水星可照时间与搜索半径影响因素研究
Influence factors of Mercury possible sunshine duration and search radius
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摘要: 采用光线追踪算法模拟起伏地形下的可照时间时,随着对地形遮蔽状况进行搜索的半径不同将直接影响到可照时间计算的准确性与高效性.本研究基于DEM数据,针对水星独特的轨道运动特征,太阳高度角随水星运动变化缓慢的特点,研究了水星2种典型地貌下不同太阳高度角的搜索半径和基于搜索半径的平均可照时间变化状况.同时构建了以5种影响搜索半径与可照时间的因子作为输入变量,分别以搜索半径与平均可照时间作为输出变量的BP神经网络.模型通过了检验,5种影响因子与搜索半径影响的显著性由高到低:太阳高度角>高程标准差>地形开阔度平均值>地形起伏度>地表粗糙度平均值;与平均可照时间影响的显著性由高到低:太阳高度角>高程标准差>地表粗糙度平均值>地形开阔度平均值>地形起伏度.该模型可为计算水星最搜索半径以及可照时间提供参考.Abstract: When Ray Tracing Algorithm is used to simulate the possible sunshine duration under undulating terrain, the different search radius of the terrain shading condition affects the accuracy and efficiency of the calculation of the possible sunshine duration. In the report, based on DEM data, aimed at the unique orbital motion characteristics of Mercury and the slow change of the solar elevation angle with the motion of Mercury, the search radius of different solar altitude angles and the change of average possible sunshine duration were investigated. At the same time, the BP neural network was constructed with five factors affecting the search radius and the searchable time as input variables and the search radius and the possible sunshine duration as output variables. The model passed the test, and the significance of the influence of the five influencing factors and the optimal search radius from high to low was: solar elevation angle > elevation standard deviation > average of terrain width > terrain relief > average of surface roughness, and the significance of the influence of average possible sunshine duration from high to low was: solar elevation angle > elevation standard deviation > average of surface roughness > average of terrain width > terrain relief. The model can be used as a reference for calculating the searching radius and average possible sunshine duration of Mercury.