...
首页> 外文期刊>Journal of African Earth Sciences >An assessment of spatial methods for merging terrestrial with GGM-derived gravity anomaly data
【24h】

An assessment of spatial methods for merging terrestrial with GGM-derived gravity anomaly data

机译:用GGM衍生重力异常数据合并陆地的空间方法评估

获取原文
获取原文并翻译 | 示例
           

摘要

The practice of merging terrestrial gravity anomalies with Global Geopotential Model (GGM) derived quantities has become popular in geodetic applications. That notwithstanding, GGM-derived gravity anomalies are mostly not consistent with their terrestrial counterparts. This study presents a method for reducing the inconsistencies between both datasets by the application of atmospheric correction, omission and commission errors to GGM-derived data. Furthermore, the study offers a comparison of the padding, kriging and least-squares collocation (LSC) methods for merging terrestrial and GGM-derived gravity anomalies. The three models were assessed by Leave Out (LO) validation method using 15 terrestrial data points that are well distributed across the study area (Nigeria). Three GGM's (EGM96, EGM2008 and SPW 5) were evaluated, and EGM2008 was selected as being optimal within the study area. The EGM2008-derived data were then merged with 1800 terrestrial FA anomaly data covering the area. Results obtained indicate the relevance of applying the atmospheric correction, omission error and commission errors to GGM-derived data before merging them with terrestrial data. Within the test region, the omission error had the largest contribution to the GGM-data inconsistency with values ranging from -72.18 to 43.98mgals. Also, the LSC technique produced the best result for the data merging with a standard deviation of residuals of +/- 5.77mgals, followed by the padding method with a standard deviation of residuals of +/- 6.35mgals.
机译:利用全球地理位置模型(GGM)衍生数量合并陆地重力异常的实践在大地型应用中变得流行。尽管如此,GGM衍生的重力异常主要与他们的地面对应物保持一致。本研究提出了一种通过应用大气校正,遗漏和委员会对GGM导出数据来减少两个数据集之间不一致的方法。此外,该研究提供了用于合并地面和GGM衍生的重力异常的填充,Kriging和最小二乘搭配(LSC)方法的比较。通过释放(LO)验证方法进行评估三种模型,该方法使用跨越研究区域(尼日利亚)的15个陆地数据点。评估三个GGM(EGM96,EGM2008和SPW 5),并选择EGM2008在研究区域内最佳。然后将EGM2008衍生的数据与覆盖该区域的1800个陆地FA异常数据合并。获得的结果表明在用地面数据合并之前将大气校正,省略误差和佣金错误应用于GGM衍生数据的相关性。在测试区域内,省略误差对GGM数据不一致具有从-72.18至43.98mgals的值的最大贡献。此外,LSC技术的数据合并具有+/- 5.77mgals残差的标准偏差的最佳结果,其次是填充方法,具有+/- 6.35mgals的标准偏差。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号