基于稳定场地的太阳反射波段基准传递定标及其不确定性评估方法
Cross Calibration Over Site and Uncertainty Assessment for Reflective Solar Bands
- 2023年 页码：1-19
网络出版日期： 2023-02-08
DOI： 10.11834/jrs.20232095
扫 描 看 全 文
浏览全部资源
扫码关注微信
摘要
空间辐射测量基准作为未来卫星定标的重要标准，为卫星数据的定量化应用提供了重要保障。通过传递定标方法实现辐射基准的传递可以提高卫星遥感器观测数据的整体精度。基于稳定场地的交叉定标作为太阳反射波段传递定标的一种主要方法，因其选定了目标均匀且反射特性较稳定的场地作为辐射基准传递对象，具有可靠性高、稳定性好、传递链条可追溯等优点。以利比亚场地为传递目标，提出一套适合于太阳反射波段的传递定标方法及其不确定性分析方案，系统分析传递定标方法的不确定性，并通过不确定性的敏感性分析给出最优的场地交叉定标的匹配方案。以气象卫星中分辨率光谱成像仪为例，以FY-3D MERSI-II和AQUA MODIS为代理数据，针对引入不确定性的主要来源：几何、时间、空间、光谱，利用大气辐射传输模型与双向反射分布函数构建不确定性分析模型，并通过蒙特卡罗方法多次模拟分析出各匹配条件对不确定性影响的敏感性，以利比亚场地为例，以各项不确定性小于1%作为约束，确定场地交叉定标匹配阈值：两遥感器观测天顶角之差应小于±7°，太阳天顶角之差小于±6°，相对方位角之差小于±15°，气溶胶厚度小于0.39，观测场地均匀性小于0.02，此条件下各通道总传递定标不确定性控制在1.5%，定标频次平均一月一次。
Abstract
Owing to the stability of Pseudo-Invariation Calibration Sites(PICS)
it contributes significantly to the improvement of calibration accuracy. The number of PICS is increasing as the work to continues to advance. Therefore
the frequency of cross calibrations based on dessert sites has been significantly increased. It is necessary to establish a generic site-based cross calibration as well as uncertainty analysis method to confirm calibration uncertainties for different sites.The aim of our study is to improve the overall accuracy of satellite remote sensor observations
by developing cross calibration method over desert site. In this paper
a cross calibration and uncertainty assessment scheme aims at solar bands is described
and the optimal matching scheme of the cross calibration is given by sensitivity analysis of the uncertainty.With image data of Libya site from MODIS and MERSI-II
the main uncertainty contributors are found in the geometric
temporal
spatial
and spectral domain. For these four aspects
the uncertainty analysis model is independently constructed using the atmospheric radiative transfer model and the bi-directional reflectance distribution function. The sensitivity of each matching condition to the effect of uncertainty is multiply simulated by Monte Carlo method.The geometric and atmospheric distribution patterns of satellite matching data were summarized
through statistically analyzing the matching data of MODIS and MERSI-II over Libya sites in 2020. The probability distribution density(PDF) of the matching condition is used as the input condition
and the discrete distribution of the relative deviation of Top-Of-Atmosphere (TOA) reflectance is obtained by the uncertainty analysis model. The standard deviation of the distribution of relative deviations of TOA reflectance is statistically considered as the standard uncertainty. After independent analysis of each factor of uncertainty
the total uncertainty is obtained by Root-Sum-Squares method.The total uncertainty of each channel could be controlled under 1.5%(at
<math id="M1"><mi>k</mi><mtext> </mtext><mo>=</mo><mtext> </mtext><mn mathvariant="normal">1</mn></math>
http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=39590369&type=
http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=39590365&type=
7.36600018
2.37066650
)
when the difference of sensor zenith angles between the two remote sensors should be less than ±7°
the difference between the solar zenith angles less than ±6°
the aerosol thickness less than 0.39
and the uniformity of the observation site less than 0.02. The results between the MODIS reflectance and the digital number (DN) recorded by MERSI reveal a good linear relationship. This cross-calibration result is also in the range of 0.5%~1.5% accuracy for each band compared to operational calibrations. Even though we only applied the algorithm to MERSI-II as a demonstration
our algorithm should be applicable to other sensors with few modifications.
