大气透过率是热红外遥感中的一个重要参数。针对前文构建的大气透过率模式,以我国环境灾害卫星HJ-1B红外相机IRS第4通道的大气透过率模式为例,利用辐射传输模型MODTRAN模拟水体辐亮度,对模式中的变量引入不同的误差,将模拟的辐亮度反演水温,分析不同气溶胶模型、水汽量、能见度和观测天顶角对反演水温的敏感性。并将该大气透过率模式用于HJ-1B/IRS热红外图像中,反演了2009年4月17日、21日、22日和25日太湖水温。研究结果表明:同一波段、不同气溶胶模型的大气透过率模式在反演温度时会产生不同的误差,以气溶胶模型为平流雾的最大、对流型的最小;大气透过率模式中3个变量的误差与温度反演的误差呈线性关系,即变量的误差越大,温度反演的误差也越大;以水汽量对温度反演最敏感,观测天顶角其次,能见度最弱。该大气透过率模式用于4天遥感图像反演中,除4月17日反演的误差稍高,均方根误差和平均相对误差分别为1.127℃和5.75%,其他3天的均方根误差都小于1℃、平均相对误差在5%以下,说明所建的大气透过率模式在热红外遥感中具有较高的应用精度。
Atmospheric transmittance is an important parameter in the thermal infrared remote sensing.For the atmospheric transmittance models in the previous paper, taking the transmittance model of the infrared camera(IRS) onboard chinese environment and disaster monitoring satellite(HJ-1B)as an example,the radiance at top atmosphere over waters was simulated, a series of error were brought to the variables in the atmospheric transmittance model, and the temperature from the simulated radiance was retrieved. Given that, the sensitivity of aerosol model, water vapor, visibility and view zenith affecting on retrieved temperature was analyzed. The atmospheric transmittance model was applied to 4 HJ/IRS thermal infrared images and the water surface temperature on April 17, 21, 22 and 25, 2009 was retrieved in lake Taihu, China. The results show that the atmospheric transmittance model within different aerosol models for any channel produce various errors during the temperature retrieving from the remote sensed radiance, that the error is the largest for the advective fog model and is the lowest for the tropospheric model, that the retrieved error of temperature displays the linear trend with the error of variables in the atmospheric transmittance models, the water vapor is the most susceptible for the temperature retrieving, the second for the view zenith and the third for visibility. When the atmospheric transmittance model is applied to HJ/IRS thermal infrared images for retrieving the water surface temperature, the error on April 17 is a little high which the root mean square error(RMSE)and the mean relative error(MRE)are1.127℃ and 5.75% respectively, while the RMSE on other 3 days is below 1℃ and their MRE is less than 5%.This illustrates that the atmospheric transmittance model have the perfect application accuracy in the thermal infrared remote sensing.