Estimation and analysis of net primary Productivity of Ruoergai wetland in China for the recent 10 years based on remote sensing

Ruoergai wetland is the biggest plateau peat wetland in the world. It plays an important role in the ecological construction and environmental protection for the upper reaches of Yangtze and yellow river. Using remote sensing technology to monitor annual and inter-annual NPP change is the key to evaluate the health condition of ecosystem of the wetland. In this study, an accuracy evaluation and model optimization function were designed to optimize the Light Utilization Efficiency (LUE) parameter of Carnegie-Ames-Stanford Approach (CASA) model, and optimized model was used to estimate and analysis spatial distribution and seasonal and annual variation of the Net Primary Productivity (NPP) for the recent 10 years of Ruoergai wetland. Results showed that, (1) Maximum light utilization efficiency used in the original model cannot reflect spatial heterogeneity of vegetation distribution. Parameter of CASA model need to be further optimized when applied in the regional scale. (2) Spatial distribution pattern of NPP in Ruoergai wetland is highly correlated with topography factor. (3) NPP of Ruoergai wetland shows a slight decline trend on the time series for the recent 10 years and area of the slight decline trend is about 67%, and there are 22% grassland who's NPP is severe decrease.