Bayesian Methods in Geodetic Earth System Research

大地测量地球系统研究中的贝叶斯方法

• 批准号: 226407636
• 负责人: Professor Dr.-Ing. Jürgen Kusche
• 金额: --
• 依托单位: Lehrstuhl für Astronomische, Physikalische und Mathematische Geodäsie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2012
• 资助国家: 德国
• 起止时间: 2011-12-31 至 2014-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/226407636?language=en
• 关键词: Bayesian; Methods; Geodetic; Earth; System

In the proposed study, we lay the foundations for the application of Bayesian methods in geodetic Earth system research. A bundle of algorithms and implementation schemes will be developed that allow to formulate Bayesian estimates when geodetic data is analysed or data and physical model output is to be combined, while existing software blocks for geodetic analysis and model integrations can be reused. Uncertainties will be strictly characterized by possibly non-Gaussian probability density functions. Numerically efficient algorithms will be developed, Our work will be generic and not restricted to a particular application within geodetic Earth system research. Yet, through case studies we will deal with the interpretation of satellite-gravimetric data.

为贝叶斯方法在大地测量地球系统研究中的应用奠定了基础。将制定一套算法和执行计划，以便在分析大地测量数据或将数据和物理模型输出相结合时，制定贝叶斯估计数，同时可重新使用现有的大地测量分析和模型整合软件块。非高斯概率密度函数将被严格地表征为可能的非高斯概率密度函数。数值效率的算法将被开发，我们的工作将是通用的，并不局限于一个特定的应用程序在大地测量地球系统的研究。然而，通过案例研究，我们将处理卫星重力数据的解释。

项目成果

Separation of global time-variable gravity signals into maximally independent components

• DOI: 10.1007/s00190-011-0532-5
• 发表时间: 2012-07-01
• 期刊: JOURNAL OF GEODESY
• 影响因子: 4.4
• 作者: Forootan, E.;Kusche, J.
• 通讯作者: Kusche, J.

Multivariate Prediction of Total Water Storage Changes Over West Africa from Multi-Satellite Data

利用多卫星数据对西非总水储量变化进行多变量预测

• DOI: 10.1007/s10712-014-9292-0
• 期刊: Surveys in Geophysics
• 影响因子: 4.6
• 作者: E. Forootan;J. Kusche;I. Loth;W-D. Schuh;A. Eicker;J. Awange;L. Longuevergne;B. Diekkrueger;M. Schmidt;C.K. Shum
• 通讯作者: C.K. Shum

Independent patterns of water mass anomalies over Australia from satellite data and models

• DOI: 10.1016/j.rse.2012.05.023
• 发表时间: 2012-09
• 期刊: Remote Sensing of Environment
• 影响因子: 13.5
• 作者: E. Forootan;J. Awange;J. Kusche;B. Heck;A. Eicker

Separation of large scale water storage patterns over Iran using GRACE, altimetry and hydrological data

• DOI: 10.1016/j.rse.2013.09.025
• 发表时间: 2014-01-01
• 期刊: REMOTE SENSING OF ENVIRONMENT
• 影响因子: 13.5
• 作者: Forootan, E.;Rietbroek, R.;Famiglietti, J.
• 通讯作者: Famiglietti, J.