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Published： 07 October 2023 ，
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李国荣，何玉青，胡秀清，王俊伟.2023.基于IR-MAD不变像元的风云三号光学成像仪同平台交叉定标.遥感学报，27（10）： 2337-2349
Li G R， He Y Q， Hu X Q， Wang J W. 2023. Cross calibration technology for the same platform of FY-3 optical imager based on IR-MAD no-change pixels. National Remote Sensing Bulletin， 27（10）：2337-2349
现有基于稳定目标场的交叉定标方法受限于卫星同步过境人工选取定的伪不变目标且靶场光谱特性较为单一，难以进行多频次、高精度的交叉定标，而传感器的精确在轨校准对其数据产品的有效性至关重要。本文提出了一种基于迭代重加权多变量变化检测（IR-MAD）的交叉定标方法，以风云三号B星（FY-3B）光学成像仪的中分辨率成像光谱仪（MERSI）为参考基准，展开对同平台的可见光红外扫描辐射计（VIRR）的交叉定标研究。该方法通过IR-MAD算法自动识别两探测器同时相场景中的不变像元，基于不变像元的反射率信息，经过光谱匹配和正交回归获得交叉定标系数。本文以FY-3B/VIRR、MERSI中国西北地区和北非地区数据展开研究，获取长时间序列的定标斜率系数。结果表明，IR-MAD方法与业务定标、敦煌沙漠场地定标结果有很好的一致性，VIRR经定标校正后与MERSI的辐射信息相对偏差优于2%，中国西北地区和北非地区获取的IR-MAD交叉定标结果吻合（多数通道优于2%）。此方法可在卫星观测场景内自动高效的选取伪不变目标，并基于所选取的伪不变目标实现交叉定标。
During the operation of the satellite in orbit
the radiation detection performance and stability of the sensor changes
and the accuracy of the acquired radiation observation signal decreases. Accurate on-orbit calibration of sensors is crucial to ensure the validity of their data products. The stable target site based cross calibration method is limited by the pseudo-invariant target
which is manually selected by the satellite synchronous transit and has simple spectral characteristics. Thus
multi-frequency and high-precision cross calibration are difficult to carry out.
Method
2
This study proposes a cross calibration method based on iterative reweighted multivariate alteration detection (IR-MAD). Taking the FY-3B medium resolution spectral imager (MERSI) as the reference
the cross-calibration of visible and infrared radiometer (VIRR) on the same platform is studied. Initially
the IR-MAD algorithm linearly combines the simultaneous multi-channel images of the two sensors to construct canonical correlation variables and performs canonical correlation analysis to eliminate the correlation between different channels of a single sensor and unmatched channels of different sensors. Then
through multiple probability reweighting iterations
the IR-MAD algorithm can automatically identify the no-change pixels (NCPs) in the same phase scene of the two sensors. The radiance of the NCPs has the largest linear correlation between VIRR and MERSI matching channels. The cross-calibration coefficients can be obtained using a linear regression model based on the apparent reflectance information of the NCPs by correcting the spectral differences between matched channels of two sensors. This study implements this procedure with data from Northwest China region and North Africa region and compares it with the calibration results obtained from other related studies.
Result
2
Experimental results show that the proposed method is consistent with the operational calibration and the Dunhuang desert site calibration. The relative deviation of the radiometric information between VIRR and MERSI after calibration exceeds 2%. The cross-calibration results of IR-MAD obtained in northwest China and north Africa are consistent (most channels are better than 2%)
verifying the generalization and stability of this method. The long-time sequence results show a correlation between the channel response decay trend and wavelength. In general
the shorter wavelength indicates a more serious decay. In addition
some seasonal fluctuations are found in the relative calibration slope time series of near-infrared and shortwave infrared channels.
Conclusion
2
This method can automatically and efficiently select pseudo-invariant targets in satellite observation scenes and realize high precision cross calibration based on the selected pseudo-invariant targets. It is applicable to the re-calibration of historical satellite data and the relative response monitoring of sensors on the same platform. Our future work will focus on the application of algorithms in different platforms and nonlinear problems.
