output
20192026
most citedCombining Physically-Based Modeling and Deep Learning for Fusing GRACE Satellite Data: Can We Learn from Mismatch?

226 citations

11 papers

physics.geo-ph2026

Cemented fibers as a testbed for distributed acoustic sensing (DAS)

Thomas Forbriger, Felix Münch, Laura Hillmann +6

A rigid connection between the optical fiber and the rock makes amplitudes of 'fiber strain' measured with Distributed Acoustic Sensing (DAS) equal to 'rock strain'. We demonstrate…

cs.CV2024★ 10 cited

Micro-Structures Graph-Based Point Cloud Registration for Balancing Efficiency and Accuracy

Rongling Zhang, Li Yan, Pengcheng Wei +3

Point Cloud Registration (PCR) is a fundamental and significant issue in photogrammetry and remote sensing, aiming to seek the optimal rigid transformation between sets of points.…

physics.geo-ph2021★ 9 cited

Inner core static tilt inferred from intradecadal oscillation in the Earth's rotation

Yachong An, Hao Ding, Zhifeng Chen +2

The geodynamic state of the inner core remains an enigma, encompassing the presence of a static tilt between the inner core and mantle. Following the experimental confirmation of a…

physics.ao-ph2021★ 108 cited

Improving prediction of the terrestrial water storage anomalies during the GRACE and GRACE-FO gap with Bayesian convolutional neural networks

Shaoxing Mo, Yulong Zhong, Xiaoqing Shi +3

The Gravity Recovery and Climate Experiment (GRACE) satellite and its successor GRACE Follow-On (GRACE-FO) provide valuable and accurate observations of terrestrial water storage a…

physics.geo-ph2020★ 10 cited

Impact of non-tidal station loading in LLR

Vishwa Vijay Singh, Liliane Biskupek, Jürgen Müller +1

Lunar Laser Ranging (LLR) measures the distance between observatories on Earth and retro-reflectors on Moon since 1970. In this paper, we study the effect of non-tidal station load…

eess.IV2020★ 2 cited

Spectral Response Function Guided Deep Optimization-driven Network for Spectral Super-resolution

Jiang He, Jie Li, Qiangqiang Yuan +2

Hyperspectral images are crucial for many research works. Spectral super-resolution (SSR) is a method used to obtain high spatial resolution (HR) hyperspectral images from HR multi…