scholarly journals Assessment of high-degree reference models and Recent Goce/Grace Global Geopotential Models over Sudan based on the GPS/Leveling data

2021 ◽  
Vol 936 (1) ◽  
pp. 012035
Author(s):  
Anas Sharafeldin Mohamed Osman ◽  
Ira Mutiara Anjasmara ◽  
Abdelrahim Ruby ◽  
Zahroh Arsy Udama
Keyword(s):  
Gravity Field ◽  
Gravity Data ◽  
Airborne Gravity ◽  
Accuracy Evaluation ◽  
Geoid Model ◽  
Gravity Field Model ◽  
Reference Models ◽  
Geopotential Models ◽  
Gps Leveling ◽  
High Degree

Abstract Nowadays, Global Geopotential Models (GGMs) can be used as a reference to develop more detailed regional/local geoids, or they can be used to provide geoid heights on their own. Since 2000, several GGMs have been released, and they are mainly derived from satellite gravity measurements, satellite-only models, terrestrial gravimetry, altimeter-derived gravity data in marine areas, and airborne gravity data. With a precise geoid model, ellipsoidal heights obtained from GPS can be converted to orthometric heights, which is reasonably quite needed in Geodesy, Civil Engineering, etc. These heights reflect changes in topography as well as local variations in gravity. This paper evaluates some of the latest releases of high degree reference models and the satellite-only global gravity field model over Sudan using 19 GPS/Leveling stations. We have been selected 6 GGMs based on Gravity field Goce and Grace, and they released in 2020, 2019, 2014, 2008, and 1996 as shown in the International Centre for Global Earth Models website (ICGEM). The accuracy evaluation of the GGM models have been discussed, the accurate GGMs over Sudan are XGM2019e_2159 and GOCO05s, which have indicated -0.019 and 0.046 meters, respectively. The evaluation results produce valuable information to academia and geoid modeling research topics in Sudan, which shows the precise model from the selected GGMs in Sudan by using the available GPS/Leveling data.

scholarly journals Accuracy Evaluation of Geoid Heights in the National Control Points of South Korea Using High-Degree Geopotential Model

2020 ◽  
Vol 10 (4) ◽  
pp. 1466
Author(s):  
Kwang Bae Kim ◽  
Hong Sik Yun ◽  
Ha Jung Choi
Keyword(s):  
South Korea ◽  
Gravity Field ◽  
Gravity Data ◽  
Altimeter Data ◽  
Airborne Gravity ◽  
Geopotential Model ◽  
Control Points ◽  
Gravimetric Geoid ◽  
Geopotential Models ◽  
High Degree

Precise geoid heights are not as important for understanding Earth’s gravity field, but they are important to geodesy itself, since the vertical datum is defined as geoid in a cm-level accuracy. Several high-degree geopotential models have been derived lately by using satellite tracking data such as those from Gravity Recovery and Climate Experiment (GRACE) and Gravity Field and Steady-State Ocean Circulation Explorer (GOCE), satellite altimeter data, and terrestrial and airborne gravity data. The Korean national geoid (KNGeoid) models of the National Geographic Information Institute (NGII) were developed using the latest global geopotential models (GGMs), which are combinations of gravity data from satellites and land gravity data. In this study, geoid heights calculated from the latest high-degree GGMs were used to evaluate the accuracy of the three GGMs (European Improved Gravity model of Earth by New techniques (EIGEN)-6C4, Earth Gravitational Model 2008 (EGM2008), and GOCE-EGM2008 combined model (GECO)) by comparing them with the geoid heights derived from the Global Navigation Satellite System (GNSS)/leveling of the 1182 unified control points (UCPs) that have been installed by NGII in South Korea since 2008. In addition, the geoid heights derived from the KNGeoid models were compared with the geoid heights derived from the GNSS/leveling of the 1182 UCPs to assess the accuracy of the KNGeoid models in terms of relative geoid heights for further gravimetric geoid determination studies in South Korea. As a result, the EGM2008 model could be selected as the suitable GGM from among the three GGMs for determining a gravimetric geoid model for South Korea.

