Contribution of GRAV-D airborne gravity to improvement of regional gravimetric geoid modelling in Colorado, USA

AbstractThis paper studies the contribution of airborne gravity data to improvement of gravimetric geoid modelling across the mountainous area in Colorado, USA. First, airborne gravity data was processed, filtered, and downward-continued. Then, three gravity anomaly grids were prepared; the first grid only from the terrestrial gravity data, the second grid only from the downward-continued airborne gravity data, and the third grid from combined downward-continued airborne and terrestrial gravity data. Gravimetric geoid models with the three gravity anomaly grids were determined using the least-squares modification of Stokes’ formula with additive corrections (LSMSA) method. The absolute and relative accuracy of the computed gravimetric geoid models was estimated on GNSS/levelling points. Results exhibit the accuracy improved by 1.1 cm or 20% in terms of standard deviation when airborne and terrestrial gravity data was used for geoid computation, compared to the geoid model computed only from terrestrial gravity data. Finally, the spectral analysis of surface gravity anomaly grids and geoid models was performed, which provided insights into specific wavelength bands in which airborne gravity data contributed and improved the power spectrum.

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Gravimetric Geoid Modeling from the Combination of Satellite Gravity Model, Terrestrial and Airborne Gravity Data: A Case Study in the Mountainous Area, Colorado

10.21203/rs.3.rs-41989/v1 ◽

2020 ◽

Author(s):

Tao Jiang ◽

Yamin Dang ◽

Chuanyin Zhang

Keyword(s):

Standard Deviation ◽

Gravity Model ◽

Gravity Data ◽

Combination Method ◽

Airborne Gravity ◽

Mountainous Area ◽

Gravimetric Geoid ◽

Geoid Model ◽

Satellite Gravity ◽

Terrestrial Gravity

Abstract Constructing a high precision and high resolution gravimetric geoid model in the mountainous area is a quite challenging task because of the high, rough nature of topography and the geological complexity. One way out is to use as many gravity observations from different sources as possible such as satellite, terrestrial and airborne gravity data, thus the proper combination of heterogeneous gravity datasets is critical. In a rough topographic area in Colorado, we computed a set of gravimetric geoid models based on different combination modes of satellite gravity models, terrestrial and airborne gravity data using the spectral combination method. The gravimetric geoid model obtained from the combination of satellite gravity model GOCO06S and terrestrial gravity data agrees with the GPS leveling measured geoid heights at 194 benchmarks in 5.8 cm in terms of the standard deviation of discrepancies, and the standard deviation reduces to 5.3 cm after including the GRAV-D airborne gravity data collected at ~6.2 km altitude into the data combination. The contributions of airborne gravity data to the signal and accuracy improvements of the geoid models were quantified for different spatial distribution and density of terrestrial gravity data. The results demonstrate that, although the airborne gravity survey was flown at a high altitude, the additions of airborne gravity data improved the accuracies of geoid models by 13.4% - 19.8% in the mountainous area (elevations > 2000 m) and 12.7% - 21% (elevations < 2000 m) in the moderate area in the cases of terrestrial gravity data spacings are larger than 15 km.

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Gravimetric geoid modeling from the combination of satellite gravity model, terrestrial and airborne gravity data: a case study in the mountainous area, Colorado

10.21203/rs.3.rs-41989/v2 ◽

2020 ◽

Author(s):

Tao Jiang ◽

Yamin Dang ◽

Chuanyin Zhang

Keyword(s):

Standard Deviation ◽

Gravity Model ◽

Gravity Data ◽

Combination Method ◽

Airborne Gravity ◽

Mountainous Area ◽

Gravimetric Geoid ◽

Geoid Model ◽

Satellite Gravity ◽

Terrestrial Gravity

Abstract Constructing a high precision and high resolution gravimetric geoid model in the mountainous area is a quite challenging task because of the the lack of terrestrial gravity observations, rough high, rough nature of topography and the geological complexity. One way out is to use as hight quality and well distributed satellite and airborne gravity data to fill the gravity data gapsmany gravity observations from different sources as possible such as satellite, terrestrial and airborne gravity data, thus the proper combination of heterogeneous gravity datasets is critical. In a rough topographic area in Colorado, we computed a set of gravimetric geoid models based on different combination modes of satellite gravity models, terrestrial and airborne gravity data using the spectral combination method. The gravimetric geoid model obtained from the combination of satellite gravity model GOCO06S and terrestrial gravity data agrees with the GPS leveling measured geoid heights at 194 benchmarks in 5.8 cm in terms of the standard deviation of discrepancies, and the standard deviation reduces to 5.3 cm after including the GRAV-D airborne gravity data collected at ~6.2 km altitude into the data combination. The contributions of airborne gravity data to the signal and accuracy improvements of the geoid models were quantified for different spatial distribution and density of terrestrial gravity data. The results demonstrate that, although the airborne gravity survey was flown at a high altitude, the additions of airborne gravity data improved the accuracies of geoid models by 13.4% - 19.8% in the mountainous area (elevations > 2000 m) and 12.7% - 21% (elevations < 2000 m) in the moderate area in the cases of terrestrial gravity data spacings are larger than 15 km.

