8.4 Digital elevation models and terrain analysis

Digital elevation models (DEMs) are vital tools in geophysics, offering a grid-based view of Earth's surface. They're created using various methods, from ground surveys to satellite data, each with its own accuracy and resolution.

DEMs enable terrain analysis, revealing crucial info about slopes, drainage, and landforms. By integrating DEMs with other data, we can explore subsurface structures, monitor deformation, and tackle real-world issues like landslide risks and groundwater exploration.

Digital Elevation Models: Principles and Methods

Generation of Digital Elevation Models

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• Digital elevation models (DEMs) are grid-based representations of the Earth's surface where each cell in the grid contains an elevation value
• DEMs provide a continuous representation of terrain elevations across a landscape
• DEMs can be generated using various data sources:
  • Ground surveys involve collecting elevation data using traditional surveying methods (total stations or GPS receivers) to create high-resolution DEMs for small areas
  • Aerial photogrammetry utilizes overlapping aerial photographs to derive elevation information through stereoscopic analysis, enabling the creation of DEMs for larger areas
  • LiDAR (Light Detection and Ranging) systems emit laser pulses and measure the time taken for the pulses to return, allowing the calculation of precise elevation values and the generation of high-resolution DEMs
  • InSAR (Interferometric Synthetic Aperture Radar) techniques use the phase differences between two or more SAR images acquired at different times to estimate surface elevation changes and generate DEMs
  • SRTM (Shuttle Radar Topography Mission) employed a radar system onboard the Space Shuttle to collect global elevation data, resulting in a near-global DEM with a resolution of approximately 90 meters

Accuracy and Uncertainties in Digital Elevation Models

• The accuracy and resolution of DEMs depend on the data acquisition method, spatial resolution, and post-processing techniques applied
• Higher resolution DEMs provide more detailed terrain information but require more computational resources and storage space
• DEMs are subject to errors and uncertainties:
  • Vertical and horizontal accuracy limitations
  • Data gaps and artifacts
• Assessing and quantifying these uncertainties is important to ensure appropriate use and interpretation of DEMs in geophysical applications

Terrain Analysis for Geomorphological and Hydrological Insights

Quantitative Characterization of Topographic Attributes

• Terrain analysis techniques involve the quantitative characterization of topographic attributes and landforms using DEMs
• These techniques enable the extraction of valuable geomorphological and hydrological information
• Slope represents the steepness of the terrain, while aspect indicates the direction of the maximum slope
  • These attributes provide insights into surface processes (erosion, runoff, and solar radiation exposure)
• Curvature analysis helps identify convex, concave, and planar surfaces, which are indicative of different geomorphological processes
  • Profile curvature describes the rate of change of slope in the direction of the maximum slope
  • Plan curvature represents the rate of change of aspect in the perpendicular direction

Hydrological Analysis and Derived Terrain Attributes

• Hydrological analysis using DEMs allows the delineation of drainage networks, catchment boundaries, and flow accumulation patterns
• Flow direction algorithms (D8 method) determine the direction of water flow based on the steepest descent from each cell
• Catchment delineation involves identifying the contributing area draining to a specific point or outlet, enabling the study of hydrological processes and water resource management
• Flow accumulation calculations determine the number of upslope cells draining into each cell, highlighting areas of concentrated water flow
• Topographic wetness index (TWI) is a derived terrain attribute that combines slope and upstream contributing area to identify areas prone to soil saturation and surface runoff
  • TWI is useful for mapping potential wetlands, groundwater recharge zones, and areas susceptible to flooding
• Geomorphometric analysis techniques (landform classification and feature extraction) can be applied to DEMs to automatically identify and map geomorphological features (ridges, valleys, peaks, and depressions)
  • These techniques rely on algorithms that analyze the local geometry and context of the terrain

