Overview
Different Data Augmentation Modules are designed to work with specific types of geoscientific data. Understanding which Module to use, and what kind of input or output it expects, helps streamline preprocessing and improves performance in DORA's modelling workflows.
This article summarizes which Modules are best suited to geology, geophysics, and geochemistry, and how each handles inputs and outputs. Some Modules generate one raster per input (1 to 1), others process multiple inputs into a single output (many to 1), and some split a single input into multiple outputs (1 to many).
By Data Type
Geology and Structure
Module | Input Type | Input to Output Relationship | Notes |
Distance Maps | Vector Data | 1 per type → 1 output per type | One raster output per feature category, such as each fault |
Structural Domain Maps | Vector Data | 1 per type → 1 output per type | Orientation-based inputs |
Fault Disturbance Maps | Vector Data | 1 input → 1 output | Calculated using faults and input parameters |
Geophysics
Module | Input Type | Input to Output Relationship | Notes |
Computer Vision Maps | Raster | 1 inputs → multiple outputs | Deep learning (ResNet); single-layer input |
Texture Filter Maps | Raster | 1 input → 4 outputs | Outputs include rasters for Contrast, Correlation, Energy, and Entropy. |
Lineament Maps | Raster | 1 input → 2 outputs | Outputs include Line Density and Structural Complexity |
Geochemistry
Module | Input Type | Input to Output Relationship | Notes |
Multivariate Anomaly Maps | Raster | Multiple inputs → 1 output | Identified anomalies from the input maps. |
Other
Module | Input Type | Input to Output Relationship | Notes |
Data Density Maps | Any spatial data (Vector or Raster) | Multiple inputs → 1 output | Counts the number of datasets contributing to each pixel |
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