Articles | Volume 17, issue 18
https://doi.org/10.5194/bg-17-4523-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-17-4523-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Sep 2020
Research article |
| 15 Sep 2020
| 15 Sep 2020
Decomposing reflectance spectra to track gross primary production in a subalpine evergreen forest
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
Troy S. Magney
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
Department of Plant Sciences, University of California, Davis, CA, USA
Debsunder Dutta
NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Department of Civil Engineering, Indian Institute of Science, Bengaluru, India
David R. Bowling
School of Biological Sciences, University of Utah, Salt Lake City, UT, USA
Barry A. Logan
Department of Biology, Bowdoin College, Brunswick, ME, USA
Sean P. Burns
Department of Geography, University of Colorado, Boulder, CO, USA
National Center for Atmospheric Research, Boulder, CO, USA
Peter D. Blanken
Department of Geography, University of Colorado, Boulder, CO, USA
Katja Grossmann
Institute of Environmental Physics, University of Heidelberg, Heidelberg, Germany
Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles, Los Angeles, CA, USA
Sophia Lopez
Department of Biology, Bowdoin College, Brunswick, ME, USA
Andrew D. Richardson
Center for Ecosystem Science and Society, and School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA
Jochen Stutz
Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles, Los Angeles, CA, USA
Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, CA, USA
Christian Frankenberg
CORRESPONDING AUTHOR
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
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23 citations as recorded by crossref.
- Proximal remote sensing and gross primary productivity in a temperate salt marsh A. Vázquez-Lule & R. Vargas 10.1016/j.agrformet.2023.109639
- The roles of radiative, structural and physiological information of sun-induced chlorophyll fluorescence in predicting gross primary production of a corn crop at various temporal scales P. Yang et al. 10.1016/j.agrformet.2023.109720
- Dynamic monitoring and analysis of factors influencing ecological environment quality in northern Anhui, China, based on the Google Earth Engine X. Wang et al. 10.1038/s41598-022-24413-0
- TSWIFT: Tower Spectrometer on Wheels for Investigating Frequent Timeseries for high-throughput phenotyping of vegetation physiology C. Wong et al. 10.1186/s13007-023-01001-5
- Accounting for canopy structure improves hyperspectral radiative transfer and sun-induced chlorophyll fluorescence representations in a new generation Earth System model R. Braghiere et al. 10.1016/j.rse.2021.112497
- Developing Hyperspectral Indices for Assessing Seasonal Variations in the Ratio of Chlorophyll to Carotenoid in Deciduous Forests G. Song & Q. Wang 10.3390/rs14061324
- Forests for forests: combining vegetation indices with solar-induced chlorophyll fluorescence in random forest models improves gross primary productivity prediction in the boreal forest Z. Pierrat et al. 10.1088/1748-9326/aca5a0
- NIRP as a remote sensing proxy for measuring gross primary production across different biomes and climate zones: Performance and limitations S. Chen et al. 10.1016/j.jag.2023.103437
- Optical vegetation indices for monitoring terrestrial ecosystems globally Y. Zeng et al. 10.1038/s43017-022-00298-5
- Solar-induced chlorophyll fluorescence captures photosynthetic phenology better than traditional vegetation indices J. Zhang et al. 10.1016/j.isprsjprs.2023.07.021
- Evaluating photosynthetic activity across Arctic-Boreal land cover types using solar-induced fluorescence R. Cheng et al. 10.1088/1748-9326/ac9dae
- Plant optics: underlying mechanisms in remotely sensed signals for phenotyping applications C. Wong & S. Kothari 10.1093/aobpla/plad039
- Vegetation spectra as an integrated measure to explain underlying soil characteristics: a review of recent advances W. Buma et al. 10.3389/fenvs.2024.1430818
- Seasonal timing of fluorescence and photosynthetic yields at needle and canopy scales in evergreen needleleaf forests Z. Pierrat et al. 10.1002/ecy.4402
- Tower‐Based Remote Sensing Reveals Mechanisms Behind a Two‐phased Spring Transition in a Mixed‐Species Boreal Forest Z. Pierrat et al. 10.1029/2020JG006191
- Diurnal and Seasonal Dynamics of Solar‐Induced Chlorophyll Fluorescence, Vegetation Indices, and Gross Primary Productivity in the Boreal Forest Z. Pierrat et al. 10.1029/2021JG006588
- Spatial covariation between solar-induced fluorescence and vegetation indices from Arctic-Boreal landscapes A. Maguire et al. 10.1088/1748-9326/ac188a
- Seasonal variation in the canopy color of temperate evergreen conifer forests B. Seyednasrollah et al. 10.1111/nph.17046
- Gross primary production (GPP) and red solar induced fluorescence (SIF) respond differently to light and seasonal environmental conditions in a subalpine conifer forest J. Yang et al. 10.1016/j.agrformet.2022.108904
- Combining NDVI, PRI and the quantum yield of solar-induced fluorescence improves estimations of carbon fluxes in deciduous and evergreen forests D. Kováč et al. 10.1016/j.scitotenv.2022.154681
- The biological basis for using optical signals to track evergreen needleleaf photosynthesis Z. Pierrat et al. 10.1093/biosci/biad116
- Snow-corrected vegetation indices for improved gross primary productivity assessment in North American evergreen forests R. Wang et al. 10.1016/j.agrformet.2023.109600
- THEMS: an automated thermal and hyperspectral proximal sensing system for canopy reflectance, radiance and temperature W. Woodgate et al. 10.1186/s13007-020-00646-w
22 citations as recorded by crossref.
