Iterative ratio method: A method to map the depth to the Moho from gravity anomalies using linear approximate invariance

Potential fields as a tool to characterize the inaccessible areas of the earth: The case of Pine Island–Ellsworth Mountains area, West Antarctica

Introduction to this special section: Gravity, electrical, and magnetic methods

Deep learning to estimate the basement depth by gravity data using a feedforward neural network

Unsupervised boundary analysis of potential field data: A machine learning method

Analysis of direct current resistivity data using continuous wavelet transform

Assessing model uncertainty for the scaling function inversion of potential fields

Self-constrained inversion of potential fields through a 3D depth weighting

Depth estimation from downward continuation: An entropy-based approach to normalized full gradient

A method for inversion of 1D vertical soundings of gravity anomalies

On the estimation of the structural index from low-pass filtered magnetic data

A computationally efficient tool for assessing the depth resolution in large-scale potential-field inversion

A fast interpretation of self-potential data using the depth from extreme points method

Understanding imaging methods for potential field data

Multiridge analysis of potential fields: Geometric method and reduced Euler deconvolution

DEXP: A fast method to determine the depth and the structural index of potential fields sources

Analysis of depth resolution in potential-field inversion

Reply by the authors to the discussions by D. W. Oldenburg and Y. Li, and by G. Strykowski and F. Boschetti

Upward continuation of scattered potential field data

3-D inversion of gravity and magnetic data with depth resolution