2-B bands (111.4% and 77.1% in the O2-A band; and 27.5% and 32.6% in the O2-B band, respectively). A comparison of fluorescence retrieval using three methods (Damm method, Braun method and DOAS) and SCOPE Fs indicates that the Damm method yields good results and that atmospheric correction can improve the accuracy of fluorescence retrieval. Damm method is the improved 3FLD method but considering atmospheric effects. Finally, hyperspectral airborne images combined with other parameters (SZA, VIS and water content) are exploited to estimate fluorescence using the Damm method and 3FLD method. The retrieval fluorescence is compared with the field measured fluorescence, yielding good results (R² = 0.91 for Damm vs. SCOPE SIF; R² = 0.65 for 3FLD vs. SCOPE SIF). Five types of vegetation, including ailanthus, elm, mountain peach, willow and Chinese ash, exhibit consistent associations between the retrieved fluorescence and field measured fluorescence.

[Extraction and analysis of solar-induced chlorophyll fluorescence of wheat with ground-based hyperspectral imaging system].

Dataset simulated with FluorMOD and images of wheat in heading stage taken by a ground-based hyperspectral imaging system with 3.3 nm spectral resolution and 0. 71-0. 74 nm spectral sampling interval were used test the feasibility and accuracy of three FLD methods (named FLD, 3FLD and iFLD). The results show that when spectral resolution is 3.3 nm, solar-induced chlorophyll fluorescence could be extracted effectively in O2-A band (around 760 nm) instead of O2-B band (around 687 nm). As to the extraction results of data with noises, both FLD and 3FLD are stabler than iFLD method. The results of FLD tend to be higher than true value.

[Remote sensing of chlorophyll fluorescence at airborne level based on unmanned airship platform and hyperspectral sensor].

The solar-induced chlorophyll fluorescence (ChlF) has a close relationship with photosynthetic and is considered as a probe of plant photosynthetic activity. In this study, an airborne fluorescence detecting system was constructed by using a hyperspectral imager on board an unmanned airship. Both Fraunhofer Line Discriminator (FLD) and 3FLD used to extract ChlF require the incident solar irradiance, which is always difficult to receive at airborne level. Alternative FLD (aFLD) can overcome the problem by selecting non-fluorescent emitter in the image. However, aFLD is based on the assumption that reflectance is identical around the Fraunhofer line, which is not realistic. A new method, a3FLD, is proposed, which assumes that reflectance varies linearly with the wavelength around Fraunhofer line. The result of simulated data shows that ChlF retrieval error of a3FLD is significantly lower than that of aFLD when vegetation reflectance varies near the Fraunhofer line. The results of hyperspectral remote sensing data with the airborne fluorescence detecting system show that the relative values of retrieved ChlF of 5 kinds of plants extracted by both aFLD and a3FLD are consistent with vegetation growth stage and the ground-level ChlF. The ChlF values of aFLD are about 15% greater than a3FLD. In addition, using aFLD, some non-fluorescent objects have considerable ChlF value, while a3FLD can effectively overcome the problem.