Integrated Correction of Nonlinear Dynamic Drift in Terrestrial Mobile Gravity Surveys: A Comparative Study Based on the Northeastern China Gravity Monitoring Network
Αποθηκεύτηκε σε:
| Εκδόθηκε σε: | Remote Sensing vol. 17, no. 12 (2025), p. 2025-2044 |
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| Κύριος συγγραφέας: | |
| Άλλοι συγγραφείς: | |
| Έκδοση: |
MDPI AG
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| Θέματα: | |
| Διαθέσιμο Online: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2072-4292 | ||
| 024 | 7 | |a 10.3390/rs17122025 |2 doi | |
| 035 | |a 3223940340 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231556 |2 nlm | ||
| 100 | 1 | |a Chen, Zhaohui | |
| 245 | 1 | |a Integrated Correction of Nonlinear Dynamic Drift in Terrestrial Mobile Gravity Surveys: A Comparative Study Based on the Northeastern China Gravity Monitoring Network | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The Northeastern China Gravity Monitoring Network (NCGMN; 40–50°N), a pioneering time-variable gravity monitoring system in high-latitude cold-temperate environments, serves as a critical infrastructure for geodynamic investigations of the Songliao Basin, Changbai Mountain volcanic zone, and northern Tan-Lu Fault Zone. To address the data reliability challenges posed by nonlinear dynamic drifts in spring-type relative gravimeters during mobile surveys, this study quantifies—for the first time—the non-smooth normal distribution characteristics of such drifts using the inaugural 2015 dataset from two CG-5 instruments. Results demonstrate a 7–15% reduction in mean dynamic drift rates compared to static conditions, with spatiotemporal variability governed by multi-physics field coupling (terrain undulation, thermal fluctuation, and barometric perturbation). A comprehensive correction framework—integrating a gravimetric line drift rate computation, multi-model validation, and absolute datum cross-validation—reveals gravity value discrepancies up to ±10 μGal across models. The innovative hybrid scheme combines local drift preprocessing (initial-point modeling, line fitting, variance-sum optimization) with global adjustment optimization, achieving the significant suppression of nonlinear drift errors. The variance-sum optimal and Bayesian adjustment hybrid synergizes local variance minimization and global temporal correlation priors, delivering the following: (1) 34% and 29% reductions in segment self-difference standard deviations versus classical and Bayesian adjustments; (2) 24% and 14% decreases in segment residual standard deviations; (3) 12% and 6% improvements in absolute datum cross-validation precision. This study establishes a foundation for the reliable extraction of μGal-level gravity signals, advancing high-precision gravity monitoring of seismicity, volcanic unrest, and fault zone deformation in complex terrains. By harmonizing local-scale accuracy with network-wide consistency, the framework sets a new benchmark for time-variable gravity studies in challenging environments. | |
| 651 | 4 | |a China | |
| 653 | |a Datum (elevation) | ||
| 653 | |a Gravity | ||
| 653 | |a Variance | ||
| 653 | |a Atmospheric pressure | ||
| 653 | |a Normal distribution | ||
| 653 | |a Standard deviation | ||
| 653 | |a Data processing | ||
| 653 | |a Monitoring | ||
| 653 | |a Drift rate | ||
| 653 | |a Comparative studies | ||
| 653 | |a Bayesian analysis | ||
| 653 | |a Seismicity | ||
| 653 | |a Temperate environments | ||
| 653 | |a Volcanic activity | ||
| 653 | |a Optimization | ||
| 653 | |a Earthquakes | ||
| 653 | |a Surveys | ||
| 653 | |a Dynamical systems | ||
| 653 | |a Drift | ||
| 653 | |a Segments | ||
| 653 | |a Nonlinear dynamics | ||
| 653 | |a Mathematical models | ||
| 653 | |a Critical infrastructure | ||
| 700 | 1 | |a Liu, Jinzhao | |
| 773 | 0 | |t Remote Sensing |g vol. 17, no. 12 (2025), p. 2025-2044 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3223940340/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3223940340/fulltextwithgraphics/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3223940340/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch |