Elliptical harmonic method for gravity forward modelling of 2D bodies

Cheng Chen; Shaofeng Bian; Motao Huang

doi:10.1007/s00190-021-01511-x

A hybrid rectangle-Gaussian grid for continuous convolution integrals: With application in gravity forward modelling

10.1190/segam2017-17496460.1 ◽

2017 ◽

Author(s):

Leyuan Wu

Keyword(s):

Forward Modelling ◽

Gravity Forward Modelling ◽

Convolution Integrals

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Experiences with the use of mass-density maps in residual gravity forward modelling

Studia Geophysica et Geodaetica ◽

10.1007/s11200-017-0656-z ◽

2018 ◽

Vol 62 (4) ◽

pp. 596-623 ◽

Cited By ~ 5

Author(s):

Meng Yang ◽

Christian Hirt ◽

Robert Tenzer ◽

Roland Pail

Keyword(s):

Mass Density ◽

Forward Modelling ◽

Residual Gravity ◽

Gravity Forward Modelling ◽

Density Maps

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Cap integration in spectral gravity forward modelling: near- and far-zone gravity effects via Molodensky’s truncation coefficients

Journal of Geodesy ◽

10.1007/s00190-018-1139-x ◽

2018 ◽

Vol 93 (1) ◽

pp. 65-83 ◽

Cited By ~ 6

Author(s):

Blažej Bucha ◽

Christian Hirt ◽

Michael Kuhn

Keyword(s):

Forward Modelling ◽

Gravity Forward Modelling ◽

Gravity Effects

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Spatial distribution of hydrocarbon reservoirs in the West Korea Bay Basin in the northern part of the Yellow Sea, estimated by 3-D gravity forward modelling

Geophysical Journal International ◽

10.1093/gji/ggw369 ◽

2016 ◽

Vol 208 (1) ◽

pp. 75-85 ◽

Cited By ~ 2

Author(s):

Sungchan Choi ◽

In-Chang Ryu ◽

H.-J. Götze ◽

Y. Chae

Keyword(s):

Spatial Distribution ◽

Yellow Sea ◽

Hydrocarbon Reservoirs ◽

The Yellow Sea ◽

Forward Modelling ◽

The West ◽

Gravity Forward Modelling

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Characterization of geothermally relevant structures at the top of crystalline basement in Switzerland by filters and gravity forward modelling

Geophysical Journal International ◽

10.1093/gji/ggu255 ◽

2014 ◽

Vol 199 (1) ◽

pp. 226-241 ◽

Cited By ~ 9

Author(s):

Yassine Abdelfettah ◽

Eva Schill ◽

Pascal Kuhn

Keyword(s):

Crystalline Basement ◽

Forward Modelling ◽

Gravity Forward Modelling

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A spectral-domain approach for gravity forward modelling of 2D bodies

Journal of Geodesy ◽

10.1007/s00190-019-01308-z ◽

2019 ◽

Vol 93 (10) ◽

pp. 2123-2144

Author(s):

Cheng Chen ◽

Shaofeng Bian ◽

Houpu Li

Keyword(s):

Spectral Domain ◽

Forward Modelling ◽

Spectral Domain Approach ◽

Gravity Forward Modelling

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The tree-canopy effect in gravity forward modelling

Geophysical Journal International ◽

10.1093/gji/ggz264 ◽

2019 ◽

Vol 219 (1) ◽

pp. 271-289 ◽

Cited By ~ 2

Author(s):

Meng Yang ◽

Christian Hirt ◽

Moritz Rexer ◽

Roland Pail ◽

Dai Yamazaki

Keyword(s):

Tree Canopy ◽

Data Sets ◽

Forward Modelling ◽

Bare Ground ◽

Gravity Forward Modelling ◽

Digital Elevation ◽

Canopy Effect ◽

Elevation Model ◽

Validation Experiments

SUMMARY High resolution and accurate digital terrain models (DTMs) are frequently used as input data sets to define the topographic masses in gravity forward modelling, for example, for terrain corrections in the context of regional gravity modelling. However, over vegetated areas such as forests and scrublands, the radar- and image-based digital elevation models (DEMs) may contain a tree bias, and therefore do not represent the bare-ground surface. The presence of vegetation-induced signals in DEMs, denoted here the tree-canopy effect, will introduce errors in the gravity forward modelling. In this study, the role of the tree-canopy effect in gravity forward modelling calculations is numerically investigated. First, spectral forward modelling techniques were applied to analyse a global tree-canopy bias model with a horizontal resolution of 1 km x 1 km and to quantify its effect on global gravity forward modelling results. We demonstrate that tree-canopy signals in the DEM produce a positive bias in the topographic gravitational field over vegetated areas, with values ranging from 0 to ∼2.7 mGal for gravity disturbances. Second, the role of the tree-canopy effect in high-frequency gravity forward modelling is studied using well-known residual terrain modelling (RTM) techniques. As DEM data sets, we used the 3″ SRTM (Shuttle Radar Topography Mission Digital 9 m Elevation Database) V4.1 (containing vegetation biases) and the 3″ MERIT-DEM (Multi-Error-Removed Improved-Terrain Digital elevation model) as a representation of the bare-ground elevations. Using Tasmania and the Amazon rainforest regions as test areas with significant tree-canopy signals we show that the tree-height effect on RTM calculations is of high-frequency nature, with rather small signals which reach in extreme cases amplitudes of ∼1–2 mGal occurring at forest boundaries. Third, using ground gravity observations, validation experiments were performed over the Australian Alps, Tasmania and the Canadian Rocky Mountains. All validation experiments show that the bare-ground elevation model MERIT-DEM performs better than SRTM V4.1 in terms of reduction of the discrepancies between modelled and observed gravity values. As a general conclusion, bare-ground DEM models should be preferred in any gravity forward modelling application to avoid or reduce the tree-canopy effect.

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