关键词
不确定性场地交叉定标蒙特卡罗方法反射波段中分辨率光谱成像仪
Keywords
uncertaintycross calibrationMonte Carlo methodreflection bandmedium resolution imaging spectroradiometer
references
Aisheng, Xiong, Xiaoxiong, et al. Characterization of Terra and Aqua MODIS VIS, NIR, and SWIR Spectral Bands' Calibration Stability.[J]. IEEE Transactions on Geoscience & Remote Sensing, 2013.[DOI 10.1109/TGRS.2012.2226588http://dx.doi.org/10.1109/TGRS.2012.2226588]
Chander G , Mishra N , Helder D L , et al. Applications of Spectral Band Adjustment Factors (SBAF) for Cross-Calibration[J]. IEEE Transactions on Geoscience & Remote Sensing, 2013a, 51(3):1267-1281.[DOI 10.1109/TGRS.2012.2228007http://dx.doi.org/10.1109/TGRS.2012.2228007]
Chander G , Hewison T J , Fox N , et al. Overview of Intercalibration of Satellite Instruments[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013b, 51(3):1056-1080. [DOI 10.1109/tgrs.2012.2228654http://dx.doi.org/10.1109/tgrs.2012.2228654]
Chander G, Helder D L, Aaron D, et al. Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 51(3): 1282-1296. [DOI 10.1109/TGRS.2012.2228008http://dx.doi.org/10.1109/TGRS.2012.2228008]
Chen J, He X, Liu Z, et al. An approach to cross-calibrating multi-mission satellite data for the open ocean[J]. Remote Sensing of Environment, 2020, 246: 111895. [DOI 10.1016/j.rse.2020.111895http://dx.doi.org/10.1016/j.rse.2020.111895]
Doelling D.R., Bhatt R., Morstard D., Scarino B., 2011. Algorithm Theotical Basis Document (ATBD) for Ray-Matching Technique of Calibrating GEO Sensors with Aqua-MODIS for GSICS. ATBD, NASA-Langley, SSAI, August 19, 2011.
Fox N, Kaiser-Weiss A, Schmutz W, et al. Accurate radiometry from space: an essential tool for climate studies[J]. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2011, 369(1953): 4028-4063. [DOI 10.1098/rsta.2011.0246http://dx.doi.org/10.1098/rsta.2011.0246]
Fox N, Paul Green,Helen Brindley,Jacqueline Russell,Dave Smith,Daniel Lobb,Michael Cutter,Andrew Barnes. Traceable radiometry underpinning terrestrial and heliostudies (truths): a bencmark mission for climate[P]. International Conference on Space Optics,2017. [DOI 10.1117/12.2304220]
Gitelson A A, Dall'Olmo G, Moses W, et al. A simple semi-analytical model for remote estimation of chlorophyll-a in turbid waters: Validation[J]. Remote Sensing of Environment, 2008, 112(9): 3582-3593. [DOI 10.1016/j.rse.2008.04.015http://dx.doi.org/10.1016/j.rse.2008.04.015]
Gong H,Tian G,Yu T, et al. Vicarious radiometric calibration and validation of CBERS02B CCD data [J]. Journal of Remote Sensing,2010,14(01):1-12.
巩慧,田国良,余涛,顾行发,高海亮,李小英.CBERS02B卫星CCD相机在轨辐射定标与真实性检验[J].遥感学报,2010,14(01):1-12.[DOI CNKI:SUN:YGXB.0.2010-01-003]
Gordon H R, Zhang T. How well can radiance reflected from the ocean–atmosphere system be predicted from measurements at the sea surface?[J]. Applied Optics, 1996, 35(33): 6527-6543. [DOI 10.1364/ao.35.006527http://dx.doi.org/10.1364/ao.35.006527]
Gorrono J , Banks A C , Fox N P , et al. Radiometric inter-sensor cross-calibration uncertainty using a traceable high accuracy reference hyperspectral imager[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 130:393-417. [DOI 10.1016/j.isprsjprs.2017.07.002http://dx.doi.org/10.1016/j.isprsjprs.2017.07.002]
Hewison T J, Wu X, Yu F, et al. GSICS inter-calibration of infrared channels of geostationary imagers using Metop/IASI[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(3): 1160-1170. [DOI 10.1109/TGRS.2013.2238544http://dx.doi.org/10.1109/TGRS.2013.2238544]
Huang H, Yi W, Qiao Y, et al. In-orbit radiometric calibration method of "Tianmai-1" satellite[J]. Journal of Remote Sensing,2012,16(S1):22-27.
