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Received：19 September 2022，
Published：07 March 2023
移动端阅览
光合有效辐射是植被生产力模型的重要输入参数，也是陆地生态系统模型及生物地化模型等的重要特征参量。目前的全球或区域尺度光合有效辐射产品在起伏地表情形的精度及可用性尚存在不足，高分系列卫星的发射，为高空间分辨率光合有效辐射遥感产品反演提供了可能。本文结合高分一号卫星（GF-1）反演的地表反照率产品，气溶胶光学厚度产品，日本新一代静止卫星Himawari-8及国产风云四号卫星（FY-4）的云光学厚度产品及美国的SNPP卫星反演的气溶胶光学厚度产品（用于填补GF气溶胶产品的空值区），发展了一种基于参数化模型的光合有效辐射遥感反演方法。晴空条件下，主要考虑气溶胶和瑞利散射对光合有效辐射的衰减；云天情形，则主要考虑云光学厚度参数对入射辐射的影响，以球形粒子的Mie散射理论和平面平行大气辐射传输原理计算总透过率；针对起伏地表，分别计算地形对坡面入射角度的影响、对直接辐射的遮蔽以及对散射辐射的增强/衰减效应，从而得到高分卫星光合有效辐射遥感反演模型及产品。利用河北怀来试验站、西南大学柑研所及黑河流域地表过程综合观测网的连续观测数据对光合有效辐射产品进行了对比验证，其相关系数为0.87，平均偏差为1.56 W/m
2
，均方根误差为16.14 W/m
2
。本算法所采用的云光学厚度输入数据的空间分辨率（5 km）及地表反照率分辨率（16 m）存在较大的空间尺度差异，可能会带来一定的误差。下一步拟利用GF-4卫星提供的50 m分辨率的大气参数，进一步提高GF光合有效辐射产品的时空精度，并针对产品开展更广泛深入的验证分析。
Photosynthetically Active Radiation (PAR) is an important input of vegetation productivity models
and also a key parameter of terrestrial ecosystem models and biogeochemical models. The accuracy and availability of current global or regional products are still insufficient to better understanding Earth system. China has launched series of Gaofen (GF) Earth observation satellites and provide the possibility of high spatial resolution PAR products retrieval. In this paper
a new method based on a parametric model for remote sensing inversion of PAR was proposed. The surface albedo products and the aerosol optical depth products were retrieved from GF-1 satellites
the cloud optical thickness products were retrieved from Himawari-8 and FY-4 satellites. Under clear sky conditions
the attenuation of PAR by aerosol and Rayleigh scattering is mainly considered. The influence of cloud on incident radiation is mainly considered for cloudy skies
and the calculation is based on the Mie scattering theory of spherical particles. Surface received direct PAR for rugged surfaces were calculated with the input of incident angle
the slope and the aspect. The enhancement or attenuation effect of the scattered radiation were retrieved using the sky view factor the horizontal surface received diffuse radiation. The PAR products were compared and verified using the continuous observation data of the ground stations collected from the Hebei Huailai
the Heihe River Basin Surface Process Comprehensive Observation Network and Ganyansuo in Chengdu. The correlation coefficient
mean bias error and the root mean square error between the two datasets were 0.87
1.56 W/m
2
and 16.14 W/m
2
respectively. The spatial resolution of the input atmospheric parameters (sub-satellite point 1 km) and the surface parameter resolution (16 m) of the PAR products have a large spatial scale difference. The atmospheric parameters with the resolution of 50 m provided by the GF-4 satellite will be used to further improve the spatiotemporal accuracy of GF PAR products
and more extensive and in-depth verification analysis will be carried out in our future study.
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