Articles | Volume 10, issue 4
https://doi.org/10.5194/bg-10-2451-2013
© Author(s) 2013. 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-10-2451-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Apr 2013
Research article |
| 12 Apr 2013
A data assimilation framework for constraining upscaled cropland carbon flux seasonality and biometry with MODIS
O. Sus
now at: CREAF, Universitat Autònoma de Barcelona, Barcelona, Spain
The University of Edinburgh, School of GeoSciences and SAGES, West Mains Road, Edinburgh, EH9 3JN, UK
M. W. Heuer
Atmospheric Turbulence and Diffusion Division, NOAA/ARL, Oak Ridge, TN, USA
T. P. Meyers
Atmospheric Turbulence and Diffusion Division, NOAA/ARL, Oak Ridge, TN, USA
M. Williams
The University of Edinburgh, School of GeoSciences and SAGES, West Mains Road, Edinburgh, EH9 3JN, UK
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Cited
16 citations as recorded by crossref.
- Grain Yield Observations Constrain Cropland CO2 Fluxes Over Europe M. Combe et al. 10.1002/2017JG003937
- Estimation of the Bio-Parameters of Winter Wheat by Combining Feature Selection with Machine Learning Using Multi-Temporal Unmanned Aerial Vehicle Multispectral Images C. Zhang et al. 10.3390/rs16030469
- Estimation of Community Land Model parameters for an improved assessment of net carbon fluxes at European sites H. Post et al. 10.1002/2015JG003297
- The Value of Sentinel-2 Spectral Bands for the Assessment of Winter Wheat Growth and Development A. Revill et al. 10.3390/rs11172050
- The impact of climate change and climate extremes on sugarcane production S. Flack‐Prain et al. 10.1111/gcbb.12797
- Time variable hydraulic parameters improve the performance of a mechanistic stand transpiration model. A case study of Mediterranean Scots pine sap flow data assimilation O. Sus et al. 10.1016/j.agrformet.2014.08.009
- The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0) S. Caldararu et al. 10.5194/gmd-10-1679-2017
- Impacts of reduced model complexity and driver resolution on cropland ecosystem photosynthesis estimates A. Revill et al. 10.1016/j.fcr.2015.12.006
- A high-altitude balloon platform for determining exchange of carbon dioxide over agricultural landscapes A. Bouche et al. 10.5194/amt-9-5707-2016
- Combining High-Resolution Remote Sensing Products with a Crop Model to Estimate Carbon and Water Budget Components: Application to Sunflower G. Pique et al. 10.3390/rs12182967
- Estimation of daily CO2 fluxes and of the components of the carbon budget for winter wheat by the assimilation of Sentinel 2-like remote sensing data into a crop model G. Pique et al. 10.1016/j.geoderma.2020.114428
- Integration of prognostic sowing and harvesting schemes to enhance crop dynamic growth simulation in Noah-MP-Crop model F. Wang et al. 10.1016/j.ecoinf.2024.102785
- Improving maize growth processes in the community land model: Implementation and evaluation B. Peng et al. 10.1016/j.agrformet.2017.11.012
- The Effect of Antecedence on Empirical Model Forecasts of Crop Yield from Observations of Canopy Properties A. Florence et al. 10.3390/agriculture11030258
- Data assimilation of soil moisture and leaf area index effectively improves the simulation accuracy of water and carbon fluxes in coupled farmland hydrological model W. Wang et al. 10.1016/j.agwat.2023.108646
- Carbon cycling of European croplands: A framework for the assimilation of optical and microwave Earth observation data A. Revill et al. 10.1016/j.rse.2013.06.002
15 citations as recorded by crossref.
- Grain Yield Observations Constrain Cropland CO2 Fluxes Over Europe M. Combe et al. 10.1002/2017JG003937
- Estimation of the Bio-Parameters of Winter Wheat by Combining Feature Selection with Machine Learning Using Multi-Temporal Unmanned Aerial Vehicle Multispectral Images C. Zhang et al. 10.3390/rs16030469
- Estimation of Community Land Model parameters for an improved assessment of net carbon fluxes at European sites H. Post et al. 10.1002/2015JG003297
- The Value of Sentinel-2 Spectral Bands for the Assessment of Winter Wheat Growth and Development A. Revill et al. 10.3390/rs11172050
- The impact of climate change and climate extremes on sugarcane production S. Flack‐Prain et al. 10.1111/gcbb.12797
- Time variable hydraulic parameters improve the performance of a mechanistic stand transpiration model. A case study of Mediterranean Scots pine sap flow data assimilation O. Sus et al. 10.1016/j.agrformet.2014.08.009
- The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0) S. Caldararu et al. 10.5194/gmd-10-1679-2017
- Impacts of reduced model complexity and driver resolution on cropland ecosystem photosynthesis estimates A. Revill et al. 10.1016/j.fcr.2015.12.006
- A high-altitude balloon platform for determining exchange of carbon dioxide over agricultural landscapes A. Bouche et al. 10.5194/amt-9-5707-2016
- Combining High-Resolution Remote Sensing Products with a Crop Model to Estimate Carbon and Water Budget Components: Application to Sunflower G. Pique et al. 10.3390/rs12182967
- Estimation of daily CO2 fluxes and of the components of the carbon budget for winter wheat by the assimilation of Sentinel 2-like remote sensing data into a crop model G. Pique et al. 10.1016/j.geoderma.2020.114428
- Integration of prognostic sowing and harvesting schemes to enhance crop dynamic growth simulation in Noah-MP-Crop model F. Wang et al. 10.1016/j.ecoinf.2024.102785
- Improving maize growth processes in the community land model: Implementation and evaluation B. Peng et al. 10.1016/j.agrformet.2017.11.012
- The Effect of Antecedence on Empirical Model Forecasts of Crop Yield from Observations of Canopy Properties A. Florence et al. 10.3390/agriculture11030258
- Data assimilation of soil moisture and leaf area index effectively improves the simulation accuracy of water and carbon fluxes in coupled farmland hydrological model W. Wang et al. 10.1016/j.agwat.2023.108646
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