GF-1 WFV surface reflectance product in China’s land area

SHE Wenqing; ZHANG Zhaoming; PENG Yan; HE Guojin; LONG Tengfei; WANG Guizhou

doi:10.11834/jrs.20222190

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GF-1 WFV surface reflectance product in China’s land area
Vol. 27, Issue 9, Pages: 2206-2218(2023)
Received：24 April 2022，

Published：07 September 2023
DOI： 10.11834/jrs.20222190
稿件说明：

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佘文庆，张兆明，彭燕，何国金，龙腾飞，王桂周.2023.中国陆地区域GF-1 WFV地表反射率产品.遥感学报，27（9）： 2206-2218 DOI： 10.11834/jrs.20222190.

She W Q，Zhang Z M，Peng Y，He G J，Long T F and Wang G Z. 2023. GF-1 WFV surface reflectance product in China’s land area. National Remote Sensing Bulletin， 27（9）：2206-2218 DOI： 10.11834/jrs.20222190.

摘要

高分一号卫星（GF-1）搭载的WFV传感器具有高空间分辨率和宽幅成像能力，是资源调查和生态环境保护等领域的重要数据源。目前GF-1 WFV数据仅提供L1级标准化产品，缺少地表反射率产品，而大多数定量遥感研究都是建立在地表反射率产品的基础上。为了研发GF-1 WFV地表反射率产品，本文提出一种基于多源MODIS AOD空间融合和动态查找表的6S大气校正算法并生产和共享中国陆地区域2020年GF-1 WFV地表反射率产品。在产品精度验证方面，通过比较大气校正前后的影像质量、直方图和典型地物反射率差异并利用同步过境的Landsat 8 OLI地表反射率产品和地面实测数据进行定量验证。精度验证和分析结果表明，经过大气校正后的影像质量改善明显，与Landsat 8 OLI地表反射率产品具有良好的一致性。基于实测地表反射率数据的精度验证结果表明蓝、绿、红和近红外波段的均方根误差（Root Mean Square Error）分别为1.21%、1.53%、1.26%和6.14%。研究结果表明，研发的GF-1 WFV地表反射率产品的质量可靠且产品算法具有自动化和业务化的生产能力。

Abstract

Land surface reflectance

as a key physical parameter describing the basic properties of the land surface

is one of the key parameters for quantitative remote sensing research and applications

such as remote sensing indices computation

leaf area index retrieval

dynamic forest cover monitoring. The main representative land surface reflectance products at home and abroad are MODIS surface reflectance products

Landsat surface reflectance products and Sentinel surface reflectance products. The WFV (Wide Field of View) sensor onboard the Gaofen-1 satellite (GF-1) has high spatial resolution and wide imaging capability. GF-1 WFV data have become an important data source in the fields of resource investigation and ecological environment. At present

GF-1 WFV data have been fully opened to the public

however the GF-1 WFV data are only provided in L1-level product and lack land surface reflectance product. The aim of this paper is to produce GF-1 WFV land surface reflectance product.

This paper proposes a coupled atmospheric correction algorithm that integrates the universal kriging method of MODIS AOD spatial fusion

6S model

and dynamic look-up table and produced an open-access GF-1 WFV land surface reflectance product of 2020 in China’s land area.

In terms of product accuracy validation

first

visual inspection

histogram

and spectral curve changes of typical land cover types before and after atmospheric correction were compared. Second

cross-validation was performed between GF-1 WFV and Landsat-8 OLI land surface reflectance products. Third

ground-based measurements were used for validation. The validation results show the image quality after atmospheric correction is remarkably improved and agrees with the Landsat 8 OLI land surface reflectance product. The root mean square error with the Landsat 8 OLI land surface reflectance products do not exceed 3%

and the

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=48410307&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=48410306&type=

2.87866688

2.37066650

is greater than 0.9.The validation results with the ground-based measurements indicate the mean values of root mean square error are 1.21%

1.53%

1.26%

and 6.14% for blue

green

red

and near infrared band

respectively. The validation results show that the GF-1 WFV land surface reflectance retrieval algorithm has good accuracy.

