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.

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Cited articles

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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.