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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。
The WFV sensor onboard the Gaofen-1 satellite (GF-1) has high spatial resolution and wide imaging capability. GF-1 WFV data has become an important data source in the fields of resource investigation and ecological environment. At present, the GF-1 WFV data is only provided in L1-level product, and lacks surface reflectance product. However, most quantitative remote sensing studies are based on surface reflectance product. In order to produce GF-1 WFV surface reflectance product, this paper proposes a coupled atmospheric correction algorithm that integrates universal kriging method of MODIS AOD spatial fusion, 6S model and dynamic look-up table, and GF-1 WFV surface reflectance product of 2020 in China"s land area was produced and in open access. In terms of product accuracy validation, firstly, visual inspection, histogram and spectral curves changes of typical land cover types before and after atmospheric correction were compared; secondly, cross-validation were performed between GF-1 WFV and Landsat-8 OLI surface reflectance products, and thirdly, ground-based measurements were used for validation. The validation results show that the image quality after atmospheric correction is significantly improved, and it is in good agreement with the Landsat-8 OLI surface reflectance product. Validation results with the ground-based measurements indicate the mean values of Root Mean Square Error (RMSE) are 1.21%、1.53%、1.26%, and 6.14% for bule, green, red, and Near Infrared band, respectively. The GF-1 WFV surface reflectance product produced by this algorithm is of reliable quality, and the algorithm has the ability of operational production.