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Gravimetric geoid modeling from the combination of satellite gravity model, terrestrial and airborne gravity data: a case study in the mountainous area, Colorado

10.21203/rs.3.rs-41989/v3 ◽

2020 ◽

Author(s):

Tao Jiang ◽

Yamin Dang ◽

Chuanyin Zhang

Keyword(s):

Standard Deviation ◽

Gravity Model ◽

Gravity Data ◽

Combination Method ◽

Airborne Gravity ◽

Mountainous Area ◽

Gravimetric Geoid ◽

Geoid Model ◽

Satellite Gravity ◽

Terrestrial Gravity

Abstract Constructing a high precision and high resolution gravimetric geoid model in the mountainous area is a quite challenging task because of the lack of terrestrial gravity observations, rough topography and the geological complexity. One way out is to use high quality and well distributed satellite and airborne gravity data to fill the gravity data gaps, thus the proper combination of heterogeneous gravity datasets is critical. In a rough topographic area in Colorado, we computed a set of gravimetric geoid models based on different combination modes of satellite gravity models, terrestrial and airborne gravity data using the spectral combination method. The gravimetric geoid model obtained from the combination of satellite gravity model GOCO06S and terrestrial gravity data agrees with the GPS leveling measured geoid heights at 194 benchmarks in 5.8 cm in terms of the standard deviation of discrepancies, and the standard deviation reduces to 5.3 cm after including the GRAV-D airborne gravity data collected at ~6.2 km altitude into the data combination. The contributions of airborne gravity data to the signal and accuracy improvements of the geoid models were quantified for different spatial distribution and density of terrestrial gravity data. The results demonstrate that, although the airborne gravity survey was flown at a high altitude, the additions of airborne gravity data improved the accuracies of geoid models by 13.4% - 19.8% in the mountainous area (elevations > 2000 m) and 12.7% - 21% (elevations < 2000 m) in the moderate area in the cases of terrestrial gravity data spacings are larger than 15 km.

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Gravimetric geoid modeling from the combination of satellite gravity model, terrestrial and airborne gravity data: a case study in the mountainous area, Colorado

Earth Planets and Space ◽

10.1186/s40623-020-01287-y ◽

2020 ◽

Vol 72 (1) ◽

Author(s):

Tao Jiang ◽

Yamin Dang ◽

Chuanyin Zhang

Keyword(s):

Standard Deviation ◽

Gravity Model ◽

Gravity Data ◽

Combination Method ◽

Airborne Gravity ◽

Mountainous Area ◽

Gravimetric Geoid ◽

Geoid Model ◽

Satellite Gravity ◽

Terrestrial Gravity

AbstractConstructing a high-precision and high-resolution gravimetric geoid model in the mountainous area is a quite challenging task because of the lack of terrestrial gravity observations, rough topography and the geological complexity. One way out is to use high-quality and well-distributed satellite and airborne gravity data to fill the gravity data gaps; thus, the proper combination of heterogeneous gravity datasets is critical. In a rough topographic area in Colorado, we computed a set of gravimetric geoid models based on different combination modes of satellite gravity models, terrestrial and airborne gravity data using the spectral combination method. The gravimetric geoid model obtained from the combination of satellite gravity model GOCO06S and terrestrial gravity data agrees with the GPS leveling measured geoid heights at 194 benchmarks in 5.8 cm in terms of the standard deviation of discrepancies, and the standard deviation reduces to 5.3 cm after including the GRAV-D airborne gravity data collected at ~ 6.2 km altitude into the data combination. The contributions of airborne gravity data to the signal and accuracy improvements of the geoid models were quantified for different spatial distribution and density of terrestrial gravity data. The results demonstrate that, although the airborne gravity survey was flown at a high altitude, the additions of airborne gravity data improved the accuracies of geoid models by 13.4%–19.8% in the mountainous area (elevations > 2000 m) and 12.7%–21% (elevations < 2000 m) in the moderate area in the cases of terrestrial gravity data spacings are larger than 15 km.