黄红莲,易维宁,乔延利,杜丽丽.“天绘一号”卫星在轨辐射定标方法[J].遥感学报,2012,16(S1):22-27.[DOI CNKI:SUN:YGXB.0.2012-S1-007]
Lacherade S , Fougnie B , Henry P , et al. Cross Calibration Over Desert Sites: Description, Methodology, and Operational Implementation[J]. IEEE Transactions on Geoscience & Remote Sensing, 2013, 51(3):1098-1113. [DOI 10.1109/TGRS.2012.2227061http://dx.doi.org/10.1109/TGRS.2012.2227061]
Liu J J, Li Z, Qiao Y L, et al. A new method for cross-calibration of two satellite sensors[J]. International Journal of Remote Sensing, 2004, 25(23): 5267-5281. [DOI 10.1080/01431160412331269779http://dx.doi.org/10.1080/01431160412331269779]
Li X , Feng G , Chen L , et al. Derivation and validation of a new kernel for kernel-driven BRDF models[J]. International Society for Optics and Photonics, 1999, 3868: 368-379.[DOI 10.1117/12.373123http://dx.doi.org/10.1117/12.373123]
Lu N, Ding L, Zheng X, et al. Introduction of the radiometric benchmark satellite being developed in China for remote sensing [J]. Journal of Remote Sensing,2020,24(06):672-680.
卢乃锰,丁雷,郑小兵,叶新,李传荣,吕达仁,张鹏,胡秀清,周成虎,尤政,房建成,龚建雅,蒋兴伟,李建军,马灵玲,徐娜.中国空间辐射测量基准技术[J].遥感学报,2020,24(06):672-680.[DOI 10.11834/jrs.202020011http://dx.doi.org/10.11834/jrs.202020011]
Min X, Wang Z ,Fu S, et al. Ground Simultaneous Measurements and Analysis of Radiometric Characterization of Dunhuang Test Site for Calibrating CBERS-1 Sensors [J]. Journal of Geo-Information Science,2002(03):43-50.
闵祥军,王志民,傅俏燕,顾英圻.CBERS-1CCD相机飞行绝对辐射标定试验地面同步测量与场地辐射特性分析[J].地球信息科学,2002(03):43-50.[DOI CNKI:SUN:DQXX.0.2002-03-007]
Mittaz J, Merchant C J, Woolliams E R. Applying principles of metrology to historical Earth observations from satellites[J]. Metrologia, 2019, 56(3): 032002. [DOI 10.1088/1681-7575/ab1705http://dx.doi.org/10.1088/1681-7575/ab1705]
Ohring G , Wielicki B , Spencer R , et al. Satellite Instrument Calibration for Measuring Global Climate Change: Report of a Workshop[J]. Bulletin of the American Meteorological Society, 2005, 86(9):1303-1313. [DOI 10.1175/bams-86-9-1303http://dx.doi.org/10.1175/bams-86-9-1303]
Rajendra B , David D , Aisheng W , et al. Initial Stability Assessment of S-NPP VIIRS Reflective Solar Band Calibration Using Invariant Desert and Deep Convective Cloud Targets[J]. Remote Sensing, 2014, 6(4):2809-2826. [DOI 10.3390/rs6042809http://dx.doi.org/10.3390/rs6042809]
Sayer A.M., Hsu N.C., Bettenhausen C., Holz R.E., Lee J., Quinn G., Veglio P., 2017. Cross-calibration of S-NPP VIIRS moderate resolution reflective solar bands against MODIS aqua over dark water scenes. Atmos. Meas. Tech. 10, 1425–1444. [DOI 10.5194/amt-10-1425-2017http://dx.doi.org/10.5194/amt-10-1425-2017]
Smyth T J, Moore G F, Hirata T, et al. Semianalytical model for the derivation of ocean color inherent optical properties: description, implementation, and performance assessment[J]. Applied Optics, 2006, 45(31): 8116-8131. [DOI 10.1364/AO.45.008116http://dx.doi.org/10.1364/AO.45.008116]
Sun L, Hu X, Guo M, et al. Multisite Calibration Tracking for FY-3A MERSI Solar Bands [J]. Advances in Meteorological Science and Technology,2013,3(04):84-96.