The GF-1 WFV land surface reflectance product produced by this algorithm is reliable

and the algorithm can be used in operational production. In addition

the algorithms and products can provide a stable and reliable data source for subsequent quantitative remote sensing research and application of GF-1 WFV data

and the GF-1 WFV land surface reflectance products can also be synergized with Landsat and Sentinel series land surface reflectance products to form a dense time-series of near-daily

high spatialresolution land surface reflectance products for China’s land area.

关键词

Keywords

references

Abrams M , Crippen R and Fujisada H . 2020 . ASTER Global Digital Elevation Model (GDEM) and ASTER Global Water Body Dataset (ASTWBD) . Remote Sensing , 12 ( 7 ): 1156 [ DOI: 10.3390/rs12071156 http://dx.doi.org/10.3390/rs12071156 ]

Armstrong M . 1984 . Problems with universal kriging . Journal of the International Association for Mathematical Geology , 16 ( 1 ): 101 - 108 [ DOI: 10.1007/BF01036241 http://dx.doi.org/10.1007/BF01036241 ]

Bai Z G . 2013 . The technology characteristics of GF-1 satellite . Aerospace China , ( 8 ): 5 - 9

白照广 . 2013 . 高分一号卫星的技术特点 . 中国航天 , ( 8 ): 5 - 9

Chander G , Mishra N , Helder D L , Aaron D B , Angal A , Choi T , Xiong X X and Doelling D R . 2013 . Applications of Spectral Band Adjustment Factors (SBAF) for cross-calibration . IEEE Transactions on Geoscience and Remote Sensing , 51 ( 3 ): 1267 - 1281 [ DOI: 10.1109/TGRS.2012.2228007 http://dx.doi.org/10.1109/TGRS.2012.2228007 ]

Chatterjee A , Michalak A M , Kahn R A , Paradise S R , Braverman A J and Miller C E . 2010 . A geostatistical data fusion technique for merging remote sensing and ground-based observations of aerosol optical thickness . Journal of Geophysical Research , 115 ( D20 ): D 20207 [ DOI: 10.1029/2009JD013765 http://dx.doi.org/10.1029/2009JD013765 ]

Hsu N C , Tsay S C , King M D and Herman J R . 2006 . Deep blue retrievals of Asian aerosol properties during ACE-Asia . IEEE Transactions on Geoscience and Remote Sensing , 44 ( 11 ): 3180 - 3195 [ DOI: 10.1109/TGRS.2006.879540 http://dx.doi.org/10.1109/TGRS.2006.879540 ]

Hu Y , Liu L Y , Liu L L , Peng D L , Jiao Q J and Zhang H . 2014 . A Landsat-5 atmospheric correction based on MODIS atmosphere products and 6S model . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 7 ( 5 ): 1609 - 1615 [ DOI: 10.1109/JSTARS.2013.2290028 http://dx.doi.org/10.1109/JSTARS.2013.2290028 ]

Hu Y , Zhong B , Ma Z Z and He M . 2018 . GF-1 WFV atmospheric correction based on MODIS atmosphere products and 6S model . Remote Sensing Information , 33 ( 5 ): 35 - 40

胡勇 , 仲波 , 马泽忠 , 何敏 . 2018 . 采用MODIS大气产品的高分一号WFV数据大气校正 . 遥感信息 , 33 ( 5 ): 35 - 40 [ DOI: 10.3969/j.issn.1000-3177.2018.05.006 http://dx.doi.org/10.3969/j.issn.1000-3177.2018.05.006 ]

Kaufman Y J and Sendra C . 1988 . Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery . International Journal of Remote Sensing , 9 ( 8 ): 1357 - 1381 [ DOI: 10.1080/01431168808954942 http://dx.doi.org/10.1080/01431168808954942 ]

Kokaly R F , Clark R N , Swayze G A , Livo K E , Hoefen T M , Pearson N C , Wise R A , Benzel W , Lowers H A , Driscoll R L and Klein A J . 2017 . USGS Spectral Library Version 7 . United States Geological Survey

Li Z Q , Chen X F , Ma Y , Qie L L , Hou W Z and Qiao Y L . 2018 . An overview of atmospheric correction for optical remote sensing satellites . Journal of Nanjing University of Information Science and Technology(Natural Science Edition) , 10 ( 1 ): 6 - 15