Development of a global geoid model 2020 (GGM2020)

2020 ◽  
Author(s):  
WenBin Shen ◽  
Youchao Xie ◽  
Jiancheng Han ◽  
Jiancheng Li
Keyword(s):  
Gravity Field ◽  
Density Model ◽  
Layer Model ◽  
Geoid Model ◽  
Gravity Field Model ◽  
Layer Method ◽  
Shallow Layer ◽  
Inner Surface ◽  
Gps Leveling ◽  
Better Than

<p>We present an updated 5′ ×5′ global geoid model 2020 (GGM2020), which is determined based on the shallow layer method (or simply Shen method). We choose an inner surface S below the EGM2008 global geoid by 15 m, and the layer bounded by the inner surface S and the Earths geographical surface E is referred to as the shallow layer. We formulate the 3D shallow mass layer model using the refined 5′ ×5′ crust density model, CRUST1.0-5min, which is an improved 5′ ×5′ density model of the CRUST1.0 with taking into account the corrections of the areas covered by ice sheets and the land-ocean crossing regions. Based on the shallow mass layer model and the gravity field EGM2008 that is defined in the region outside the Earth’s geographical surface E, we determine the gravity field model EGM2008S that is defined in the whole region outside the inner surface S. Based on the gravity field EGM2008S and the geoid equation W(P) =W0, where W0 is the geopotential constant on the geoid and P is the point on the geoid G, we established a 5′ ×5′ global geoid model GGM2020. Comparisons show that in average the GGM2020 fits the globally available GPS/leveling points better than the EGM2008 global geoid. This study is supported by NSFCs (grant Nos. 41721003, 41631072, 41874023, 41804012, 41429401, 41574007).</p>

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

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>

Application of global geopotential models to high-precesion levelling processing

2017 ◽  
Vol 926 (8) ◽  
pp. 2-9
Author(s):  
V.V. Popadyev ◽  
D.A. Kuliev
Keyword(s):  
Field Model ◽  
Direct Evaluation ◽  
Gravity Field Model ◽  
Bouguer Anomalies ◽  
Free Air ◽  
Geopotential Models ◽  
Integral Characteristics ◽  
Indirect Evaluation ◽  
Gravity Map ◽  
High Degree

The article studies the properties of the high-degree gravity field model EGM-2008 in the calculation of integral characteristics at large distances several times greater than the spatial resolution of the model. As an example of an indirect evaluation of a high-degree model, a gravimetric correction was computed into the sum of the measured elevations along the line of the high-precision I class leveling of the Krasnovodsk – Chardzhou line located in Turkmenistan. Using the calculator ICGEM, the Bouguer anomalies were calculated at each point of the line, then the attraction of the Bouguer layer (used heights are from catalog) excluded for the transition to free-air anomalies. In parallel, for a direct evaluation of the model, a regular grid of Bouguer anomalies with a step of 2 angular minutes within line area was also obtained, which were then compared with the anomalies from the gravity map J-40 of scale 1

Towards an updated, enhanced regional gravity field solution for Antarctica

2021 ◽  
Author(s):  
Mirko Scheinert ◽  
Philipp Zingerle ◽  
Theresa Schaller ◽  
Roland Pail ◽  
Martin Willberg
Keyword(s):  
Gravity Anomaly ◽  
Gravity Field ◽  
Gravity Data ◽  
Gravity Anomalies ◽  
Data Set ◽  
Gravity Field Model ◽  
Terrestrial Gravity ◽  
Field Solution ◽  
Gravity Disturbances ◽  
Regional Gravity

<p>In the frame of the IAG Subcommission 2.4f “Gravity and Geoid in Antarctica” (AntGG) a first Antarctic-wide grid of ground-based gravity anomalies was released in 2016 (Scheinert et al. 2016). That data set was provided with a grid space of 10 km and covered about 73% of the Antarctic continent. Since then a considerably amount of new data has been made available, mainly collected by means of airborne gravimetry. Regions which were formerly void of any terrestrial gravity observations and have now been surveyed include especially the polar data gap originating from GOCE satellite gravimetry. Thus, it is timely to come up with an updated and enhanced regional gravity field solution for Antarctica. For this, we aim to improve further aspects in comparison to the AntGG 2016 solution: The grid spacing will be enhanced to 5 km. Instead of providing gravity anomalies only for parts of Antarctica, now the entire continent should be covered. In addition to the gravity anomaly also a regional geoid solution should be provided along with further desirable functionals (e.g. gravity anomaly vs. disturbance, different height levels).</p><p>We will discuss the expanded AntGG data base which now includes terrestrial gravity data from Antarctic surveys conducted over the past 40 years. The methodology applied in the analysis is based on the remove-compute-restore technique. Here we utilize the newly developed combined spherical-harmonic gravity field model SATOP1 (Zingerle et al. 2019) which is based on the global satellite-only model GOCO05s and the high-resolution topographic model EARTH2014. We will demonstrate the feasibility to adequately reduce the original gravity data and, thus, to also cross-validate and evaluate the accuracy of the data especially where different data set overlap. For the compute step the recently developed partition-enhanced least-squares collocation (PE-LSC) has been used (Zingerle et al. 2021, in review; cf. the contribution of Zingerle et al. in the same session). This method allows to treat all data available in Antarctica in one single computation step in an efficient and fast way. Thus, it becomes feasible to iterate the computations within short time once any input data or parameters are changed, and to easily predict the desirable functionals also in regions void of terrestrial measurements as well as at any height level (e.g. gravity anomalies at the surface or gravity disturbances at constant height).</p><p>We will discuss the results and give an outlook on the data products which shall be finally provided to present the new regional gravity field solution for Antarctica. Furthermore, implications for further applications will be discussed e.g. with respect to geophysical modelling of the Earth’s interior (cf. the contribution of Schaller et al. in session G4.3).</p>

