Back to search

Article

Mutual Information assessment of the quality of the GRAV-D airborne gravity data and its compatibility with the NGS’ historical surface gravity database

2026-07-09

Abstract excerpt

<title>Abstract</title> <p>The Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project acquired airborne gravity observations across the United States, extending at least 150 km into Canada, Mexico, and the surrounding oceans. In this study, we investigate the Mutual Information (MI) of the GRAV-D dataset and explore the scientific interpretation of the resulting MI maps. Mutual Information q...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
c3f0e2d8-87d2-5d5b-8f5f-2442c7f693ab
DOI
10.21203/rs.3.rs-10267680/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 8 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Mutual Information assessment of the quality of the GRAV-D airborne gravity data and its compatibility with the NGS’ historical surface gravity databaseDOI 10.21203/rs.3.rs-10267680/v1
Graph-Based Learning for Multi-Horizon Martian Atmospheric ForecastingSemantic proximity
An extended w-test for outlier diagnostics in linear modelsSemantic proximity
Comparative Study of Ground-Based and Satellite Observations of Pc5 Geomagnetic Pulsations During Solar Cycle 23Semantic proximity
A New Approach to Generate Dynamical Cone of Uncertainty for Cyclone Track Forecast over North Indian OceanSemantic proximity
GenAI Minimum Acceptance Checks Static and Dynamic Model Checking of Conditioning Generative Artificial Intelligence Models for Subsurface ModelingSemantic proximity
A Deep Learning Ensemble Framework for Off-Nadir Geocentric Pose PredictionSemantic proximity
Automatic Multi-Temporal Land Cover Mapping with Fine Spatial Resolution Using the Model Migration MethodSemantic proximity
Urban Ground Subsidence Monitoring and Prediction Using Time-Series InSAR and Machine Learning Approaches: A Case Study of Tianjin, ChinaSemantic proximity
Select a neighboring publication to make it the new centre.