Articles | Volume 15, issue 17
Geosci. Model Dev., 15, 6919–6933, 2022
https://doi.org/10.5194/gmd-15-6919-2022
Geosci. Model Dev., 15, 6919–6933, 2022
https://doi.org/10.5194/gmd-15-6919-2022
Model description paper
13 Sep 2022
Model description paper | 13 Sep 2022

Improved CASA model based on satellite remote sensing data: simulating net primary productivity of Qinghai Lake basin alpine grassland

Chengyong Wu et al.

Viewed

Total article views: 1,480 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,146 299 35 1,480 78 9 12
  • HTML: 1,146
  • PDF: 299
  • XML: 35
  • Total: 1,480
  • Supplement: 78
  • BibTeX: 9
  • EndNote: 12
Views and downloads (calculated since 10 Mar 2022)
Cumulative views and downloads (calculated since 10 Mar 2022)

Viewed (geographical distribution)

Total article views: 1,480 (including HTML, PDF, and XML) Thereof 1,354 with geography defined and 126 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 30 Jan 2023
Download
Short summary
The traditional Carnegie–Ames–Stanford Approach (CASA) model driven by multisource data such as meteorology, soil, and remote sensing (RS) has notable disadvantages. We drove the CASA using RS data and conducted a case study of the Qinghai Lake basin alpine grassland. The simulated result is similar to published and measured net primary productivity (NPP). It may provide a reference for simulating vegetation NPP to satisfy the requirements of accounting carbon stocks and other applications.