Articles | Volume 15, issue 17
https://doi.org/10.5194/gmd-15-6919-2022
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, Kelong Chen, Chongyi E, Xiaoni You, Dongcai He, Liangbai Hu, Baokang Liu, Runke Wang, Yaya Shi, Chengxiu Li, and Fumei Liu

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Cited articles

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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.