可见光红外扫描辐射计中分辨率成像光谱仪迭代重加权多变量变化检测不变像元交叉定标
Visible and Infra-Red Radiometer (VIRR)Medium Resolution Spectral Imager (MERSI)IR-MADno-change pixelscross calibration
Canty M J and Nielsen A A. 2008. Automatic radiometric normalization of multitemporal satellite imagery with the iteratively re-weighted MAD transformation. Remote Sensing of Environment, 112(3): 1025-1036 [DOI: 10.1016/j.rse.2007.07.013http://dx.doi.org/10.1016/j.rse.2007.07.013]
Canty M J, Nielsen A A and Schmidt M. 2004. Automatic radiometric normalization of multitemporal satellite imagery. Remote Sensing of Environment, 91(3/4): 441-451 [DOI: 10.1016/S0034-4257(04)00120-8http://dx.doi.org/10.1016/S0034-4257(04)00120-8]
Du Y, Teillet P M and Cihlar J. 2002. Radiometric normalization of multitemporal high-resolution satellite images with quality control for land cover change detection. Remote sensing of Environment, 82(1): 123-134 [DOI: 10.1016/s0034-4257(02)00029-9http://dx.doi.org/10.1016/s0034-4257(02)00029-9]
He L L, Hu X Q, Wang L, Chen L, Xu N and Zhang P. 2020. Calibration tracking of the optical payload based on automatic methods. Spacecraft Recovery and Remote Sensing, 41(6): 103-113
何灵莉, 胡秀清, 王玲, 陈林, 徐娜, 张鹏. 2020. 基于自动化方法的光学载荷定标跟踪. 航天返回与遥感, 41(6): 103-113 [DOI: 10.3969/j.issn.1009-8518.2020.06.010http://dx.doi.org/10.3969/j.issn.1009-8518.2020.06.010]
Hu X Q, Liu J J, Sun L, Rong Z G, Li Y, Zhang Y, Zheng Z J, Wu R H, Zhang L J and Gu X F. 2010. Characterization of CRCS Dunhuang test site and vicarious calibration utilization for Fengyun (FY) series sensors. Canadian Journal of Remote Sensing, 36(5): 566-582 [DOI: 10.5589/m10-087http://dx.doi.org/10.5589/m10-087]
Hu X Q, Sun L, Liu J J, Ding L, Wang X H, Li Y, Zhang Y, Xu N and Chen L. 2013. Calibration for the solar relfective bands of medium resolution spectral imager onboard FY-3A. Advances in Meteorological Science and Technology, (4): 71-83
胡秀清, 孙凌, 刘京晶, 丁雷, 王向华, 李元, 张勇, 徐娜, 陈林. 2013. 风云三号A星中分辨率光谱成像仪反射太阳波段辐射定标. 气象科技进展, (4): 71-83 [DOI: 10.3969/j.issn.2095-1973.2013.04.008http://dx.doi.org/10.3969/j.issn.2095-1973.2013.04.008]
Hu X Q, Wang L, Wang J W, He L L, Chen L, Xu N, Tao B C, Zhang L, Zhang P and Lu N M. 2020. Preliminary selection and characterization of pseudo-invariant calibration sites in northwest China. Remote Sensing, 12(16): 2517 [DOI: 10.3390/rs12162517http://dx.doi.org/10.3390/rs12162517]
Lacherade S, Fougnie B, Henry P and Gamet P. 2013. Cross calibration over desert sites: description, methodology, and operational implementation. IEEE Transactions on Geoscience and Remote Sensing, 51(3): 1098-1113 [DOI: 10.1109/TGRS.2012.2227061http://dx.doi.org/10.1109/TGRS.2012.2227061]
Lü J Y, Chen L, He M Y and Hu X Q. 2017. Degradation analysis for FY3B/VIRR reflective solar bands based on the Dunhuang radiometric calibration site. Spectroscopy and Spectral Analysis, 37(8): 2397-2401
吕佳彦, 陈林, 何明元, 胡秀清. 2017. 基于敦煌辐射校正场的FY3B/VIRR反射太阳波段衰减分析. 光谱学与光谱分析, 37(8): 2397-2401 [DOI: 10.3964/j.issn.1000-0593(2017)08-2397-05http://dx.doi.org/10.3964/j.issn.1000-0593(2017)08-2397-05]
Moran M S, Jackson R D, Slater P N and Teillet P M. 1992. Evaluation of simplified procedures for retrieval of land surface reflectance factors from satellite sensor output. Remote Sensing of Environment, 41(2/3): 169-184 [DOI: 10.1016/0034-4257(92)90076-Vhttp://dx.doi.org/10.1016/0034-4257(92)90076-V]
Nielsen A A, Conradsen K and Simpson J J. 1998. Multivariate alteration detection (MAD) and MAF postprocessing in multispectral, bitemporal image data: new approaches to change detection studies. Remote Sensing of Environment, 64(1): 1-19 [DOI: 10.1016/S0034-4257(97)00162-4http://dx.doi.org/10.1016/S0034-4257(97)00162-4]
Obata K, Tsuchida S, Yamamoto H and Thome K. 2017. Cross-calibration between ASTER and MODIS visible to near-infrared bands for improvement of ASTER radiometric calibration. Sensors, 17(8): 1793 [DOI: 10.3390/s17081793http://dx.doi.org/10.3390/s17081793]
