利用氧气和水汽吸收波段暗像元假设的MERIS影像二类水体大气校正方法

摘 要:MERIS数据以其更为合理的水色波段设置和300m较高的空间分辨率,在内陆湖泊水环境遥感监测中有较大的应用潜力, 对其进行有效的大气校正则是水环境参数定量化反演的前提。以太湖为研究区, 研究基于氧气和水汽吸收波段的暗象元假设, 改进传统的近红外波段暗像元假设的大气校正方法。采用MERIS L2p数据辅助获取湖区气溶胶参数, 并利用2007年11月11日、2008年11月20日以及2009年4月25日三景MERIS影像进行方法验证。结果表明, 该方法能够快速、有效地完成MERIS影像的大气校正, 与地面准同步实测数据相比, 三次校正的RMSP都在25%以下; 与BEAM自带的二类水体大气校正算法、气溶胶厚度辅助的6S大气校正以及改进的暗象元算法进行精度比较, 表明该算法校正精度较高。由于该算法不需要同步实测气溶胶数据, 因此具有一定的适用性。

Atmospheric correction of MERIS data on the black pixel assumption in oxygen and water vapor absorption bands

Abstract: The Medium Resolution Imaging Spectrometer (MERIS) sensor, with the reasonable ocean color bands and the high spatial resolution of 300 m, has large potential in the monitoring of inland waters. To quantitatively retrieve water environmental parameters by using remote sensing image, accurate atmospheric correction becomes very significant. In the present study, the oxygen and water vapor absorption bands were used to improve the traditional black pixels assumption which used the near infrared bands. First, the method of calculating aerosol parameters through MERIS L2p data was developed; then, this method was assessed by using MERIS L1p data recorded on November 11th, 2007, November 20th, 2008 and April 25th, 2009. Meanwhile, the in situ measured data were used to compare with the modeled values. The obtained results show that the proposed method is efficacious with RMSP less than 25%. Another important work was also done, that is, comparing the proposed method with other algorithms such as case II atmospheric correction algorithm embedded in MERIS (BEAM) processor, Aerosol thickness aided 6S and modified black pixels algorithm. The results indicate that the proposed algorithm has certain applicability considering its independence of synchronous measured aerosol data.