DEM Integration for Geophysical Interpretation

Enhancing Understanding through Data Integration

• Integrating DEMs with other geospatial data sources enhances the understanding and interpretation of geophysical processes and phenomena
• This integration allows for a more comprehensive analysis of the Earth's surface and subsurface
• Geological maps and structural data can be overlaid on DEMs to visualize the spatial relationships between topography and geological features
  • This integration helps in understanding the influence of geological structures (faults and folds) on the landscape morphology and drainage patterns
• Combining DEMs with remote sensing data (multispectral and hyperspectral imagery) enables the identification and mapping of surface materials, vegetation cover, and land use patterns
  • This integration facilitates the study of surface processes (erosion, deposition, and land cover change)

Integrating Geophysical and Deformation Data

• Geophysical data (gravity, magnetic, and seismic surveys) can be integrated with DEMs to explore subsurface structures and properties
  • By combining surface topography with geophysical anomalies, researchers can better constrain the interpretation of subsurface features and their relationship to surface expressions
• Integration of DEMs with GPS and InSAR-derived surface deformation data allows for the monitoring and analysis of ground movements (earthquakes, volcanic activity, and landslides)
  • This integration helps in understanding the spatial and temporal patterns of surface deformation and their potential impacts on the landscape
• Hydrological modeling can benefit from the integration of DEMs with data on soil properties, land cover, and climate variables
  • This integration enables the simulation of surface and subsurface water flow, soil moisture dynamics, and the assessment of water resources and flood hazards
• Integrating DEMs with geospatial data requires careful consideration of data resolution, accuracy, and coordinate systems
  • Proper data preprocessing (resampling, reprojection, and error assessment) is essential to ensure compatibility and minimize uncertainties in the integrated analysis

DEM Applications in Landslide Susceptibility and Groundwater Exploration

Landslide Susceptibility Mapping

• DEMs serve as valuable inputs for various geophysical applications, enabling the analysis and modeling of Earth surface processes and subsurface phenomena
• Landslide susceptibility mapping involves assessing the likelihood of landslide occurrence based on topographic, geological, and environmental factors
• DEMs provide essential topographic information (slope gradient, aspect, and curvature) which are key predictors of landslide susceptibility
• Slope stability analysis using DEMs helps identify areas with steep slopes and high relief, which are more prone to landslides
  • By combining slope data with information on soil properties, land cover, and rainfall patterns, researchers can develop landslide susceptibility models
• DEMs enable the calculation of topographic attributes (topographic wetness index and stream power index) which are indicators of potential soil saturation and erosive power
  • These attributes contribute to the assessment of landslide triggering factors
• Integration of DEMs with geotechnical data (soil strength parameters and groundwater conditions) enhances the accuracy and reliability of landslide susceptibility mapping
  • This integration allows for the consideration of both surface and subsurface factors influencing slope stability

Groundwater Exploration

• Groundwater exploration relies on DEMs to understand the topographic controls on groundwater flow, recharge, and discharge processes
• DEMs provide valuable insights into the geomorphological and hydrological characteristics of an area, aiding in the identification of potential groundwater resources
• Delineation of drainage networks and catchment boundaries using DEMs helps identify areas of groundwater recharge and discharge
  • By analyzing the flow accumulation patterns and topographic lows, researchers can locate potential groundwater accumulation zones
• Integration of DEMs with geological and hydrogeological data (lithology, fracture networks, and aquifer properties) enables the mapping of groundwater potential
  • This integration allows for the identification of permeable formations, structural controls on groundwater flow, and areas with favorable recharge conditions
• DEMs can be used to derive topographic indices (topographic wetness index) which are indicative of soil moisture and groundwater potential
  • These indices help prioritize areas for groundwater exploration and well placement
• Combining DEMs with geophysical data (electrical resistivity and seismic surveys) enhances the characterization of subsurface hydrogeological conditions
  • This integration aids in the delineation of aquifer boundaries, estimation of aquifer thickness, and identification of preferential groundwater flow paths