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A Practical Approach to Landsat 8 TIRS Stray Light Correction Using Multi-Sensor Measurements

机译:利用多传感器测量的实用方法徘徊8 TIRS杂散校正

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摘要

It has been noticed that the Landsat 8 Thermal Infrared Sensor (TIRS) had an issue with stray light since its launch in 2013. This artifact is due to out-of-field radiance that scatters onto the TIRS focal plane. Much effort has been taken to develop an algorithm to remove this artifact. One proposed approach involves using TIRS data itself (referred to as TIRS-on-TIRS) to retrieve the true sensor-reaching radiance. This approach has been proven to be operational and supports the TIRS Collection-1 product. A methodology of calibrating the TIRS sensor with information from the Geostationary Operational Environmental Satellite (GOES) instrument may optimally reduce the stray light effect for special cases where there is a large temperature contrast between the edge of the TIRS image and out-of-field radiance (referred to as GOES-on-TIRS). This paper illustrates a GOES to TIRS conversion (GTTC) algorithm with the North American Regional Reanalysis (NARR) data to support the GOES-on-TIRS method. Results show this GOES_TIRS correction method performs similarly to the TIRS Collection-1 product. Additionally, a simplified methodology is proposed to improve the GOES data processing which can operationalize the GOES-on-TIRS algorithm. Results also show that, using the proposed algorithm with these special cases, the maximum difference between the Collection-1 product and the GOES-on-TIRS correction results in a temperature difference from 0.5% to 0.7%.
机译:已经注意到,自2013年推出以来,Landsat 8热红外传感器(TIRS)具有杂散光的问题。该工件是由于散发到TIRS焦平面上的场外发光。已经采取了很多努力来开发算法以删除此工件。一种提出的方​​法涉及使用TIRS数据本身(称为TIRS-ON-TIRS)来检索真正的传感器达到辐射。此方法已被证明是可操作的,并支持TIRS Collection-1产品。利用来自地球静止操作环境卫星(GUSE)仪器的信息校准TIRS传感器的方法可以最佳地降低对TIR图像边缘的高温对比的特殊情况下的杂散光效应,以及对外辐射的外辐射之间存在大的温度对比(被称为持续的TIRS)。本文说明了与北美区域重新分析(Narr)数据的TIRS转换(GTTC)算法来支持TIR-TIRS方法。结果显示此Good_Tirs校正方法与TIRS Collection-1产品类似地执行。另外,提出了一种简化的方法来改进可以运行延时算法的数据处理。结果还表明,使用所提出的算法具有这些特殊情况,收集-1产品与延期校正的最大差异导致温度差为0.5%至0.7%。

著录项

  • 作者

    Yue Wang; Emmett Ientilucci;

  • 作者单位
  • 年度 2018
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
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