Estimating Subsurface Geostatistical Properties from GPR Reflection Data Using a Supervised Deep Learning Approach

The quantitative characterization of near-surface heterogeneity using ground-penetrating radar (GPR) is an important but challenging task. The estimation of subsurface geostatistical parameters from surface-based common-offset GPR reflection data has so far relied upon a Monte-Carlo-type inversion a...

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Bibliographic Details
Main Authors: Yu Liu, James Irving, Klaus Holliger
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/17/13/2284
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