Using High-Frequency PAR Measurements to Assess the Quality of the SIF Derived from Continuous Field Observations
Abstract
:1. Introduction
2. Methodology
2.1. Field Ground Measurements
2.1.1. Observation System
2.1.2. Measurement Scheme
2.2. SIF Retrieval
2.3. Methods for Evaluating Data Quality and Selecting Data
3. Results
3.1. The CVs of PAR during Different Sky Conditions
3.2. Performance of Data Quality Assessment and Data Selection
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Zarco-Tejada, P.J.; González-Dugo, V.; Berni, J.A. Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera. Remote Sens. Environ. 2012, 117, 322–337. [Google Scholar] [CrossRef]
- Garzonio, R.; Di Mauro, B.; Colombo, R.; Cogliati, S. Surface reflectance and sun-induced fluorescence spectroscopy measurements using a small hyperspectral UAS. Remote Sens. 2017, 9, 472. [Google Scholar] [CrossRef] [Green Version]
- Vargas, J.Q.; Bendig, J.; Mac Arthur, A.; Burkart, A.; Julitta, T.; Maseyk, K.; Thomas, R.; Siegmann, B.; Rossini, M.; Celesti, M. Unmanned aerial systems (UAS)-based methods for solar induced chlorophyll fluorescence (SIF) retrieval with non-imaging spectrometers: State of the art. Remote Sens. 2020, 12, 1624. [Google Scholar] [CrossRef]
- Morata, M.; Siegmann, B.; Morcillo-Pallarés, P.; Rivera-Caicedo, J.P.; Verrelst, J. Emulation of sun-induced fluorescence from radiance data recorded by the hyplant airborne imaging spectrometer. Remote Sens. 2021, 13, 4368. [Google Scholar] [CrossRef]
- Joiner, J.; Guanter, L.; Lindstrot, R.; Voigt, M.; Vasilkov, A.; Middleton, E.; Huemmrich, K.; Yoshida, Y.; Frankenberg, C. Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: Methodology, simulations, and application to GOME-2. Atmos. Meas. Tech. 2013, 6, 2803–2823. [Google Scholar] [CrossRef] [Green Version]
- Du, S.; Liu, L.; Liu, X.; Zhang, X.; Zhang, X.; Bi, Y.; Zhang, L. Retrieval of global terrestrial solar-induced chlorophyll fluorescence from tansat satellite. Sci. Bull. 2018, 63, 1502–1512. [Google Scholar] [CrossRef] [Green Version]
- Köhler, P.; Frankenberg, C.; Magney, T.S.; Guanter, L.; Joiner, J.; Landgraf, J. Global retrievals of solar-induced chlorophyll fluorescence with TROPOMI: First results and intersensor comparison to OCO-2. Geophys. Res. Lett. 2018, 45, 10456–10463. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mohammed, G.H.; Colombo, R.; Middleton, E.M.; Rascher, U.; van der Tol, C.; Nedbal, L.; Goulas, Y.; Pérez-Priego, O.; Damm, A.; Meroni, M. Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress. Remote Sens. Environ. 2019, 231, 111177. [Google Scholar] [CrossRef]
- Gu, L.; Wood, J.; Chang, C.Y.; Sun, Y.; Riggs, J.S. Advancing terrestrial ecosystem science with a novel automated measurement system for sun-induced chlorophyll fluorescence for integration with eddy covariance flux networks. J. Geophys. Res. Biogeosci. 2019, 124, 127–146. [Google Scholar] [CrossRef] [Green Version]
- Zhang, Y.; Zhang, Q.; Liu, L.; Zhang, Y.; Wang, S.; Ju, W.; Zhou, G.; Zhou, L.; Tang, J.; Zhu, X. Chinaspec: A network for long-term ground-based measurements of solar-induced fluorescence in china. J. Geophys. Res. Biogeosci. 2021, 126, e2020JG006042. [Google Scholar] [CrossRef]
