Remote sensing in geology

Remote Sensing in Geology

Overview

  • Remote sensing encompasses the technologies and techniques employed to gather information about the Earth's features without direct physical contact.

  • It is utilized extensively in geology for processing, exploration, and application.

Remote Sensing Platforms

  • Common platforms include:

    • Landsat

    • SPOT

    • AVIRIS (Airborne Visible/Infrared Imaging Spectrometer)

Hyperspectral Imaging

  • Definition:

    • Utilizes ten to hundreds of bands with smaller wavelengths (0.01 µm).

  • Significance:

    • Ideal for mineral and lithology identification due to the unique spectral reflectance of Earth materials, especially in the infrared region.

  • Example:

    • AVIRIS is an important tool in hyperspectral imaging.

Importance of Remote Sensing in Geology

  • Spectral Characteristics:

    • Many minerals, rocks, and soils possess unique spectral absorption and reflectance, aiding in geological exploration.

  • Processing Techniques:

    • Various techniques enhance and detect different Earth materials, improving the efficacy of analysis.

Digital Image Processing Techniques

  • Key Processes Involved:

    • Atmospheric Correction: Addresses atmospheric interference on images.

    • Geometric Distortions: Corrects distortions caused by viewing angles or satellite movement.

    • Contrast Enhancement: Improves image clarity and detail.

    • Density Slicing: Categorizes data into various ranges for better visualization.

    • Edge Enhancement: Improves the visibility of object edges.

    • Intensity, Hue, Saturation (IHS): Adjusts image colors.

    • Mosaicking: Combines multiple images to create a comprehensive view.

    • Principal Component Analysis (PCA): Reduces image complexity.

    • Ratio Images: Enhances features by comparing different bands.

    • Colour Combination: Utilizes various spectral bands in RGB formats.

Image Restoration Techniques

Atmospheric Correction

  • Removes haze effects caused by atmospheric scattering of light, improving image brightness and contrast.

Geometric Correction

  • Accounts for distortions due to camera angles and Earth's rotation, ensuring accurate spatial representation.

Image Enhancement Techniques

Contrast Enhancement

  • Uses rapid intensity scaling (0 to 255) to achieve optimal contrast, thus displaying a full range of colors from black to white.

Intensity, Hue, Saturation

  • Addresses and corrects under-saturation issues, enhancing the visual quality of the image.

Edge Enhancement

  • Focuses on improving the visibility of edges within images to aid in further analysis.

Information Extraction Techniques

Band Combination

  • Experiment with different spectral bands to enhance imagery based on specific geological objectives.

    • Examples of combinations include:

      • True Colour Composite (RGB: 321)

      • False Colour Composite (RGB: 452)

Ratios and Transformations

Ratio Transformation

  • Definition: Ratio transformations minimize environmental effects on imagery and highlight subtle differences between materials.

  • Applications: Useful in discriminating between soils and vegetation.

  • Calculation: The number of unique ratio combinations for a multispectral sensor with P bands is computed as n= P(P-1).

Applications of Remote Sensing in Geology

  • Common Uses:

    • Landslide assessment

    • Mineral exploration

    • Geothermal studies

    • Lithology mapping

    • Geomorphological studies

    • Hydrology analysis

Key Satellites in Geological Studies

  • Notable satellites for geological remote sensing include:

    • Landsat

    • SPOT

    • ASTER

    • AVIRIS

Important Considerations in Remote Sensing and Mapping

  • Factors to Consider:

    • Contrast

    • Size of objects (e.g., landslides, geological materials)

    • Methods of interpretation

    • Experience of the interpreter with the technology

Principles of Remote Sensing

  • Spectral Contrast:

    • Different objects exhibit distinct spectral contrasts that can be analyzed.

  • Color and Shape Distinction:

    • Ability to differentiate objects based on their appearance and surrounding materials.

Specific Principles in Geological Contexts

Landslide Mapping

  • Case Studies:

    • Example from Sunkosi River using Landsat imagery to identify landslides in true and false color composites.

Lithology Analysis

  • Usage of ASTER Images:

    • Thermal infrared bands display variations in mineral contents with distinct colors representing quartz, carbonate rocks, etc.

Geomorphology Mapping

  • Landsat Observations:

    • Tracks changes in vegetation and stream channels, providing insight into dynamic geomorphological processes.

Mineral Exploration

  • ASTER Imagery Applications:

    • Identification of minerals based on their spectral signatures, aiding in recognizing various rock types and locations of ore deposits.

Approaches for Mineral Exploration

  • Mapping geological features and fracture patterns on multiple scales.

  • Detecting tendencies of mineral concentration based on intersecting lineaments, indicating potential mineral deposits.

Contribution to Field Mapping

Mineral Exploration

  • Digitally processed images allow geologists to interpret rock types and locate minerals efficiently.

Landslide Mapping

  • Monitoring landslide occurrences and patterns, including detection of past events in remote areas through spectral analysis.

Limitations of Remote Sensing

For Mineral Exploration

  • Issues include low signal-to-noise ratios and similarities in spectral signatures among neighboring materials, hampering distinct identification.

For Landslide Studies

  • Satellite data is most effective for larger features and requires validation through ground-truthing due to limitations in detail and temporal data availability.