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Geoid Modelling of Kalimantan Island using Airborne Gravity Data and Global Geoid Model (EGM2008)

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/936/1/012029 ◽

2021 ◽

Vol 936 (1) ◽

pp. 012029

Author(s):

Zahroh Arsy Udama ◽

Ira Mutiara Anjasmara ◽

Arisauna Maulidyan Pahlevi ◽

Anas Sharafeldin Mohamed Osman

Keyword(s):

Standard Deviation ◽

Gravity Anomaly ◽

Gravity Data ◽

Airborne Gravity ◽

Gravimetric Geoid ◽

Wave Component ◽

Geoid Model ◽

Free Air ◽

Free Air Gravity ◽

Local Geoid

Abstract The availability of geoids, especially in survey and mapping activities, is useful for transforming the geometric heights obtained from observations of the Global Navigation Satellite System (GNSS) into orthometric heights that have real physical meanings such as those obtained from waterpass measurements. If a geoid is available, the orthometric heights of points on earth can be determined using the GNSS heighting method. The use of modern survey and mapping instruments based on satellite observations such as GNSS is more efficient in terms of time, effort, and cost compared to the accurate waterpass method. According to the Indonesian Geospatial Information Agency (BIG) it is stated that the application of geoid as a national Vertical Geospatial Reference System has an adequate and ideal category if the accuracy is higher than 15 cm. Recent studies have shown that it is possible to generate local geoid models with centimetre accuracy by utilizing airborne gravity data. We calculate free-air gravity anomaly data is calculated by processing airborne gravity and GNSS data using the Stokes Integral method on AGR software. Next a geoid model is created by calculating the contribution of three components, namely the long wave component represented by the EGM2008 global geoid data model, the shortwave component represented by the Shuttle Radar Topography Mission (SRTM) data and the medium wave component represented by the free-air gravity anomaly data. The geoid model validation was carried out using the geoid fitting method for geoid accuracy by calculating the difference between the gravimetric geoid and the geometric geoid and comparing it with the global geoid model EGM2008 degrees 2190. As a result, the total geoid model accuracy value was determined to be 49.4 cm on gravimetric geoid undulations with a standard deviation of 7.1 cm. Meanwhile, the results of the EGM2008 geoid undulation accuracy test at 2190 degrees resulted in an accuracy of 51.9 cm with a standard deviation of 9.9 cm. These results indicate that the local geoid model from airborne gravity measurement data produces a geoid model with a higher accuracy than the global geoid model EGM2008 degrees 2190. However, the accuracy of the resulting data is still below the BIG standard of 15 cm, so further research is needed to produce a geoid model which conforms to the standard.

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Quantifying the contribution of airborne gravity data for geoid modeling: two case studies

10.5194/egusphere-egu2020-17734 ◽

2020 ◽

Author(s):

Tao Jiang ◽

Yamin Dang ◽

Chuanyin Zhang

Keyword(s):

Large Scale ◽

Gravity Data ◽

Airborne Gravity ◽

Gravimetric Geoid ◽

Geoid Model ◽

Satellite Gravity ◽

Terrestrial Gravity ◽

Modeling Experiment ◽

The Usa ◽

Gps Leveling

<p>Airborne gravimetry has become increasingly important for geoid modeling because of its capability of collecting large scale gravity data over difficult areas. In order to quantify the contribution of airborne gravity data for geoid determination, two regions with distinct topographical condition, a hilly desert area in Mu Us of China and a mountainous region in Colorado of the USA were selected for gravimetric geoid modeling experiment. The gravimetric geoid model computed by combining satellite gravity model, terrestrial and airborne gravity data fits with GPS leveling data to 0.8 cm for Mu Us case and 5.3 cm for Colorado case. The contribution of airborne gravity data to the signal and accuracy improvement of the geoid was quantitatively evaluated for different spatial distribution and density of terrestrial gravity data. The results demonstrate that in the cases of the spacing of terrestrial gravity points exceeds 15 km, the additions of airborne gravity data improve the accuracies of gravimetric geoid models by 11.1%~48.3% for Mu Us case and 13%~20% for Colorado case.</p>

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GRAVIMETRIC GEOID MODELLING OVER PENINSULAR MALAYSIA USING TWO DIFFERENT GRIDDING APPROACHES FOR COMBINING FREE AIR ANOMALY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-w16-515-2019 ◽

2019 ◽

Vol XLII-4/W16 ◽

pp. 515-522

Author(s):

M. F. Pa’suya ◽

A. H. M. Din ◽

J. C. McCubbine ◽

A. H. Omar ◽

Z. M. Amin ◽

...