The experimental geoid 2020 – the first joint geoid model for the North American and Pacific Geopotential Datum 

2021 ◽  
Author(s):  
Yan Ming Wang ◽  
Xiaopeng Li ◽  
Kevin Ahlgren ◽  
Jordan Krcmaric ◽  
Ryan Hardy ◽  
...  
Keyword(s):  
North American ◽  
Gravity Data ◽  
The United States ◽  
Geodetic Survey ◽  
Airborne Gravity ◽  
Data Sets ◽  
National Geodetic Survey ◽  
Geoid Model ◽  
Satellite Gravity ◽  
The North

<p>For the upcoming North American-Pacific Geopotential Datum of 2022, the National Geodetic Survey (NGS), the Canadian Geodetic Survey (CGS) and the National Institute of Statistics and Geography of Mexico (INEGI) computed the first joint experimental gravimetric geoid model (xGEOID) on 1’x1’ grids that covers a region bordered by latitude 0 to 85 degree, longitude 180 to 350 degree east. xGEOID20 models are computed using terrestrial gravity data, the latest satellite gravity model GOCO06S, altimetric gravity data DTU15, and an additional nine airborne gravity blocks of the GRAV-D project, for a total of 63 blocks. In addition, a digital elevation model in a 3” grid was produced by combining MERIT, TanDEM-X, and USGS-NED and used for the topographic/gravimetric reductions. The geoid models computed from the height anomalies (NGS) and from the Helmert-Stokes scheme (CGS) were combined using two different weighting schemes, then evaluated against the independent GPS/leveling data sets. The models perform in a very similar way, and the geoid comparisons with the most accurate Geoid Slope Validation Surveys (GSVS) from 2011, 2014 and 2017 indicate that the relative geoid accuracy could be around 1-2 cm baseline lengths up to 300 km for these GSVS lines in the United States. The xGEOID20 A/B models were selected from the combined models based on the validation results. The geoid accuracies were also estimated using the forward modeling.</p>

scholarly journals Performance Comparison of Geoid Refinement between XGM2016 and EGM2008 Based on the KTH and RCR Methods: Jilin Province, China

2020 ◽  
Vol 12 (2) ◽  
pp. 324
Author(s):  
Qiong Wu ◽  
Hongyao Wang ◽  
Bin Wang ◽  
Shengbo Chen ◽  
Hongqing Li
Keyword(s):  
Gravity Field ◽  
Mean Square Error ◽  
Gravity Data ◽  
Jilin Province ◽  
Mountainous Area ◽  
Mean Square ◽  
Geoid Model ◽  
Plain Area ◽  
Gravity Field Models ◽  
Global Mean

