Geoid determination using airborne gravity vectors
Bibliographic record
Abstract
Abstract In traditional airborne gravimetry, the vertical component of the gravity vector is used as an approximation of the measured magnitude of the gravity vector, which enters the determination of the local geoid. In this study, a comprehensive computational scheme for determining the local geoid using three components of the airborne gravity vector is presented. Our approach extends the existing one-step method for local geoid modeling by incorporating the full gravity vector measured by airborne sensors as boundary values in the gravimetric boundary-value problem. We derive integral kernel functions along with far-zone contributions for the three components of the airborne gravity vector and apply deterministic modifications to them. To validate our derivations, we use a global geopotential model (GGM)-based airborne gravity vectors burdened with realistic colored noise at one of the most challenging test sites for geoid determination, the 1-cm geoid test area in Colorado (USA). Results of closed-loop tests confirm that applying all three components of the GGM-based airborne gravity vector improves the internal accuracy of the geoid by 50% compared to using only the vertical component. We further use real airborne gravity vectors observed at a test site in the same region and show that the STD of the estimated geoid heights evaluated against the reference geoidal heights along the Geoid Slope Validation Survey of 2017 (GSVS17) Line is 2.3 cm using the “traditional approach” and 1.3 cm including the horizontal components. This indicates a significant improvement in the external accuracy (~ 46%) of the geoid when the full gravity vector is used, without using other heterogeneous observations. Graphical Abstract
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".