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Gradient modeling with gravity and DEM

Zhu, Lizhi
http://rave.ohiolink.edu/etdc/view?acc_num=osu1180110427

Abstract Details

2007, Doctor of Philosophy, Ohio State University, Geodetic Science and Surveying.
This study deals with the methods of forward gravity gradient modeling based on gravity data and densely sampled digital elevation data. In this study, we develop an improved modeling of the gravity gradient tensors and study the comprehensive process to determine gravity gradients and their errors from real data and various models (Stokes’ integral, radial-basis spline and LSC). Usually, the gravity gradients are modeled using digital elevation model data under simple density assumptions. Finite element method, FFT and polyhedral methods are analyzed in the determination of DEM-derived gravitational gradients. Here, we develop a method to model gradients from a combination of gravity anomaly and DEM data. Through a solution on the boundary value problem of the potential field, the gravity anomaly data are combined consistently with the forward model of DEM to yield six components of the gravity gradient tensor. The second Helmert condensation principle and the remove-restore technique are used to connect DEM and gravity data in the determination of gravity gradients. Modeling of the gradients thus, particularly at some altitude above ground, from surface gravity anomalies is based on numerical implementations of solutions to boundary-value problems in potential theory, such as Stokes’ integral, least-squares collocation, and some Fourier transform methods, or even with radial-basis splines. Modeling of this type would offer a complementary if not alternative type of support in the validation of airborne gradiometry systems. We compare these various modeling techniques using FTG (full tensor gradient) data by Bell Geospace and modeled gradients, thus demonstrating techniques and principles, as well limitations and advantages in each. The Stokes’ integral and the least-squares collocation methods are more accurate (about 3 E at altitude of 1200 m) than radial-basis splines in the determination of gravity gradient using synthetic data. Furthermore, the comparison between the modeled data and real data verifies that the high resolution (higher than 1 arcmin) gravity data is necessary to validate the gradiometry survey data. Ground and airborne gradiometer systems can be validated by analyzing the spectral properties of modeled gradients. Also, such modeling allows the development of survey parameters for such instrumentation.
Christopher Jekeli (Advisor)
173 p.
Geodesy
Gradient modeling; gravity and DEM

Recommended Citations

Citations

  • Zhu, L. (2007). Gradient modeling with gravity and DEM [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1180110427

    APA Style (7th edition)

  • Zhu, Lizhi. Gradient modeling with gravity and DEM. 2007. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1180110427.

    MLA Style (8th edition)

  • Zhu, Lizhi. "Gradient modeling with gravity and DEM." Doctoral dissertation, Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1180110427

    Chicago Manual of Style (17th edition)

osu1180110427
2,752
© 2007, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.