Articles | Volume 14, issue 5
https://doi.org/10.5194/gmd-14-2603-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-2603-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
12 May 2021
Methods for assessment of models |
| 12 May 2021
| 12 May 2021
Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance
Alexey N. Shiklomanov
CORRESPONDING AUTHOR
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Michael C. Dietze
Department of Earth and Environment, Boston University, Boston, MA, USA
Istem Fer
Finnish Meteorological Institute, Helsinki, Finland
Toni Viskari
Finnish Meteorological Institute, Helsinki, Finland
Shawn P. Serbin
Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, USA
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Cited
15 citations as recorded by crossref.
- The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0 J. Zhang et al. 10.5194/gmd-15-5107-2022
- Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land Y. Wang et al. 10.1029/2021MS002964
- Simulating Global Dynamic Surface Reflectances for Imaging Spectroscopy Spaceborne Missions: LPJ‐PROSAIL B. Poulter et al. 10.1029/2022JG006935
- ND-space: Normalized difference spectral mapping W. Philpot et al. 10.1016/j.rse.2021.112622
- Mapping foliar photosynthetic capacity in sub-tropical and tropical forests with UAS-based imaging spectroscopy: Scaling from leaf to canopy S. Liu et al. 10.1016/j.rse.2023.113612
- Reviews and syntheses: Remotely sensed optical time series for monitoring vegetation productivity L. Kooistra et al. 10.5194/bg-21-473-2024
- Towards uninterrupted canopy-trait time-series: A Bayesian radiative transfer model inversion using multi-sourced satellite observations D. Zhang & M. Dietze 10.1016/j.rse.2023.113475
- Linking Remote Sensing with APSIM through Emulation and Bayesian Optimization to Improve Yield Prediction H. Dokoohaki et al. 10.3390/rs14215389
- Simulating the Impacts of Drought and Warming in Summer and Autumn on the Productivity of Subtropical Coniferous Forests M. Xie et al. 10.3390/f13122147
- Extending the GOSAILT Model to Simulate Sparse Woodland Bi-Directional Reflectance with Soil Reflectance Anisotropy Consideration J. Cheng et al. 10.3390/rs14041001
- On the impact of canopy model complexity on simulated carbon, water, and solar-induced chlorophyll fluorescence fluxes Y. Wang & C. Frankenberg 10.5194/bg-19-29-2022
- Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET H. Dokoohaki et al. 10.5194/gmd-15-3233-2022
- Reducing model uncertainty of climate change impacts on high latitude carbon assimilation A. Rogers et al. 10.1111/gcb.15958
- Remote Sensing of Tundra Ecosystems Using High Spectral Resolution Reflectance: Opportunities and Challenges P. Nelson et al. 10.1029/2021JG006697
- Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance A. Shiklomanov et al. 10.5194/gmd-14-2603-2021
14 citations as recorded by crossref.
- The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0 J. Zhang et al. 10.5194/gmd-15-5107-2022
- Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land Y. Wang et al. 10.1029/2021MS002964
- Simulating Global Dynamic Surface Reflectances for Imaging Spectroscopy Spaceborne Missions: LPJ‐PROSAIL B. Poulter et al. 10.1029/2022JG006935
- ND-space: Normalized difference spectral mapping W. Philpot et al. 10.1016/j.rse.2021.112622
- Mapping foliar photosynthetic capacity in sub-tropical and tropical forests with UAS-based imaging spectroscopy: Scaling from leaf to canopy S. Liu et al. 10.1016/j.rse.2023.113612
- Reviews and syntheses: Remotely sensed optical time series for monitoring vegetation productivity L. Kooistra et al. 10.5194/bg-21-473-2024
- Towards uninterrupted canopy-trait time-series: A Bayesian radiative transfer model inversion using multi-sourced satellite observations D. Zhang & M. Dietze 10.1016/j.rse.2023.113475
- Linking Remote Sensing with APSIM through Emulation and Bayesian Optimization to Improve Yield Prediction H. Dokoohaki et al. 10.3390/rs14215389
- Simulating the Impacts of Drought and Warming in Summer and Autumn on the Productivity of Subtropical Coniferous Forests M. Xie et al. 10.3390/f13122147
- Extending the GOSAILT Model to Simulate Sparse Woodland Bi-Directional Reflectance with Soil Reflectance Anisotropy Consideration J. Cheng et al. 10.3390/rs14041001
- On the impact of canopy model complexity on simulated carbon, water, and solar-induced chlorophyll fluorescence fluxes Y. Wang & C. Frankenberg 10.5194/bg-19-29-2022
- Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET H. Dokoohaki et al. 10.5194/gmd-15-3233-2022
- Reducing model uncertainty of climate change impacts on high latitude carbon assimilation A. Rogers et al. 10.1111/gcb.15958
- Remote Sensing of Tundra Ecosystems Using High Spectral Resolution Reflectance: Opportunities and Challenges P. Nelson et al. 10.1029/2021JG006697
Latest update: 02 Nov 2024
Short summary
Airborne and satellite images are a great resource for calibrating and evaluating computer models of ecosystems. Typically, researchers derive ecosystem properties from these images and then compare models against these derived properties. Here, we present an alternative approach where we modify a model to predict what the satellite would see more directly. We then show how this approach can be used to calibrate model parameters using airborne data from forest sites in the northeastern US.
Airborne and satellite images are a great resource for calibrating and evaluating computer...
