Improvement of Downward Continuation Values of Airborne Gravity Data in Taiwan

Zhao, Qingzhi; Xu, Xinyu; Forsberg, R.; Strykowski, Gabriel

doi:10.3390/rs10121951

Cited by 8 publications

(9 citation statements)

References 37 publications

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“…This indicated that there was a systematic error (bias) present in the airborne gravity data compared to the terrestrial gravity data. A slightly larger systematic error was found in some other studies, such as: Hwang et al (2007, Table 2), McCubbine (2016, Table 6.5) and Zhao et al (2018), where mean values of the differences were 1.5, 1.0, and − 1.9 mGal, respectively. The expected impact on the determined geoid undulation caused by the bias of airborne gravity data was estimated using Eq.…”

Section: Analysis Of Airborne and Terrestrial Gravity Data Errorsmentioning

confidence: 44%

“…The method was used in several studies; see, e.g. Alberts and Klees (2004), Barzaghi et al (2009), Goli and Najafi-Alamdari (2011), McCubbine et al (2017), andZhao et al (2018). Global gravity field and topography information were used to remove and restore low-and high-frequency gravity contents before and after DWC.…”

Section: Downward Continuation Of Airborne Gravity Datamentioning

confidence: 99%

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

Varga¹,

Pitoňák

Novák

et al. 2021

J Geod

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This 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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Section: Analysis Of Airborne and Terrestrial Gravity Data Errorsmentioning

confidence: 44%

Section: Downward Continuation Of Airborne Gravity Datamentioning

confidence: 99%

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

Varga¹,

Pitoňák

Novák

et al. 2021

J Geod

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“…The accuracy of GraviMob measurements can be then assessed using the downward continued shipborne data. In this study, the Least-Squares Collocation (LSC) approach [20] adapted to the Remove-Compute-Restore (RCR) method was used as it offers several advantages [21][22][23][24][25]. This method enables interpolation anywhere in the 3D space and input data do not need to be at the same height/depth.…”

Section: Downward Continuation Modelmentioning

confidence: 99%

“…Therefore, terrain effects were used to complement EGM2008 in the calculation of the gravimetric geoid/quasi-geoid [35], and the geopotential value for the establishment of a modern local [36,37] or international [38] height reference system. The RTM effects also play an important role in the upward/downward continuation procedure used to validate airborne gravity data (see [23,39,40]). These studies indicated that the incorporation of the RTM effects substantially improved the accuracy of the DC airborne gravity anomalies, especially in mountainous areas.…”

Section: Downward Continuation Of Shipborne Gravity Datamentioning

confidence: 99%

High-Resolution Gravity Measurements on Board an Autonomous Underwater Vehicle: Data Reduction and Accuracy Assessment

Vu,

Verdun,

Cali

et al. 2024

Remote Sensing

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Gravity on Earth is of great interest in geodesy, geophysics, and natural resource exploration. Ship-based gravimeters are a widely used instrument for the collection of surface gravity field data in marine regions. However, due to the considerable distance from the sea surface to the seafloor, the spatial resolution of surface gravity data collected from ships is often insufficient to image the detail of seafloor geological structures and to explore offshore natural minerals. Therefore, the development of a mobile underwater gravimetry system is necessary. The GraviMob gravimeter, developed for a moving underwater platform by Geo-Ocean (UMR 6538 CNRS-Ifremer-UBO-UBS), GeF (UR4630, Cnam) and MAPPEM Geophysics, has been tested over the last few years. In this study, we report on the high-resolution gravity measurements from the GraviMob system mounted on an Autonomous Underwater Vehicle, which can measure at depths of up to several kilometres. The dedicated GraviMob underwater gravity measurements were conducted in the Mediterranean Sea in March 2016, with a total of 26 underwater measurement profiles. All these measurement profiles were processed and validated. In a first step, the GraviMob gravity measurements were corrected for temperature based on a linear relationship between temperature and gravity differences. Through repeated profiles, we acquired GraviMob gravity measurements with an estimated error varying from 0.8 to 2.6 mGal with standard deviation after applying the proposed temperature correction. In a second step, the shipborne gravity data were downward continued to the measurement depth to validate the GraviMob measurements. Comparisons between the corrected GraviMob gravity anomalies and downward continued surface shipborne gravity data revealed a standard deviation varying from 0.8 to 3.2 mGal and a mean bias value varying from −0.6 to 0.6 mGal. These results highlight the great potential of the GraviMob system in measuring underwater gravity.

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“…The LSC algorithm has been used to estimate crustal movement signals from GPS velocity fields [9][10][11][12][13][14][15]. It has also been used in various earth science fields to control systematic and anomaly errors in GIS spatial data [16], detect outliers in multibeam bathymetric data [17], solve common point coordinate errors in 3D coordinate transformation [18], improve the accuracy of mobile light detection and ranging (LiDAR) systems in hostile environments [19], improve the results of downward continuation values of airborne gravity data [20], and refine the local covariance model of gravity anomalies [21].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Least-Squares Collocation Algorithm Considering Distance Scale Factor for GPS Crustal Velocity Field Fitting and Estimation

Chen

Liang

et al. 2019

Remote Sensing

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High-precision, high-reliability, and high-density GPS crustal velocity are extremely important requirements for geodynamic analysis. The least-squares collocation algorithm (LSC) has unique advantages over crustal movement models to overcome observation errors in GPS data and the sparseness and poor geometric distribution in GPS observations. However, traditional LSC algorithms often encounter negative covariance statistics, and thus, calculating statistical Gaussian covariance function based on the selected distance interval leads to inaccurate estimation of the correlation between the random signals. An unreliable Gaussian statistical covariance function also leads to inconsistency in observation noise and signal variance. In this study, we present an improved LSC algorithm that takes into account the combination of distance scale factor and adaptive adjustment to overcome these problems. The rationality and practicability of the new algorithm was verified by using GPS observations. Results show that the new algorithm introduces the distance scale factor, which effectively weakens the influence of systematic errors by improving the function model. The new algorithm can better reflect the characteristics of GPS crustal movement, which can provide valuable basic data for use in the analysis of regional tectonic dynamics using GPS observations.

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Improvement of Downward Continuation Values of Airborne Gravity Data in Taiwan

Cited by 8 publications

References 37 publications

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

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

High-Resolution Gravity Measurements on Board an Autonomous Underwater Vehicle: Data Reduction and Accuracy Assessment

Adaptive Least-Squares Collocation Algorithm Considering Distance Scale Factor for GPS Crustal Velocity Field Fitting and Estimation

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