摘要
依据四川盆地和其西部高原地区1549个地面重力实测点数据,利用基于‘消去-恢复’思想的最小二乘配置方法,将EGM2008地球重力场模型给出的自由空气重力异常与地面实测自由空气重力异常两种数据进行融合,并对其适用性加以验证分析.计算结果表明,在四川高原地形起伏剧烈的山地,利用采样间隔4 km的地面测点,通过该数据融合方法能将模型值与实测值的标准差从41.9 mGal(10^(-5)ms^(-2))提高到11.6 mGal,平均差异从-105.4 mGal提高到-0.5 mGal;在龙泉山以东较为平坦的盆地区域,间隔8 km的地面测点密度就可以将模型标准差从5.2 mGal提高到1.9 m Gal,平均差异从-16.8 mGal提高到-0.1 mGal.上述不同地面测点分布密度对数据融合结果影响的分析表明,在地形起伏的山地,要将模型标准差控制在10 mGal左右,必须将地面测点密度控制在2 km以内;在平坦的盆地或平原地区,地面测点60 km间隔采样就可以将EGM2008模型值标准差校正到5 mGal左右.
Based on 1549 ground gravity measure points data from Sichuan Basin and north plateau of Sichuan,Use‘remove-restore＇least-squares collocation method to coalesce the EGM2008 gravity modeling freeair gravity anomaly data and actual observed freeair gravity anomaly data and to analyze the feasibility. In the precipitous mountain area of Sichuan Plateau,Using the sampling interval of 4 km of the ground observation can improve the modeling standard deviation from 41. 9 mGal（ 10^-5ms^-2） to 11. 6 mGal and average deviation from -105. 4 mGal to -0. 5 mGal by this data fusion method; in the flat basin of east Longquan Mountain,8 km density of measure points can improve the modeling standard deviation from 5. 2 mGal to 1. 9 mGal and average deviation from -16. 8 mGal to -0. 1 mGal. The analysis showed that diverse ground measure point density has positive impact on data coalescing. For the undulate mountain area,to control the standard deviation around 10 mGal,it is necessary to have a measure point density below 2 km. For the flat basin or plain,60 km measure point density can modify the EGM2008 ＇s standard deviation to around 5 mGal.
出处
《地球物理学进展》
CSCD
北大核心
2017年第3期1051-1058,共8页
Progress in Geophysics
基金
国家自然科学基金(41574071)
东北亚地震
海啸
火山合作研究计划项目(ZRH2014-01-02)
地震行业专项(201108004)联合资助