- Proximal remote sensing and gross primary productivity in a temperate salt marsh A. Vázquez-Lule & R. Vargas 10.1016/j.agrformet.2023.109639
- The roles of radiative, structural and physiological information of sun-induced chlorophyll fluorescence in predicting gross primary production of a corn crop at various temporal scales P. Yang et al. 10.1016/j.agrformet.2023.109720
- Dynamic monitoring and analysis of factors influencing ecological environment quality in northern Anhui, China, based on the Google Earth Engine X. Wang et al. 10.1038/s41598-022-24413-0
- TSWIFT: Tower Spectrometer on Wheels for Investigating Frequent Timeseries for high-throughput phenotyping of vegetation physiology C. Wong et al. 10.1186/s13007-023-01001-5
- Accounting for canopy structure improves hyperspectral radiative transfer and sun-induced chlorophyll fluorescence representations in a new generation Earth System model R. Braghiere et al. 10.1016/j.rse.2021.112497
- Developing Hyperspectral Indices for Assessing Seasonal Variations in the Ratio of Chlorophyll to Carotenoid in Deciduous Forests G. Song & Q. Wang 10.3390/rs14061324
- Forests for forests: combining vegetation indices with solar-induced chlorophyll fluorescence in random forest models improves gross primary productivity prediction in the boreal forest Z. Pierrat et al. 10.1088/1748-9326/aca5a0
- NIRP as a remote sensing proxy for measuring gross primary production across different biomes and climate zones: Performance and limitations S. Chen et al. 10.1016/j.jag.2023.103437
- Optical vegetation indices for monitoring terrestrial ecosystems globally Y. Zeng et al. 10.1038/s43017-022-00298-5
- Solar-induced chlorophyll fluorescence captures photosynthetic phenology better than traditional vegetation indices J. Zhang et al. 10.1016/j.isprsjprs.2023.07.021
- Evaluating photosynthetic activity across Arctic-Boreal land cover types using solar-induced fluorescence R. Cheng et al. 10.1088/1748-9326/ac9dae
- Plant optics: underlying mechanisms in remotely sensed signals for phenotyping applications C. Wong & S. Kothari 10.1093/aobpla/plad039
- Vegetation spectra as an integrated measure to explain underlying soil characteristics: a review of recent advances W. Buma et al. 10.3389/fenvs.2024.1430818
- Seasonal timing of fluorescence and photosynthetic yields at needle and canopy scales in evergreen needleleaf forests Z. Pierrat et al. 10.1002/ecy.4402
- Tower‐Based Remote Sensing Reveals Mechanisms Behind a Two‐phased Spring Transition in a Mixed‐Species Boreal Forest Z. Pierrat et al. 10.1029/2020JG006191
- Diurnal and Seasonal Dynamics of Solar‐Induced Chlorophyll Fluorescence, Vegetation Indices, and Gross Primary Productivity in the Boreal Forest Z. Pierrat et al. 10.1029/2021JG006588
- Spatial covariation between solar-induced fluorescence and vegetation indices from Arctic-Boreal landscapes A. Maguire et al. 10.1088/1748-9326/ac188a
- Seasonal variation in the canopy color of temperate evergreen conifer forests B. Seyednasrollah et al. 10.1111/nph.17046
- Gross primary production (GPP) and red solar induced fluorescence (SIF) respond differently to light and seasonal environmental conditions in a subalpine conifer forest J. Yang et al. 10.1016/j.agrformet.2022.108904
- Combining NDVI, PRI and the quantum yield of solar-induced fluorescence improves estimations of carbon fluxes in deciduous and evergreen forests D. Kováč et al. 10.1016/j.scitotenv.2022.154681
- The biological basis for using optical signals to track evergreen needleleaf photosynthesis Z. Pierrat et al. 10.1093/biosci/biad116
- Snow-corrected vegetation indices for improved gross primary productivity assessment in North American evergreen forests R. Wang et al. 10.1016/j.agrformet.2023.109600
Latest update: 13 Dec 2024
Short summary
We measured reflected sunlight from an evergreen canopy for a year to detect changes in pigments that play an important role in regulating the seasonality of photosynthesis. Results show a strong mechanistic link between spectral reflectance features and pigment content, which is validated using a biophysical model. Our results show spectrally where, why, and when spectral features change over the course of the season and show promise for estimating photosynthesis remotely.
We measured reflected sunlight from an evergreen canopy for a year to detect changes in pigments...
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