Terrain Analysis and Geomorphometry

Terrain analysis — or geomorphometry — is the quantitative characterisation of land-surface form from digital elevation models (DEMs). It is one of the original strengths of the Whitebox platform and covers first-order derivatives (slope, aspect), curvature families, terrain position, roughness, multiscale analysis, and visibility.

This chapter walks through a complete primary-derivative workflow in the QGIS Processing Toolbox, followed by a Python console version for batch scripting.

Key Concepts

• DEM: Raster where each cell stores surface elevation. All terrain derivatives begin here. Common sources: LiDAR bare-earth, drone photogrammetry, SRTM, Copernicus DEM.
• Slope: Maximum rate of elevation change per unit distance (degrees or percent). Core input for erosion, landslide, and routing models.
• Aspect: Compass direction a slope faces (0–360°, clockwise from north). Flat cells are assigned –1. Controls solar insolation and moisture.
• Curvature: Rate of change of slope. Profile curvature describes flow acceleration/deceleration; plan curvature describes flow convergence/divergence.
• TPI / geomorphons: Terrain position indices and landform classification assign cells to ridge, slope, valley, etc., without manual thresholds.
• TWI: Topographic Wetness Index — ln(upslope area / tan(slope)) — predicts persistent soil moisture and runoff zones.

End-to-End Workflow: Primary Terrain Derivatives

This workflow takes a raw DEM through sink filling, then derives the most commonly used terrain surfaces.

Inputs

Step 1 — Fill Depressions

Sinks (isolated low cells) in a DEM cause flow-routing artifacts in all downstream terrain derivatives. Fill them first.

Processing Toolbox → Whitebox Workflows → Spatial Hydrology → Fill Depressions

Why fix flats? Perfectly flat areas produce ambiguous flow directions. Adding a tiny gradient across flats ensures a routable surface.

Step 2 — Slope

Processing Toolbox → Whitebox Workflows → Terrain Analysis → Slope

Expected output range: 0° (flat) to ~85° (near-vertical cliff). Values above 70° often indicate interpolation artefacts — inspect those cells.

Step 3 — Aspect

Processing Toolbox → Whitebox Workflows → Terrain Analysis → Aspect

Flat cells receive –1. Apply a pseudocolor ramp (circular HSV) to aspect for intuitive visualisation of slope direction.

Step 4 — Hillshade

Processing Toolbox → Whitebox Workflows → Terrain Analysis → Hillshade

Set the hillshade layer to Multiply blend mode in QGIS and overlay it on a coloured DEM for a publication-quality relief map.

Step 5 — Profile and Plan Curvature

Processing Toolbox → Whitebox Workflows → Terrain Analysis → Profile Curvature

Repeat for Plan Curvature → plan_curv.tif.

Style both outputs with a diverging colour ramp centred on 0. Negative profile curvature (blue) marks deceleration zones (valley bottoms); positive (red) marks acceleration zones (ridge crests). Plan curvature negatives mark convergent hollows; positives mark divergent noses.

Step 6 — Topographic Wetness Index

Processing Toolbox → Whitebox Workflows → Terrain Analysis → Wetness Index

High TWI values (> 8–10) indicate persistent moisture zones. Use as a predictor variable in soil, flood, and habitat models.

Python Console Equivalent

Paste the following into the QGIS Python Console (Plugins → Python Console) or save as a Processing script to batch multiple DEMs.

import processing

dem = '/data/dem.tif'

# Step 1: fill depressions
processing.run('whitebox_workflows:fill_depressions', {
    'dem': dem,
    'fix_flats': True,
    'flat_increment': 0.001,
    'output': '/data/dem_filled.tif',
})

# Step 2: slope
processing.run('whitebox_workflows:slope', {
    'dem': '/data/dem_filled.tif',
    'units': 'Degrees',
    'zfactor': 1.0,
    'output': '/data/slope.tif',
})

# Step 3: aspect
processing.run('whitebox_workflows:aspect', {
    'dem': '/data/dem_filled.tif',
    'output': '/data/aspect.tif',
})

# Step 4: hillshade
processing.run('whitebox_workflows:hillshade', {
    'dem': '/data/dem_filled.tif',
    'azimuth': 315.0,
    'altitude': 45.0,
    'zfactor': 1.0,
    'output': '/data/hillshade.tif',
})

# Step 5: curvature
processing.run('whitebox_workflows:profile_curvature', {
    'dem': '/data/dem_filled.tif',
    'output': '/data/profile_curv.tif',
})
processing.run('whitebox_workflows:plan_curvature', {
    'dem': '/data/dem_filled.tif',
    'output': '/data/plan_curv.tif',
})

print("Terrain derivatives complete.")

Advanced: Geomorphons Landform Classification

Geomorphons classify each cell into one of ten landform elements (peak, ridge, shoulder, spur, slope, hollow, footslope, valley, pit, flat) by analysing horizon profiles in eight compass directions.

Processing Toolbox → Whitebox Workflows → Terrain Analysis → Geomorphons

The output is a categorical raster (1–10). Apply a predefined categorical colour map — the Geomorphons palette is available in many QGIS style repositories.

processing.run('whitebox_workflows:geomorphons', {
    'dem': '/data/dem_filled.tif',
    'search': 50,
    'skip': 0,
    'threshold': 1.0,
    'output': '/data/geomorphons.tif',
})

Common Pitfalls

Validation Checklist

• DEM uses a projected CRS (not geographic degrees).
• No unexpected flat artefacts introduced by depression filling.
• Slope range plausible for local relief (inspect histogram).
• Aspect –1 cells are spatially limited to genuine flats.
• Curvature raster has a near-symmetric distribution centred on 0.
• Hillshade visually matches known ridgelines and valley geometry.