Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 5
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.
https://doi.org/10.5194/gmd-14-2603-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 5
Methods for assessment of models
 | 
12 May 2021
Methods for assessment of models |  | 12 May 2021

Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance

Alexey N. Shiklomanov, Michael C. Dietze, Istem Fer, Toni Viskari, and Shawn P. Serbin

Viewed

Total article views: 4,366 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,113 1,154 99 4,366 88 141
  • HTML: 3,113
  • PDF: 1,154
  • XML: 99
  • Total: 4,366
  • BibTeX: 88
  • EndNote: 141
Views and downloads (calculated since 12 Oct 2020)
Cumulative views and downloads (calculated since 12 Oct 2020)

Viewed (geographical distribution)

Total article views: 4,366 (including HTML, PDF, and XML) Thereof 4,119 with geography defined and 247 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 06 Dec 2025
Download
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.
Read more
Share