ICGEM – 15 years of successful collection and distribution of global gravitational models, associated services, and future plans

Ince, E. Sinem; Barthelmes, Franz; Reißland, Sven; Elger, Kirsten; Förste, Christoph; Flechtner, Frank; Schuh, Harald

doi:10.5194/essd-11-647-2019

Cited by 234 publications

(130 citation statements)

References 38 publications

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“…Massive plantations and canal developments are located at the eastern side of the peat dome, where street and canal networks in blocks can easily be seen in Figure 1. The data used for this research consist of: (1) Geological maps of the Siakinderapura, Tanjung Pinang, and Bengkalis areas with a scale of 1:250,000 from Geological Research and Development Center (P3GL) Republic of Indonesia; (2) Gravity disturbance data of the Tebing Tinggi Island area [37] calculated using the Satellite Gravity Gradiometry Ultra-high Gravity-field Model (SGG-UGM-1) gravity model derived from the Earth Gravitational Model 2008 (EGM2008) and the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) satellite data, (downloaded from http://icgem. gfz-potsdam.de/calcgrid); (3) Peat soil mapping data collected by The Ministry of Environment and Forestry, Republic of Indonesia, generated using ground-based peat probe survey data with a transect pattern for each 500 meters distance between drilling points and 1 km interval distances between the transects, (see Section 3.2. in more detail); (4) Aerial orthophoto with a spatial resolution of 10 cm, taken using a medium format metric camera [38]; and (5) a DTM generated from LiDAR measurement data from the Peat Restoration Agency (BRG), Republic of Indonesia [38].…”

Section: Methodsmentioning

confidence: 99%

The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data

2020

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High-accuracy peat maps are essential for peatland restoration management, but costly, labor-intensive, and require an extensive amount of peat drilling data. This study offers a new method to create an accurate peat depth map while reducing field drilling data up to 75%. Ordinary least square (OLS) adjustments were used to estimate the elevation of the mineral soil surface based on the surrounding soil parameters. Orthophoto and Digital Terrain Models (DTMs) from LiDAR data of Tebing Tinggi Island, Riau, were used to determine morphology, topography, and spatial position parameters to define the DTM and its coefficients. Peat depth prediction models involving 100%, 50%, and 25% of the field points were developed using the OLS computations, and compared against the field survey data. Raster operations in a GIS were used in processing the DTM, to produce peat depth estimations. The results show that the soil map produced from OLS provided peat depth estimations with no significant difference from the field depth data at a mean absolute error of ±1 meter. The use of LiDAR data and the OLS method provides a cost-effective methodology for estimating peat depth and mapping for the purpose of supporting peat restoration.

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Section: Methodsmentioning

confidence: 99%

The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data

2020

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“…For this purpose, data from the SGG‐UTM‐1 model, a combination of EGM2008 data and GOCE satellite data, were used (Liang et al, ). The free‐air anomaly based on this model was calculated with the ICGEM service (Barthelmes, ; Ince et al, ). To avoid the Gibbs effect, ICGEM's “gentle cut” option was used from degree 2000 up to degree 2159 (the maximum degree of the model).…”

Section: Methodsmentioning

confidence: 99%

Analysis of Free‐Air Anomalies on the Seaway of the Gulf of Gdańsk: A Case Study

Pyrchla

Pająk

Pyrchla

et al. 2020

Earth and Space Science

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In this paper, we present an attempt to determine the accuracy of shipborne gravimetry for the needs of geoid determination. The shipborne gravity campaign, described in this article, is the beginning of a series of gravimetry measurements in the Polish Exclusive Economy Zone. The campaign was conducted in the area where the accuracy of geoid determination is crucial for the safety of navigation on numerous intersecting ships' routes. The vicinity of the seashore, various depths, and short-lasting campaign enabled determination of the level of measurement accuracy that can be obtained depending on the conditions. Internal data consistency was estimated as well as an attempt to compute external accuracy. The data were compared with satellite data available for the region. We identified which of the differences are related to the influence of external factors.

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“…The International Center for Global Earth Models [60] database has published 175 geopotential models so far and almost 30% of these models include GOCE mission data. In order to quantify the quality of the GGMs independently, validating the models using external information is necessary.…”

Section: Synthesis Of the Gravity Field Parameters Using Ggms Sphericmentioning

confidence: 99%

An Assessment of the GOCE High-Level Processing Facility (HPF) Released Global Geopotential Models with Regional Test Results in Turkey

2020

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The launch of dedicated satellite missions at the beginning of the 2000s led to significant improvement in the determination of Earth gravity field models. As a consequence of this progress, both the accuracies and the spatial resolutions of the global geopotential models increased. However, the spectral behaviors and the accuracies of the released models vary mainly depending on their computation strategies. These strategies are briefly explained in this article. Comprehensive quality assessment of the gravity field models by means of spectral and statistical analyses provides a comparison of the gravity field mapping accuracies of these models, as well as providing an understanding of their progress. The practical benefit of these assessments by means of choosing an optimal model with the highest accuracy and best resolution for a specific application is obvious for a broad range of geoscience applications, including geodesy and geophysics, that employ Earth gravity field parameters in their studies. From this perspective, this study aims to evaluate the GOCE High-Level Processing Facility geopotential models including recently published sixth releases using different validation methods recommended in the literature, and investigate their performances comparatively and in addition to some other models, such as GOCO05S, GOGRA04S and EGM2008. In addition to the validation statistics from various countries, the study specifically emphasizes the numerical test results in Turkey. It is concluded that the performance improves from the first generation RL01 models toward the final RL05 models, which were based on the entire mission data. This outcome was confirmed when the releases of different computation approaches were considered. The accuracies of the RL05 models were found to be similar to GOCO05S, GOGRA04S and even to RL06 versions but better than EGM2008, in their maximum expansion degrees. Regarding the results obtained from these tests using the GPS/leveling observations in Turkey, the contribution of the GOCE data to the models was significant, especially between the expansion degrees of 100 and 250. In the study, the tested geopotential models were also considered for detailed geoid modeling using the remove-compute-restore method. It was found that the best-fitting geopotential model with its optimal expansion degree (please see the definition of optimal degree in the article) improved the high-frequency regional geoid model accuracy by almost 15%.

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ICGEM – 15 years of successful collection and distribution of global gravitational models, associated services, and future plans

Cited by 234 publications

References 38 publications

The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data

The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data

Analysis of Free‐Air Anomalies on the Seaway of the Gulf of Gdańsk: A Case Study

An Assessment of the GOCE High-Level Processing Facility (HPF) Released Global Geopotential Models with Regional Test Results in Turkey

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