Realization Of Estimation System And Analysis Of Net Primary Production Based On Fen Yun Geostationary Satellite

Net Primary Productivity(NPP)refers to the remainder of the total organic matter produced by photosynthesis per unit time and unit area after depletion of autotrophic respiration.NPP can effectively reflect the effects of temperature,precipitation,and solar radiation on vegetation growth.It is of great significance for assessing the health of terrestrial ecosystems and analyzing the global carbon cycle process.At present,NPP uses data from foreign polar orbit satellite.Compared with polar orbiting satellites,geostationary satellites have the advantages of highfrequency observations and a wide coverage area,which is convenient for removing cloud cover to obtain surface information.The remote sensing capabilities of domestic satellites are also continuously improved.Based on the visible and infrared data and surface temperature data of domestic geostationary satellites,combined with land cover type distribution data and digital elevation data,this study uses the improved CASA(Carnegie Ames Stanford Approach)model to develop an NPP estimation system based on domestic geostationary satellites.The quality of the data,products,and final NPP results was carefully evaluated.Later,according to the climate of China,the response of vegetation NPP in different regions to changes in moisture,temperature,solar radiation,and vegetation was studied,which proved that domestic geostationary satellites can contribute to the study of the global carbon cycle and expanding the use of domestic satellites.Main tasks are as follows:(1)Design and implementation of NPP estimation system based on domestic satellites.For domestic geostationary satellites,using Java and Python languages,a vegetation primary productivity estimation system based on domestic geostationary satellites was implemented,and optimized for the characteristics of large amounts of geostationary satellite data.The powerful system has a friendly interface and high processing efficiency,which can promote the application of domestic geostationary satellite data.(2)The domestic geostationary satellite data and the NPP simulated by the improved CASA model are evaluated.Through comparison with MODIS data,it is found that during the research period,the correlation coefficients of NDVI and MOD13A2 products based on Fengyun-4 data are greater than 0.6,and the cloud content is generally lower than MOD13A2;the correlation coefficients of FY-2G surface temperature products and MOD11A2 are greater than 0.4,90% of the time the correlation coefficient is greater than 0.6,the average value of the correlation coefficient is 0.7;on the total amount of NPP,based on the domestic geostationary satellite NPP and MO17A2 H product correlation coefficient is 0.78,the root mean square error is 46.38 Mt.The two are in good agreement in terms of total volume,and the transportation volume is also lower than that of MOD17A2 H products.(3)The driving factors of NPP changes in various regions of China are analyzed.According to the climate conditions,China's land area is divided into northern region,southern region,Qinghai-Tibet region,and northwestern region.After analyzing the response of each region to moisture,temperature,vegetation,and solar radiation,.It is found that the vegetation NPP in the northern region is sensitive to the water and temperature caused by the change of sensons,followed by the northwestern region;the southern region and Qinghai-Tibet regions are less sensitive to changes in temperature,moisture,and vegetation;After the analysis of the correlation between vegetation NPP and solar radiation values,we found that Vegetation NPP will not respond very differently to the change of solar radiation due to location or climate.