摘要
大气纠正的目的是从遥感影像中去除大气影响,并反演获取地物真实反射率。介绍了一种逐像元对遥感影像进行大气纠正的算法,该算法基于6S(Second Simulation of the Satellite Signal in the Solar Spectrum)大气辐射传输模型计算建立的查找表(look-up table),并利用地面暗目标(dark object)进行陆地气溶胶光学厚度的自动反演,由于气溶胶的分布具有空间连续性,在获取地面暗目标气溶胶光学厚度值后,通过空间插值的方法计算影像中非暗目标像元的气溶胶光学厚度值,经过查找表二次插值计算,逐像元进行大气纠正并获取像元地表反射率值。以Landsat5遥感影像为例,介绍了算法流程,展示了大气纠正的结果。结果显示,利用查找表逐像元大气纠正的算法,能够在一定程度上去除云雾对影像的影响,更加精确的对遥感影像进行大气纠正并获取地物的真实反射率。
The objective of atmospheric correction is to retrieve the surface reflectance from remotely sensed imagery by removing the atmospheric effects. A new algorithm based on the look up table which founded by 6S model was introduced and used to derive the aerosol optical depth and retrieve surface reflectance from a Landsat5 imagery. Dark object algorithm was used to identify the dense dark vegetation and then the aerosol optical depth of those pixels was computed by interpolation from the look-up table automatically. A reverse distance interpolation was applied to all imagery and so every pixels got a aerosol optical depth value. The look-up table was used to derive atmospheric parameters and surface reflectance. The algorithm was applied to the Landsat5 imagery and the result shows that the atmospheric correction effect is good.
出处
《光学技术》
EI
CAS
CSCD
北大核心
2007年第1期11-15,共5页
Optical Technique
基金
国家自然科学基金资助项目(40471093)
北京市科技新星计划项目(2005A23)
国家攻关资助项目(门头沟区生态修复总体规划及技术方案研究与科技示范工程)
