Geoid of South East Sulawesi from airborne gravity using Hotine approach

Sabri, LM; Sudarsono, Bambang; Pahlevi, Arisauna Maulidyan

doi:10.1088/1755-1315/731/1/012014

Cited by 3 publications

(4 citation statements)

References 2 publications

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“…N is the geoid height or geoid undulation; in this case, it is the geometric geoid undulation. Determining geometric undulation values can use absolute or relative equations [16]. The final equation is used to obtain the undulation value from one point.…”

Section: Geometric Undulationmentioning

confidence: 99%

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Analysis of Determining Geoid Height Values in Urban Areas

Sari,

Shodiq,

Syauqi

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Floods have a significant impact on human life. To reduce the risk due to flooding, mitigation is needed. Mitigation can be done when information about the flood model has been mapped. Flood modeling requires primary data in height values with reasonable accuracy. The essential data can be obtained through INAGEOID2020. INAGEOID2020 cannot be used optimally due to a lack of information regarding its accuracy. The validation process has been carried out on 5 (five) significant islands. One is the island of Borneo, which focuses on the Kalimantan Barat and Kalimantan Timur Provinces. In the two provinces, the accuracy of 5.88 to 6.43cm. There is no information about the accuracy of INAGEOID2020 in the Kalimantan Selatan Province. So, it is necessary to validate INAGEOID2020 in that province. So, validation activities are needed to get the accuracy of INAGEOID2020 in Kalimantan Selatan. Research requires two types of data, namely primary and secondary data. Preliminary data was obtained by carrying out GNSS observations. In addition, measurements of height differences between validation points were also carried out. In addition, terrestrial gravity data is needed at the validation point as a corrector value for height difference measurements. Secondary data was obtained from the Geospatial Information Agency as validation point gravimetric undulation values. Before carrying out the INAGEOID2020 validation, a geometric undulation calculation must be carried out by utilizing the leveling and GNSS data calculation results. This article shows that the geometric undulation standard deviation value results are 0.368 m, and the RMS value is 0.336 m.

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Section: Geometric Undulationmentioning

confidence: 99%

“…The final equation is used to obtain the undulation value from one point. The fundamental equation for determining the geometric geoid undulation value is shown in Equation 3 [16].…”

Section: Geometric Undulationmentioning

confidence: 99%

Analysis of Determining Geoid Height Values in Urban Areas

Sari,

Shodiq,

Syauqi

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…With the enrichment of measurement means, the breadth and depth of geospatial data are being continuously improved by terrestrial, shipborne, airborne and satellite gravity surveys, etc. [2][3][4][5][6][7]. The unified land-ocean quasi-geoid can be constructed by fusing heterogeneous data sets in the boundary areas between land and ocean, which is beneficial to advance the construction of land-ocean integration.…”

Section: Introductionmentioning

confidence: 99%

Unified Land–Ocean Quasi-Geoid Computation from Heterogeneous Data Sets Based on Radial Basis Functions

Liu

Lou

2022

Remote Sensing

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The determination of the land geoid and the marine geoid involves different data sets and calculation strategies. It is a hot issue at present to construct the unified land–ocean quasi-geoid by fusing multi-source data in coastal areas, which is of great significance to the construction of land–ocean integration. Classical geoid integral algorithms such as the Stokes theory find it difficult to deal with heterogeneous gravity signals, so scholars have gradually begun using radial basis functions (RBFs) to fuse multi-source data. This article designs a multi-layer RBF network to construct the unified land–ocean quasi-geoid fusing measured terrestrial, shipborne, satellite altimetry and airborne gravity data based on the Remove–Compute–Restore (RCR) technique. EIGEN-6C4 of degree 2190 is used as a reference gravity field. Several core problems in the process of RBF modeling are studied in depth: (1) the behavior of RBFs in the spatial domain; (2) the locations of RBFs; (3) ill-conditioned problems of the design matrix; (4) the effect of terrain masses. The local quasi-geoid with a 1′ resolution is calculated, respectively, on the flat east coast and the rugged west coast of the United States. The results show that the accuracy of the quasi-geoid computed by fusing four types of gravity data in the east coast experimental area is 1.9 cm inland and 1.3 cm on coast after internal verification (the standard deviation of the quasi-geoid w.r.t GPS/leveling data). The accuracy of the quasi-geoid calculated in the west coast experimental area is 2.2 cm inland and 2.1 cm on coast. The results indicate that using RBFs to calculate the unified land–ocean quasi-geoid from heterogeneous data sets has important application value.

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“…Pahlevi et al (2015) contains 44 points using circles, and the third GPS/leveling dataset obtained fromSabri et al (2021) contains 11 points using squares in southeastern Sulawesi. As mentioned above, the orthometric heights obtained from a leveling route refer to an MSL observed at a specific tidal station.…”

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confidence: 99%

Advanced Geoid Modeling in Sulawesi and Accuracy Verification Strategies for Accommodating Diverse MSL Vertical Datums

Shih,

Heliani,

Hsiao

et al. 2024

Preprint

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This study aims to improve the accuracy of the geoid model in Sulawesi, which is crucial for converting GNSS-observed ellipsoid heights to orthometric heights. There are limitations of terrestrial gravity surveys in Indonesia due to its complex geography, so airborne gravity surveys were conducted from 2008 to 2019 through a collaboration between BIG, the Technical University of Denmark (DTU), and the National Chiao Tung University (NCTU) gravity research team. The airborne gravity data currently cover almost the entire land area of Indonesia. The geoid modeling process involved refining the EGM08-derived geoid heights by incorporating downward-continued airborne gravity data and RTM-derived geoid effects and adjusting the geometric geoid heights to accommodate variations in the mean sea levels observed in different GPS/leveling datasets. The study revealed that airborne gravity data significantly improved the accuracy of the geoid, achieving an impressive accuracy of approximately 0.04 cm. Additionally, this study examined the impacts of different global gravitational models (GGMs), such as EIGEN-6C4, GECO, XGM2019e, and SGG-UGM-2, on geoid modeling and revealed that differences arise from the different datasets used in the development process of the GGM. The modeling approach significantly improves the accuracy of the geoid from decimeter-level accuracy to centimeter-level accuracy. Accurate geoids are critical for infrastructure development, land-use planning, and resource management and play an integral role in supporting sustainable development goals (SDGs) by providing accurate spatial referencing, ensuring precise mapping, and offering location-based services.

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Geoid of South East Sulawesi from airborne gravity using Hotine approach

Cited by 3 publications

References 2 publications

Analysis of Determining Geoid Height Values in Urban Areas

Analysis of Determining Geoid Height Values in Urban Areas

Unified Land–Ocean Quasi-Geoid Computation from Heterogeneous Data Sets Based on Radial Basis Functions

Advanced Geoid Modeling in Sulawesi and Accuracy Verification Strategies for Accommodating Diverse MSL Vertical Datums

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