Keyword(s):

Gravity Data ◽

Reference Signal ◽

Digital Terrain Model ◽

Peninsular Malaysia ◽

Airborne Gravity ◽

Geopotential Model ◽

Gravimetric Geoid ◽

Geoid Model ◽

Free Air ◽

Free Air Anomaly

Abstract. We investigate the use of the KTH Method to compute gravimetric geoid models of Malaysian Peninsular and the effect of two differing strategies to combine and interpolate terrestrial, marine DTU17 free air gravity anomaly data at regular grid nodes. Gravimetric geoid models were produced for both free air anomaly grids using the GOCE-only geopotential model GGM GO_CONS_GCF_2_SPW_R4 as the long wavelength reference signal and high-resolution TanDEM-X global digital terrain model. The geoid models were analyzed to assess how the different gridding strategies impact the gravimetric geoid over Malaysian Peninsular by comparing themto 172 GNSS-levelling derived geoid undulations. The RMSE of the two sets of gravimetric geoid model / GNSS-levelling residuals differed by approx. 26.2 mm. When a 4-parameter fit is used, the difference between the RMSE of the residuals reduced to 8 mm. The geoid models shown here do not include the latest airborne gravity data used in the computation of the official gravimetric geoid for the Malaysian Peninsular, for this reason they are not as precise.

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The Uganda Gravimetric Geoid Model 2014 Computed by The KTH Method

Journal of Geodetic Science ◽

10.1515/jogs-2015-0007 ◽

2015 ◽

Vol 5 (1) ◽

Cited By ~ 3

Author(s):

L. E. Sjöberg ◽

A. Gidudu ◽

R. Ssengendo

Keyword(s):

Gravity Field ◽

Gravity Data ◽

Geoid Determination ◽

Geopotential Model ◽

Gravimetric Geoid ◽

Geoid Model ◽

Satellite Mission ◽

Terrestrial Gravity ◽

Gravity Field Recovery ◽

Goce Satellite

AbstractFor many developing countries such as Uganda, precise gravimetric geoid determination is hindered by the low quantity and quality of the terrestrial gravity data. With only one gravity data point per 65 km2, gravimetric geoid determination in Uganda appears an impossible task. However, recent advances in geoid modelling techniques coupled with the gravity-field anomalies from the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) satellite mission have opened new avenues for geoid determination especially for areas with sparse terrestrial gravity. The present study therefore investigates the computation of a gravimetric geoid model overUganda (UGG2014) using the Least Squares Modification of Stokes formula with additive corrections. UGG2014 was derived from sparse terrestrial gravity data from the International Gravimetric Bureau, the 3 arc second SRTM ver4.1 Digital Elevation Model from CGIAR-CSI and the GOCE-only global geopotential model GO_CONS_GCF_2_TIM_R5. To compensate for the missing gravity data in the target area, we used the surface gravity anomalies extracted from the World Gravity Map 2012. Using 10 Global Navigation Satellite System (GNSS)/levelling data points distributed over Uganda, the RMS fit of the gravimetric geoid model before and after a 4-parameter fit is 11 cm and 7 cm respectively. These results show that UGG2014 agrees considerably better with GNSS/levelling than any other recent regional/ global gravimetric geoid model. The results also emphasize the significant contribution of the GOCE satellite mission to the gravity field recovery, especially for areas with very limited terrestrial gravity data.With an RMS of 7 cm, UGG2014 is a significant step forward in the modelling of a “1-cm geoid” over Uganda despite the poor quality and quantity of the terrestrial gravity data used for its computation.

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Quasi Geoid and Geoid Modeling with the Use of Terrestrial and Airborne Gravity Data by the GGI Method—A Case Study in the Mountainous Area of Colorado

Remote Sensing ◽

10.3390/rs13214217 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4217

Author(s):

Marek Trojanowicz ◽

Magdalena Owczarek-Wesołowska ◽

Yan Ming Wang ◽

Olgierd Jamroz

Keyword(s):

Gravity Data ◽

Research Work ◽

Airborne Gravity ◽

Mountainous Area ◽

Geoid Model ◽

Data Inversion ◽

Gravimetric Quasigeoid ◽

The Mean ◽

Grid Points

This article concerns the development of gravimetric quasigeoid and geoid models using the geophysical gravity data inversion technique (the GGI method). This research work was carried out on the basis of the data used in the Colorado geoid experiment, and the mean quasigeoid (ζm) and mean geoid (Nm) heights, determined by the approaches used in the Colorado geoid experiment, were used as a reference. Three versions of the quasigeoid GGI models depending on gravity data were analyzed: terrestrial-only, airborne-only, and combined (using airborne and terrestrial datasets). For the combined version, which was the most accurate, a model in the form of a 1′×1′ grid was calculated in the same area as the models determined in the Colorado geoid experiment. For the same grid, the geoid–quasigeoid separation was determined, which was used to build the geoid model. The agreement (in terms of the standard deviation of the differences) of the determined models, with ζm and Nm values for the GSVS17 profile points, was ±0.9 cm for the quasigeoid and ±1.2 cm for the geoid model. The analogous values, determined on the basis of all 1′×1′ grid points, were ±2.3 cm and ±2.6 cm for the quasigeoid and geoid models, respectively.

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