孙凌,胡秀清,郭茂华,徐娜.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[J].气象科技进展,2013,3(04):84-96.[DOI 10.3969/j.issn.2095-1973.2013.04.009http://dx.doi.org/10.3969/j.issn.2095-1973.2013.04.009]
Wang M, Gordon H R. Calibration of ocean color scanners: how much error is acceptable in the near infrared?[J]. Remote Sensing of Environment, 2002, 82(2-3): 497-504. [DOI 10.1016/S0034-4257(02)00072-Xhttp://dx.doi.org/10.1016/S0034-4257(02)00072-X]
Wang M, Bailey S W. Correction of the sunglint contamination on the SeaWiFS aerosol optical thickness retrievals[J]. SeaWiFS postlaunch calibration and validation analyses, Part, 2000, 1: 64-68.
Wielicki B A , Young D F , Mlynczak M G , et al. Achieving Climate Change Absolute Accuracy in Orbit[J]. Bulletin of the American Meteorological Society, 2013, 94(10):1519-1539. [DOI 10.1175/BAMS-D-12-00149.1http://dx.doi.org/10.1175/BAMS-D-12-00149.1]
Wielicki B A, Young D F, Mlynczak M G, et al. Achieving climate change absolute accuracy in orbit[J]. Bulletin of the American Meteorological Society, 2013, 94(10): 1519-1539. [DOI 10.1175/BAMS-D-12-00149.1http://dx.doi.org/10.1175/BAMS-D-12-00149.1]
Wilson , R . T . Py6S: A Python interface to the 6S radiative transfer model[J]. Computers & Geoences, 2013, 51(2):166-171. [DOI doi:10.1016/j.cageo.2012.08.002]
Wu X, Hewison T, Tahara Y. GSICS GEO-LEO intercalibration: Baseline algorithm and early results[C]//Atmospheric and Environmental Remote Sensing Data Processing and Utilization V: Readiness for GEOSS III. International Society for Optics and Photonics, 2009, 7456: 745604. [DOI 10.1117/12.825460http://dx.doi.org/10.1117/12.825460]
Xiong X , Sun J , Xie X , et al. On-Orbit Calibration and Performance of Aqua MODIS Reflective Solar Bands[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(1):535-546. [DOI 10.1109/TGRS.2009.2024307http://dx.doi.org/10.1109/TGRS.2009.2024307]
Xu Y, Jiang QG. A Pixel by Pixel Atmospheric Correction Algorithm and Its Application for MODIS Data Based on 6S Model [J]. Journal of Jilin University (Earth Science Edition), 2015, 45(5):1547-1553.
徐言, 姜琦刚. 基于6S模型的MODIS影像逐像元大气校正及其应用[J]. 吉林大学学报(地球科学版), 2015, 45(5):1547-1553.[DOI 10.13278/j.cnki.jjuese.201505304http://dx.doi.org/10.13278/j.cnki.jjuese.201505304]
Zhang P , Lu N , Li C , et al. Development of the Chinese Space-Based Radiometric Benchmark Mission LIBRA[J]. Remote Sensing, 2020, 12(14):2179. [DOI 10.3390/rs12142179http://dx.doi.org/10.3390/rs12142179]
Zhang Y, Qiu K, Hu X. Vicarious radiometric calibration of satellite FY-1D sensors at visible and near infrared channels. Acta Meteorologica Sinica, 2004, 18(4): 505-516.
文章被引用时，请邮件提醒。
提交
相关作者
暂无数据
相关机构
中国科学院大学
中国科学院空天信息创新研究院
兰州大学 资源环境学院
西南林业大学 地理与生态旅游学院
长沙市规划信息服务中心
选择翻译语言
- 地址：北京市海淀区北四环西路19号 《遥感学报》编辑部 邮编：100190
- 联系电话：010-58887052 Email：nrsb@aircas.ac.cn
- 技术支持由北京北大方正电子有限公司提供 京ICP备20021838号-9
京公网安备11010802024621 - 本系统建议在Chrome、 IE9+ 以上版本浏览器阅读本站内容，360浏览器请切换至极速模式
- Cookies帮助我们提供服务并提供个性化体验。使用本网站，即表示您同意我们使用Cookies
0
回到顶部