基于主成分分析的CO2统计反演方法

二氧化碳（CO2）卫星遥感中，大气环境因素是影响反演精度的重要原因，目前反演条件通常限制在气溶胶光学厚度小于0.3的情况。我国大气气溶胶高值情况较为普遍，对大气条件的较高要求将严重影响我国CO2卫星遥感数据的应用能力。针对这种情况，利用基于主成分分析法对中国京津地区高气溶胶光学厚度的大气CO2反演，得到的CO2柱浓度与2013年、2014年GOSAT-Level2产品进行对比分析，均方根误差分别为0.65%和0.46%，相关性分别为0.77和0.93。

Statistic Retrieval Method of Carbon Dioxide Based on Principal Component Analysis

In the satellite remote sensing of carbon dioxide (CO2), atmospheric environmental factor is the important factor affecting the inversion accuracy. The inversion conditions is usually limited to the situation of the aerosol optical thickness less than 0.3. The higher requirement of the atmospheric conditions will seriously affect the application ability of our country's CO2 satellite remote sensing data. For this kind of situation, based on principal component analysis (PCA), atmospheric CO2 of Beijing and Tianjin areas of China is inversed of high aerosol optical thickness, the CO2 column concentration obtained is compared with the product of GOSAT - Level2 in 2013, 2014. The root mean square error is 0.65% and 0.46%, respectively, and the correlation is 0.77 and 0.93, respectively.