基于GF-4卫星的长三角城市群PM_(2.5)遥感反演

Remote estimation of PM_(2.5) based on GaoFen-4 satellite data in the Yangtze River Delta urban agglomeration

基于静止卫星高分四号(GF-4)遥感数据,利用6SV辐射传输模型与暗目标算法进行高空间分辨率气溶胶光学厚度(AOD)遥感反演;在此基础上,结合地面监测站大气细颗粒物(PM_(2.5))浓度、气象资料等数据,采用物理订正方法及线性混合效应模型,实现长三角城市群区域大尺度空间连续的PM_(2.5)浓度遥感反演;最后利用十折交叉验证法对反演精度进行验证.结果表明:GF-4反演的AOD结果分辨率较高,空间连续性好,与AERONET地基监测相关性R达到0.82;利用GF-4 AOD的PM_(2.5)估算模型精度较高,模型估算PM_(2.5)浓度与地面实测数据拟合度R^(2)为0.74;在分春夏秋冬4个季节建模情景下,交叉验证R^(2)依次为0.67,0.59,0.63和0.72,平均绝对误差MAE为10.40,7.42,10.10,13.34μg/m^(3),表明GF-4卫星适用于区域PM_(2.5)浓度监测.

This paper used 6 SV model and dark target algorithm to retrieve AOD with a high spatial resolution based on GaoFen-4(GF-4) geostationary satellite data. Afterwards, combined with the PM_(2.5)concentration data of the ground air quality observation sites, meteorological factors and other data, physical correction methods and linear mixed effects(LME) model were used to monitor the large-scale and spatial continuous PM_(2.5)concentration in the Yangtze River Delta urban agglomeration(YRDUA). The results showed that the retrieved GF-4 AOD has good spatial resolution and spatial continuity, and the correlation coefficient(R) with AERONET ground-based monitoring data reached 0.82. The LME model based on GF-4 AOD showed a good agreement between the estimated PM_(2.5)concentration and the in situ observed values(R^(2)=0.74). The 10-fold cross-validation R^(2) of spring, summer,autumn and winter were 0.67, 0.59, 0.64 and 0.72, respectively;and the mean absolute error(MAE) were 10.40, 7.42, 10.10 and 13.34μg/m^(3), respectively, which indicates that GF-4 can be used for regional PM_(2.5)concentration monitoring.