Qi X D and Yue J B. 2016. VIRR image cloud detection based on image enhancement and comprehensive decision-making. Journal of Henan Polytechnic University (Natural Science), 35(6): 802-809
齐修东, 岳继博. 2016. 基于影像增强和综合决策的VIRR影像云检测. 河南理工大学学报(自然科学版), 35(6): 802-809 [DOI: 10.16186/j.cnki.1673-9787.2016.06.009http://dx.doi.org/10.16186/j.cnki.1673-9787.2016.06.009]
Schmidt M, King E A and McVicar T R. 2008. A method for operational calibration of AVHRR reflective time series data. Remote Sensing of Environment, 112(3): 1117-1129 [DOI: 10.1016/j.rse.2007.07.015http://dx.doi.org/10.1016/j.rse.2007.07.015]
Sun L, Guo M H, Xu N, Zhang L J, Liu J J, Hu X Q, Li Y, Rong Z G and Zhao Z H. 2012. On-orbit response variation analysis of FY-3 MERSI reflective solar bands based on Dunhuang site calibration. Spectroscopy and Spectral Analysis, 32(7): 1869-1877
孙凌, 郭茂华, 徐娜, 张立军, 刘京晶, 胡秀清, 李元, 戎志国, 赵泽会. 2012. 基于敦煌场地定标的FY-3 MERSI反射太阳波段在轨响应变化分析. 光谱学与光谱分析, 32(7): 1869-1877 [DOI: 10.3964/j.issn.1000-0593(2012)07-1869-09http://dx.doi.org/10.3964/j.issn.1000-0593(2012)07-1869-09]
Sun L, Hu X Q, Guo M H and Xu N. 2013. Multisite calibration tracking for FY-3A MERSI solar bands. Advances in Meteorological Science and Technology, (4): 84-96
孙凌, 胡秀清, 郭茂华, 徐娜. 2013. 风云三号A星中分辨率光谱成像仪反射太阳波段的多场地定标跟踪. 气象科技进展, (4): 84-96 [DOI: 10.3969/j.issn.2095-1973.2013.04.009http://dx.doi.org/10.3969/j.issn.2095-1973.2013.04.009]
Sun L and Li X J. 2014. The recalibration of FY-3 MERSI reflective solar bands//Proceedings Volume 9298, International Symposium on Optoelectronic Technology and Application 2014: Imaging Spectroscopy; and Telescopes and Large Optics. Beijing: SPIE: 159-169 [DOI: 10.1117/12.2072169http://dx.doi.org/10.1117/12.2072169]
Tong J J, Qiu K M, Li X W and Yang Z D. 2005. Radiometric cross-calibration of the FY1D/VIRR and EOS/MODIS in the visible and near-infrared spectral bands. Journal of Remote Sensing, 9(4): 349-356
童进军, 邱康睦, 李小文, 杨忠东. 2005. 利用EOS/MODIS交叉定标FY1D/VIRR可见光—近红外通道. 遥感学报, 9(4): 349-356 [DOI: 10.11834/jrs.20050451http://dx.doi.org/10.11834/jrs.20050451]
Wang J W, Hu X Q, He Y Q and Gao K. 2019. Response degradation analysis of Fengyun-3A medium-resolution spectral imager based on intelligent detection of invariant pixels. Acta Optica Sinica, 39(9): 0912001
王俊伟, 胡秀清, 何玉青, 高昆. 2019. 基于智能检测不变像元的FY-3A/MERSI仪器响应衰变分析. 光学学报, 39(9): 0912001 [DOI: 10.3788/AOS201939.0912001http://dx.doi.org/10.3788/AOS201939.0912001]
Wang L, Hu X Q, Chen L and He L L. 2018. Consistent calibration of VIRR reflective solar channels onboard FY-3A, FY-3B, and FY-3C using a multisite calibration method. Remote Sensing, 10(9): 1336 [DOI: 10.3390/rs10091336http://dx.doi.org/10.3390/rs10091336]
Wang M, Zhou S D, He M Y and Chen X Y. 2015. Characterization and calibration method of satellite sensor radiometric calibration site. Geomatics and Spatial Information Technology, (7): 24-27
王敏, 周树道, 何明元, 陈晓颖. 2015. 国内外卫星遥感器辐射定标场地特性比较分析. 测绘与空间地理信息, (7): 24-27 [DOI: 10.3969/j.issn.1672-5867.2015.07.009http://dx.doi.org/10.3969/j.issn.1672-5867.2015.07.009]
Wei W. 2017. Research on Long Time Series Calibration of Satellite Sensor Based on Global Calibration Site Network. Hefei: University of Science and Technology of China
韦玮. 2017. 基于全球定标场网的卫星遥感器长时间序列定标方法研究. 合肥: 中国科学技术大学
Xu N, Chen L, Hu X Q, Zhang L Y and Zhang P. 2014. Assessment and correction of on-orbit radiometric calibration for FY-3 VIRR thermal infrared channels. Remote Sensing, 6(4): 2884-2897 [DOI: 10.3390/rs6042884http://dx.doi.org/10.3390/rs6042884]
Zhong B, Yang A, Wu S, Li J, Liu S and Liu Q. 2018. Cross-calibration of reflective bands of major moderate resolution remotely sensed data. Remote Sensing of Environment, 204: 412-423 [DOI: 10.1016/j.rse.2017.10.014http://dx.doi.org/10.1016/j.rse.2017.10.014]
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