- Cogliati, S.; Rossini, M.; Julitta, T.; Meroni, M.; Schickling, A.; Burkart, A.; Pinto, F.; Rascher, U.; Colombo, R. Continuous and long-term measurements of reflectance and sun-induced chlorophyll fluorescence by using novel automated field spectroscopy systems. Remote Sens. Environ. 2015, 164, 270–281. [Google Scholar] [CrossRef]
- Porcar-Castell, A.; Mac Arthur, A.; Rossini, M.; Eklundh, L.; Pacheco-Labrador, J.; Anderson, K.; Balzarolo, M.; Martín, M.P.; Jin, H.; Tomelleri, E. Eurospec: At the interface between remote-sensing and ecosystem CO2 flux measurements in Europe. Biogeosciences 2015, 12, 6103–6124. [Google Scholar] [CrossRef] [Green Version]
- Drolet, G.; Wade, T.; Nichol, C.J.; MacLellan, C.; Levula, J.; Porcar-Castell, A.; Nikinmaa, E.; Vesala, T. A temperature-controlled spectrometer system for continuous and unattended measurements of canopy spectral radiance and reflectance. Int. J. Remote Sens. 2014, 35, 1769–1785. [Google Scholar] [CrossRef]
- Pacheco-Labrador, J.; Hueni, A.; Mihai, L.; Sakowska, K.; Julitta, T.; Kuusk, J.; Sporea, D.; Alonso, L.; Burkart, A.; Cendrero-Mateo, M.P. Sun-induced chlorophyll fluorescence I: Instrumental considerations for proximal spectroradiometers. Remote Sens. 2019, 11, 960. [Google Scholar] [CrossRef] [Green Version]
- Aasen, H.; Van Wittenberghe, S.; Sabater Medina, N.; Damm, A.; Goulas, Y.; Wieneke, S.; Hueni, A.; Malenovský, Z.; Alonso, L.; Pacheco-Labrador, J. Sun-induced chlorophyll fluorescence II: Review of passive measurement setups, protocols, and their application at the leaf to canopy level. Remote Sens. 2019, 11, 927. [Google Scholar] [CrossRef] [Green Version]
- Damm, A.; Guanter, L.; Verhoef, W.; Schläpfer, D.; Garbari, S.; Schaepman, M.E. Impact of varying irradiance on vegetation indices and chlorophyll fluorescence derived from spectroscopy data. Remote Sens. Environ. 2015, 156, 202–215. [Google Scholar] [CrossRef]
- MacArthur, A.; Robinson, I.; Rossini, M.; Davis, N.; MacDonald, K. A dual-field-of-view spectrometer system for reflectance and fluorescence measurements (Piccolo Doppio) and correction of etaloning. In Proceedings of the Fifth International Workshop on Remote Sensing of Vegetation Fluorescence, Paris, France, 22–24 April 2014; European Space Agency: Paris, France, 2014. [Google Scholar]
- Zhou, X.; Liu, Z.; Xu, S.; Zhang, W.; Wu, J. An automated comparative observation system for sun-induced chlorophyll fluorescence of vegetation canopies. Sensors 2016, 16, 775. [Google Scholar] [CrossRef] [Green Version]
- Chang, C.Y.; Guanter, L.; Frankenberg, C.; Köhler, P.; Gu, L.; Magney, T.S.; Grossmann, K.; Sun, Y. Systematic assessment of retrieval methods for canopy far-red solar-induced chlorophyll fluorescence using high-frequency automated field spectroscopy. J. Geophys. Res. Biogeosci. 2020, 125, e2019JG005533. [Google Scholar] [CrossRef]
- Xu, S.; Liu, Z.; Zhao, L.; Zhao, H.; Ren, S. Diurnal response of sun-induced fluorescence and PRI to water stress in maize using a near-surface remote sensing platform. Remote Sens. 2018, 10, 1510. [Google Scholar] [CrossRef] [Green Version]
- Yang, P.; van der Tol, C. Linking canopy scattering of far-red sun-induced chlorophyll fluorescence with reflectance. Remote Sens. Environ. 2018, 209, 456–467. [Google Scholar] [CrossRef]
