中国陆地区域GF-1 WFV地表反射率产品
GF-1 WFV surface reflectance product in China’s land area
- 2023年27卷第9期 页码:2206-2218
纸质出版日期: 2023-09-07
DOI: 10.11834/jrs.20222190
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纸质出版日期: 2023-09-07 ,
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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
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
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。
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
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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.
遥感GF-1 WFV地表反射率大气校正6S模型空间融合动态查找表中国陆地区域
remote sensingGF-1 WFVsurface reflectanceatmospheric correction6S modelspatial fusiondynamic lookup tableChina’s land area
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