李正强 , 陈兴峰 , 马䶮 , 伽丽丽 , 侯伟真 , 乔延利 . 2018 . 光学遥感卫星大气校正研究综述 . 南京信息工程大学学报(自然科学版) , 10 ( 1 ): 6 - 15 [ DOI: 10.13878/j.cnki.jnuist.2018.01.002 http://dx.doi.org/10.13878/j.cnki.jnuist.2018.01.002 ]

Liang S L , Fang H L , Chen M Z , Shuey C J , Walthall C , Daughtry C , Morisette J , Schaaf C and Strahler A . 2002 . Validating MODIS land surface reflectance and albedo products: methods and preliminary results . Remote Sensing of Environment , 83 ( 1/2 ): 149 - 162 . [ DOI: 10.1016/S0034-4257(02)00092-5 http://dx.doi.org/10.1016/S0034-4257(02)00092-5 ]

Liu J , Wang L M , Yang L B , Teng F , Shao J , Yang F G and Fu C H . 2015 . GF-1 satellite image atmospheric correction based on 6S model and its effect . Transactions of the Chinese Society of Agricultural Engineering , 31 ( 19 ): 159 - 168

刘佳 , 王利民 , 杨玲波 , 滕飞 , 邵杰 , 杨福刚 , 富长虹 . 2015 . 基于6S模型的GF-1卫星影像大气校正及效果 . 农业工程学报 , 31 ( 19 ): 159 - 168 [ DOI: 10.11975/j.issn.1002-6819.2015.19.022 http://dx.doi.org/10.11975/j.issn.1002-6819.2015.19.022 ]

Lyapustin A , Wang Y J , Korkin S and Huang D . 2018 . MODIS collection 6 MAIAC algorithm . Atmospheric Measurement Techniques , 11 ( 10 ): 5741 - 5765 [ DOI: 10.5194/amt-2018-141 http://dx.doi.org/10.5194/amt-2018-141 ]

Ma L L , Zhao Y G , Woolliams E R , Dai C H , Wang N , Liu Y K , Li L , Wang X H , Gao C X , Li C R and Tang L L . 2020 . Uncertainty analysis for RadCalNet instrumented test sites using the Baotou sites BTCN and BSCN as examples . Remote Sensing , 12 ( 11 ): 1696 [ DOI: 10.3390/rs12111696 http://dx.doi.org/10.3390/rs12111696 ]

Main-Knorn M , Pflug B , Louis J , Debaecker V , Müller-Wilm U and Gascon F . 2017 . Sen2Cor for Sentinel-2//Proceedings Volume 10427, Image and Signal Processing for Remote Sensing XXIII . Warsaw : SPIE [ DOI: 10.1117/12.2278218 http://dx.doi.org/10.1117/12.2278218 ]

Martins V S , Soares J V , Novo E M L M , Barbosa C C F , Pinto C T , Arcanjo J S and Kaleita A . 2018 . Continental-scale surface reflectance product from CBERS-4 MUX data: assessment of atmospheric correction method using coincident Landsat observations . Remote Sensing of Environment , 218 : 55 - 68 [ DOI: 10.1016/j.rse.2018.09.017 http://dx.doi.org/10.1016/j.rse.2018.09.017 ]

Peng Y , He G J , Zhang Z M , Long T F , Wang M M and Ling S G . 2016 . Study on atmospheric correction approach of Landsat-8 imageries based on 6S model and look-up table . Journal of Applied Remote Sensing , 10 ( 4 ): 045006 [ DOI: 10.1117/1.JRS.10.045006 http://dx.doi.org/10.1117/1.JRS.10.045006 ]

Peng Y , He G J , Zhang Z M and Yin R Y . 2020 . Landsat surface reflectance products over China . China Scientific Data , 5 ( 4 ): 53 - 62

彭燕 , 何国金 , 张兆明 , 尹然宇 . 2020 . 中国区域Landsat地表反射率产品 . 中国科学数据 , 5 ( 4 ): 53 - 62 [ DOI: 10.11922/csdata.2020.0032.zh http://dx.doi.org/10.11922/csdata.2020.0032.zh ]

Richter R , Schläpfer D and Müller A . 2006 . An automatic atmospheric correction algorithm for visible/NIR imagery . International Journal of Remote Sensing , 27 ( 10 ): 2077 - 2085 [ DOI: 10.1080/01431160500486690 http://dx.doi.org/10.1080/01431160500486690 ]

