Error sources and data limitations for the prediction ofsurface gravity: a case study using benchmarks
Gravity-based heights require gravity values at levelled benchmarks (BMs), whichsometimes have to be predicted from surrounding observations. We use EGM2008 andthe Australian National Gravity Database (ANGD) as examples of model and terrestrialobserved data respectively to predict gravity at Austral...
| Main Authors: | , , |
|---|---|
| Format: | Journal Article |
| Published: |
Springer
2012
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/12353 |
| _version_ | 1848748052789067776 |
|---|---|
| author | Filmer, Michael Hirt, Christian Featherstone, Will |
| author_facet | Filmer, Michael Hirt, Christian Featherstone, Will |
| author_sort | Filmer, Michael |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Gravity-based heights require gravity values at levelled benchmarks (BMs), whichsometimes have to be predicted from surrounding observations. We use EGM2008 andthe Australian National Gravity Database (ANGD) as examples of model and terrestrialobserved data respectively to predict gravity at Australian national levelling network(ANLN) BMs. The aim is to quantify errors that may propagate into the predicted BMgravity values and then into gravimetric height corrections (HCs). Our results indicatethat an approximate ±1 arc-minute horizontal position error of the BMs causesmaximum errors in EGM2008 BM gravity of ~ 22 mGal (~55 mm in the HC at ~2200 melevation) and ~18 mGal for ANGD BM gravity because the values are not computed atthe true location of the BM. We use RTM (residual terrain modelling) techniques toshow that ~50% of EGM2008 BM gravity error in a moderately mountainous regioncan be accounted for by signal omission. Non-representative sampling of ANGDgravity in this region may cause errors of up to 50 mGals (~120 mm for the Helmertorthometric correction at ~2200 m elevation). For modelled gravity at BMs to beviable, levelling networks need horizontal BM positions accurate to a few metres, whileRTM techniques can be used to reduce signal omission error. Unrepresentative gravitysampling in mountains can be remedied by denser and more representative re-surveys,and/or gravity can be forward modelled into regions of sparser gravity. |
| first_indexed | 2025-11-14T06:58:55Z |
| format | Journal Article |
| id | curtin-20.500.11937-12353 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:58:55Z |
| publishDate | 2012 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-123532017-09-13T15:54:08Z Error sources and data limitations for the prediction ofsurface gravity: a case study using benchmarks Filmer, Michael Hirt, Christian Featherstone, Will RTM levelling Helmert orthometric heights height corrections gravity Gravity-based heights require gravity values at levelled benchmarks (BMs), whichsometimes have to be predicted from surrounding observations. We use EGM2008 andthe Australian National Gravity Database (ANGD) as examples of model and terrestrialobserved data respectively to predict gravity at Australian national levelling network(ANLN) BMs. The aim is to quantify errors that may propagate into the predicted BMgravity values and then into gravimetric height corrections (HCs). Our results indicatethat an approximate ±1 arc-minute horizontal position error of the BMs causesmaximum errors in EGM2008 BM gravity of ~ 22 mGal (~55 mm in the HC at ~2200 melevation) and ~18 mGal for ANGD BM gravity because the values are not computed atthe true location of the BM. We use RTM (residual terrain modelling) techniques toshow that ~50% of EGM2008 BM gravity error in a moderately mountainous regioncan be accounted for by signal omission. Non-representative sampling of ANGDgravity in this region may cause errors of up to 50 mGals (~120 mm for the Helmertorthometric correction at ~2200 m elevation). For modelled gravity at BMs to beviable, levelling networks need horizontal BM positions accurate to a few metres, whileRTM techniques can be used to reduce signal omission error. Unrepresentative gravitysampling in mountains can be remedied by denser and more representative re-surveys,and/or gravity can be forward modelled into regions of sparser gravity. 2012 Journal Article http://hdl.handle.net/20.500.11937/12353 10.1007/s11200-012-1114-6 Springer fulltext |
| spellingShingle | RTM levelling Helmert orthometric heights height corrections gravity Filmer, Michael Hirt, Christian Featherstone, Will Error sources and data limitations for the prediction ofsurface gravity: a case study using benchmarks |
| title | Error sources and data limitations for the prediction ofsurface gravity: a case study using benchmarks |
| title_full | Error sources and data limitations for the prediction ofsurface gravity: a case study using benchmarks |
| title_fullStr | Error sources and data limitations for the prediction ofsurface gravity: a case study using benchmarks |
| title_full_unstemmed | Error sources and data limitations for the prediction ofsurface gravity: a case study using benchmarks |
| title_short | Error sources and data limitations for the prediction ofsurface gravity: a case study using benchmarks |
| title_sort | error sources and data limitations for the prediction ofsurface gravity: a case study using benchmarks |
| topic | RTM levelling Helmert orthometric heights height corrections gravity |
| url | http://hdl.handle.net/20.500.11937/12353 |