Articles | Volume 12, issue 15
https://doi.org/10.5194/bg-12-4577-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-12-4577-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
03 Aug 2015
Research article |
| 03 Aug 2015
Predicting landscape-scale CO2 flux at a pasture and rice paddy with long-term hyperspectral canopy reflectance measurements
J. H. Matthes
CORRESPONDING AUTHOR
Department of Geography, Dartmouth College, 6017 Fairchild, Hanover, NH, USA
S. H. Knox
Department of Environmental Science, Policy, and Management, University of California – Berkeley, Berkeley, CA, USA
C. Sturtevant
Department of Environmental Science, Policy, and Management, University of California – Berkeley, Berkeley, CA, USA
O. Sonnentag
Département de Géographie, Université de Montréal, Montréal, Canada
J. Verfaillie
Department of Environmental Science, Policy, and Management, University of California – Berkeley, Berkeley, CA, USA
D. Baldocchi
Department of Environmental Science, Policy, and Management, University of California – Berkeley, Berkeley, CA, USA
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Cited
18 citations as recorded by crossref.
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- Spatiotemporal changes in the boreal forest in Siberia over the period 1985–2015 against the background of climate change W. Fu et al. 10.5194/esd-14-223-2023
- Forest dynamics and responses to climate change and human activities in the arid and semiarid regions of the Altai Mountains, China L. Zhang et al. 10.1093/jpe/rtaf001
- Assessing Across-Scale Optical Diversity and Productivity Relationships in Grasslands of the Italian Alps K. Sakowska et al. 10.3390/rs11060614
- Dynamics of the alpine timberline and its response to climate change in the Hengduan mountains over the period 1985–2015 L. Tian et al. 10.1016/j.ecolind.2022.108589
- The synergic approach between machine learning, chemometrics, and NIR hyperspectral imagery for a real-time, reliable, and accurate prediction of mass loss in cement samples A. Diane et al. 10.1016/j.heliyon.2023.e15898
- Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images F. Xin et al. 10.1016/j.rse.2016.11.025
- Proximal remote sensing and gross primary productivity in a temperate salt marsh A. Vázquez-Lule & R. Vargas 10.1016/j.agrformet.2023.109639
- Using imaging spectroscopy to detect variation in terrestrial ecosystem productivity across a water‐stressed landscape S. DuBois et al. 10.1002/eap.1733
- Hyperspectral and Thermal Sensing of Stomatal Conductance, Transpiration, and Photosynthesis for Soybean and Maize under Drought V. Sobejano-Paz et al. 10.3390/rs12193182
- Making full use of hyperspectral data for gross primary productivity estimation with multivariate regression: Mechanistic insights from observations and process-based simulations B. Dechant et al. 10.1016/j.rse.2019.111435
- Can abandoned peatland pasture sequestrate more carbon dioxide from the atmosphere than an adjacent pristine bog in Newfoundland, Canada? M. Wang et al. 10.1016/j.agrformet.2017.09.010
- On estimating the gross primary productivity of Mediterranean grasslands under different fertilization regimes using vegetation indices and hyperspectral reflectance S. Cerasoli et al. 10.5194/bg-15-5455-2018
- Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods J. Verrelst et al. 10.1007/s10712-018-9478-y
- Spatio-temporal divergence in the responses of Finland’s boreal forests to climate variables M. Hou et al. 10.1016/j.jag.2020.102186
- Hyperspectral Reflectance for Measuring Canopy‐Level Nutrients and Photosynthesis in a Salt Marsh A. Vázquez‐Lule et al. 10.1029/2022JG007088
- Hyperspectral narrowband and multispectral broadband indices for remote sensing of crop evapotranspiration and its components (transpiration and soil evaporation) M. Marshall et al. 10.1016/j.agrformet.2015.12.025
17 citations as recorded by crossref.
- Decomposing reflectance spectra to track gross primary production in a subalpine evergreen forest R. Cheng et al. 10.5194/bg-17-4523-2020
- The effect of urban morphological characteristics on the spatial variation of PM2.5 air quality in downtown Nanjing T. Kokkonen et al. 10.1039/D1EA00035G
- Spatiotemporal changes in the boreal forest in Siberia over the period 1985–2015 against the background of climate change W. Fu et al. 10.5194/esd-14-223-2023
- Forest dynamics and responses to climate change and human activities in the arid and semiarid regions of the Altai Mountains, China L. Zhang et al. 10.1093/jpe/rtaf001
- Assessing Across-Scale Optical Diversity and Productivity Relationships in Grasslands of the Italian Alps K. Sakowska et al. 10.3390/rs11060614
- Dynamics of the alpine timberline and its response to climate change in the Hengduan mountains over the period 1985–2015 L. Tian et al. 10.1016/j.ecolind.2022.108589
- The synergic approach between machine learning, chemometrics, and NIR hyperspectral imagery for a real-time, reliable, and accurate prediction of mass loss in cement samples A. Diane et al. 10.1016/j.heliyon.2023.e15898
- Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images F. Xin et al. 10.1016/j.rse.2016.11.025
- Proximal remote sensing and gross primary productivity in a temperate salt marsh A. Vázquez-Lule & R. Vargas 10.1016/j.agrformet.2023.109639
- Using imaging spectroscopy to detect variation in terrestrial ecosystem productivity across a water‐stressed landscape S. DuBois et al. 10.1002/eap.1733
- Hyperspectral and Thermal Sensing of Stomatal Conductance, Transpiration, and Photosynthesis for Soybean and Maize under Drought V. Sobejano-Paz et al. 10.3390/rs12193182
- Making full use of hyperspectral data for gross primary productivity estimation with multivariate regression: Mechanistic insights from observations and process-based simulations B. Dechant et al. 10.1016/j.rse.2019.111435
- Can abandoned peatland pasture sequestrate more carbon dioxide from the atmosphere than an adjacent pristine bog in Newfoundland, Canada? M. Wang et al. 10.1016/j.agrformet.2017.09.010
- On estimating the gross primary productivity of Mediterranean grasslands under different fertilization regimes using vegetation indices and hyperspectral reflectance S. Cerasoli et al. 10.5194/bg-15-5455-2018
- Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods J. Verrelst et al. 10.1007/s10712-018-9478-y
- Spatio-temporal divergence in the responses of Finland’s boreal forests to climate variables M. Hou et al. 10.1016/j.jag.2020.102186
- Hyperspectral Reflectance for Measuring Canopy‐Level Nutrients and Photosynthesis in a Salt Marsh A. Vázquez‐Lule et al. 10.1029/2022JG007088
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Latest update: 30 Jul 2025
Short summary
This research used a long-term data set of near-surface canopy hyperspectral reflectance collected over 5 years to test the ability of these measurements to predict ecosystem carbon flux at a pasture and rice paddy in the California Delta, USA. We determined that each reflectance sampling event best captured the integrated prior week of carbon dioxide uptake, providing an important benchmark for understanding the lagged correlation between ecosystem carbon uptake and biochemical reflectance.
This research used a long-term data set of near-surface canopy hyperspectral reflectance...
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