The selection of an appropriate global gravity field model and refinement method can effectively improve the accuracy of the refined regional geoid model in a certain research area. We analyzed the accuracy of Experimental Geopotential Model (XGM2016) based on the GPS-leveling data and the modification parameters of the global mean square errors in the KTH geoid refinement in Jilin Province, China. The regional geoid was refined based on Earth Gravitational Model (EGM2008) and XGM2016 using both the Helmert condensation method with an RCR procedure and the KTH method. A comparison of the original two gravity field models to the GPS-leveling benchmarks showed that the accuracies of XGM2016 and EGM2008 in the plain area of Jilin Province are similar with a standard deviation (STD) of 5.8 cm, whereas the accuracy of EGM2008 in the high mountainous area is 1.4 cm better than that of XGM2016, which may be attributed to its low resolution. The modification parameters between the two gravity field models showed that the coefficient error of XGM2016 model was lower than that of EGM2008 for the same degree of expansion. The different modification limits and integral radii may produce a centimeter level difference in global mean square error, while the influence of the truncation error caused by the integral was at the millimeter level. The terrestrial gravity data error accounted for the majority of the global mean square error. The optimal least squares modification obtained the minimum global mean square error, and the global mean square error calculated based on XGM2016 model was reduced by about 1~3 cm compared with EGM2008. The refined geoid based on the two gravity field models indicated that both KTH and RCR method can effectively improve the STD of the geoid model from about six to three centimeters. The refined accuracy of EGM2008 model using RCR and KTH methods is slightly better than that of XGM2016 model in the plain and high mountain areas after seven-parameter fitting. EGM2008 based on the KTH method was the most precise at ± 2.0 cm in the plain area and ± 2.4 cm in the mountainous area. Generally, for the refined geoid based on the two Earth gravity models, KTH produced results similar to RCR in the plain area, and had relatively better performance for the mountainous area where terrestrial gravity data is sparse and unevenly distributed.

Fitting the GPS/Leveling Quasi-Geoid Using Bayesian-Regulation BP Neural Network

2011 ◽  
Vol 90-93 ◽  
pp. 2903-2906
Author(s):  
Lei Song ◽  
Xiao Qing Hu
Keyword(s):  
Neural Network ◽  
Gravity Field ◽  
Bp Neural Network ◽  
Field Model ◽  
Gravity Field Model ◽  
Global Gravity ◽  
Fitting In ◽  
Gps Leveling ◽  
Global Gravity Field Model

The 2.5′×2.5′resolution local quasi-geoid is calculated using the global gravity field model and GPS/leveling data of region which points spacing is about 10km with the Bayesian- regulation BP neural network in this paper. The inner and outer precision of quasi-geoid are both superior 0.05m.The result indicat that the Bayesian regulation BP neural network could improve the precision of fitting and restrain the over-fitting in fitting. The region quasi-geoid excelled than 0.05m can be computed using the global gravity field model and about 10km baseline GPS/leveling data in smoothness region.

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

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.

scholarly journals GRAVITY ANOMALY ASSESSMENT USING GGMS AND AIRBORNE GRAVITY DATA TOWARDS BATHYMETRY ESTIMATION

2016 ◽  
Vol XLII-4/W1 ◽  
pp. 287-297
Author(s):  
A. Tugi ◽  
A. H. M. Din ◽  
K. M. Omar ◽  
A. S. Mardi ◽  
Z. A. M. Som ◽  
...  
Keyword(s):  
Gravity Anomaly ◽  
Gravity Field ◽  
Ocean Circulation ◽  
Gravity Data ◽  
Gravity Anomalies ◽  
Airborne Gravity ◽  
Satellite Gravity ◽  
Earth’S Gravity Field ◽  
Explorer Mission ◽  
Satellite Gravity Missions

The Earth’s potential information is important for exploration of the Earth’s gravity field. The techniques of measuring the Earth’s gravity using the terrestrial and ship borne technique are time consuming and have limitation on the vast area. With the space-based measuring technique, these limitations can be overcome. The satellite gravity missions such as Challenging Mini-satellite Payload (CHAMP), Gravity Recovery and Climate Experiment (GRACE), and Gravity-Field and Steady-State Ocean Circulation Explorer Mission (GOCE) has introduced a better way in providing the information on the Earth’s gravity field. From these satellite gravity missions, the Global Geopotential Models (GGMs) has been produced from the spherical harmonics coefficient data type. The information of the gravity anomaly can be used to predict the bathymetry because the gravity anomaly and bathymetry have relationships between each other. There are many GGMs that have been published and each of the models gives a different value of the Earth’s gravity field information. Therefore, this study is conducted to assess the most reliable GGM for the Malaysian Seas. This study covered the area of the marine area on the South China Sea at Sabah extent. Seven GGMs have been selected from the three satellite gravity missions. The gravity anomalies derived from the GGMs are compared with the airborne gravity anomaly, in order to figure out the correlation (R<sup>2</sup>) and the root mean square error (RMSE) of the data. From these assessments, the most suitable GGMs for the study area is GOCE model, GO_CONS_GCF_2_TIMR4 with the R<sup>2</sup> and RMSE value of 0.7899 and 9.886 mGal, respectively. This selected model will be used in the estimating the bathymetry for Malaysian Seas in future.

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