Roy D P , Ju J C , Kline K , Scaramuzza P L , Kovalskyy V , Hansen M , Loveland T R , Vermote E and Zhang C S . 2010 . Web-enabled Landsat Data (WELD): Landsat ETM+composited mosaics of the conterminous United States . Remote Sensing of Environment , 114 ( 1 ): 35 - 49 [ DOI: 10.1016/j.rse.2009.08.011 http://dx.doi.org/10.1016/j.rse.2009.08.011 ]

Roy D P , Zhang H K , Ju J , Gomez-Dans J L , Lewis P E , Schaaf C B , Sun Q , Li J , Huang H and Kovalskyy V . 2016 . A general method to normalize Landsat reflectance data to nadir BRDF adjusted reflectance . Remote Sensing of Environment , 176 : 255 - 271 [ DOI: 10.1016/j.rse.2016.01.023 http://dx.doi.org/10.1016/j.rse.2016.01.023 ]

Shen Q , Yao Y , Li L W , Long T F , Chen F and Zhang B . 2021 . Annual 0.8 m surface reflectance data set of Beijing plain area from 2015 to 2019 . National Remote Sensing Bulletin , 25 ( 11 ): 2303 - 2312

申茜 , 姚月 , 李利伟 , 龙腾飞 , 陈甫 , 张兵 . 2021 . 北京市平原区 2015 年— 2019 年 0 .8 m地表反射率数据集. 遥感学报 , 25 ( 11 ): 2303 - 2312 [ DOI: 10.11834/jrs.20210407 http://dx.doi.org/10.11834/jrs.20210407 ]

Vermote E F , El Saleous N Z and Justice C O . 2002 . Atmospheric correction of MODIS data in the visible to middle infrared: first results . Remote Sensing of Environment , 83 ( 1/2 ): 97 - 111 [ DOI: 10.1016/S0034-4257(02)00089-5 http://dx.doi.org/10.1016/S0034-4257(02)00089-5 ]

Vermote E F and Kotchenova S . 2008 . Atmospheric correction for the monitoring of land surfaces . Journal of Geophysical Research : Atmospheres , 113 ( D23 ): D23 S 90 [ DOI: 10.1029/2007JD009662 http://dx.doi.org/10.1029/2007JD009662 ]

Vermote E F , Tanre D , Deuze J L , Herman M and Morcette J J . 1997 . Second simulation of the satellite signal in the solar spectrum , 6 S: an overview. IEEE Transactions on Geoscience and Remote Sensing , 35 ( 3 ): 675 - 686 [ DOI: 10.1109/36.581987 http://dx.doi.org/10.1109/36.581987 ]

Vermote E F , Justice C , Claverie M and Franch B . 2016 . Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product . Remote Sensing of Environment , 185 ( 2016 ): 46 - 56 . [ DOI: 10.1016/j.rse.2016.04.008 http://dx.doi.org/10.1016/j.rse.2016.04.008 ]

Wang Z T , Xin J Y , Jia S L , Li Q , Chen L F and Zhao S H . 2015 . Retrieval of AOD from GF-1 16 m camera via DDV algorithm . Journal of Remote Sensing , 19 ( 3 ): 530 - 538

王中挺 , 辛金元 , 贾松林 , 厉青 , 陈良富 , 赵少华 . 2015 . 利用暗目标法从高分一号卫星16 m相机数据反演气溶胶光学厚度 . 遥感学报 , 19 ( 3 ): 530 - 538 [ DOI: 10.11834/jrs.20154110 http://dx.doi.org/10.11834/jrs.20154110 ]

Wei J , Li Z Q , Peng Y R and Sun L . 2019 . MODIS collection 6.1 aerosol optical depth products over land and ocean: validation and comparison . Atmospheric Environment , 201 : 428 - 440 [ DOI: 10.1016/j.atmosenv.2018.12.004 http://dx.doi.org/10.1016/j.atmosenv.2018.12.004 ]

Zheng W and Zeng Z Y . 2004 . A review on methods of atmospheric correction for remote sensing images . Remote Sensing Information , ( 4 ): 66 - 70

郑伟 , 曾志远 . 2004 . 遥感图像大气校正方法综述 . 遥感信息 , ( 4 ): 66 - 70 [ DOI: 10.3969/j.issn.1000-3177.2004.04.019 http://dx.doi.org/10.3969/j.issn.1000-3177.2004.04.019 ]

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