- Cendrero-Mateo, M.P.; Wieneke, S.; Damm, A.; Alonso, L.; Pinto, F.; Moreno, J.; Guanter, L.; Celesti, M.; Rossini, M.; Sabater, N. Sun-induced chlorophyll fluorescence III: Benchmarking retrieval methods and sensor characteristics for proximal sensing. Remote Sens. 2019, 11, 962. [Google Scholar] [CrossRef] [Green Version]
- Maier, S.W.; Günther, K.P.; Stellmes, M. Sun-induced fluorescence: A new tool for precision farming. Digit. Imaging Spectr. Tech. Appl. Precis. Agric. Crop Physiol. 2004, 66, 207–222. [Google Scholar]
- Meroni, M.; Colombo, R. Leaf level detection of solar induced chlorophyll fluorescence by means of a subnanometer resolution spectroradiometer. Remote Sens. Environ. 2006, 103, 438–448. [Google Scholar] [CrossRef]
- Meroni, M.; Busetto, L.; Colombo, R.; Guanter, L.; Moreno, J.; Verhoef, W. Performance of spectral fitting methods for vegetation fluorescence quantification. Remote Sens. Environ. 2010, 114, 363–374. [Google Scholar] [CrossRef]
- Guanter, L.; Frankenberg, C.; Dudhia, A.; Lewis, P.E.; Gómez-Dans, J.; Kuze, A.; Suto, H.; Grainger, R.G. Retrieval and global assessment of terrestrial chlorophyll fluorescence from gosat space measurements. Remote Sens. Environ. 2012, 121, 236–251. [Google Scholar] [CrossRef]
- Guanter, L.; Rossini, M.; Colombo, R.; Meroni, M.; Frankenberg, C.; Lee, J.-E.; Joiner, J. Using field spectroscopy to assess the potential of statistical approaches for the retrieval of sun-induced chlorophyll fluorescence from ground and space. Remote Sens. Environ. 2013, 133, 52–61. [Google Scholar] [CrossRef]
- Zhang, L.; Wang, S.; Huang, C.; Cen, Y.; Zhai, Y.; Tong, Q. Retrieval of sun-induced chlorophyll fluorescence using statistical method without synchronous irradiance data. IEEE Geosci. Remote Sens. Lett. 2017, 14, 384–388. [Google Scholar] [CrossRef]
- Li, S.; Gao, M.; Li, Z.-L.; Duan, S.; Leng, P. Uncertainty analysis of svd-based spaceborne far–red sun-induced chlorophyll fluorescence retrieval using tansat satellite data. Int. J. Appl. Earth Obs. Geoinf. 2021, 103, 102517. [Google Scholar] [CrossRef]
- Siheng, W.; Changping, H.; Lifu, Z.; Xianlian, G.; Anmin, F. Designment and assessment of far-red solar-induced chlorophyll fluorescence retrieval method for the terrestrial ecosystem carbon inventory satellite. Remote Sens. Technol. Appl. 2019, 34, 476–487. [Google Scholar]
- Liu, X.; Liu, L. Influence of the canopy BRDF characteristics and illumination conditions on the retrieval of solar-induced chlorophyll fluorescence. Int. J. Remote Sens. 2018, 39, 1782–1799. [Google Scholar] [CrossRef]
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Han, S.; Liu, Z.; Chen, Z.; Jiang, H.; Xu, S.; Zhao, H.; Ren, S. Using High-Frequency PAR Measurements to Assess the Quality of the SIF Derived from Continuous Field Observations. Remote Sens. 2022, 14, 2083. https://doi.org/10.3390/rs14092083
Han S, Liu Z, Chen Z, Jiang H, Xu S, Zhao H, Ren S. Using High-Frequency PAR Measurements to Assess the Quality of the SIF Derived from Continuous Field Observations. Remote Sensing. 2022; 14(9):2083. https://doi.org/10.3390/rs14092083
Chicago/Turabian StyleHan, Shuai, Zhigang Liu, Zhuang Chen, Hao Jiang, Shan Xu, Huarong Zhao, and Sanxue Ren. 2022. "Using High-Frequency PAR Measurements to Assess the Quality of the SIF Derived from Continuous Field Observations" Remote Sensing 14, no. 9: 2083. https://doi.org/10.3390/rs14092083