Network Analysis

Network analysis in WbW-QGIS spans both transportation and hydrologic networks. This chapter is aligned with the Python and R manuals and now covers three common tracks:

• Transportation routing and service areas
• OD and nearest-facility analysis
• Stream-network hierarchy and connectivity

Core Concepts You Should Know First

• Network: A graph of edges (line segments) and nodes (junctions/endpoints).
• Cost or impedance: Value minimized by routing (distance, minutes, or other weighted friction).
• OD pair: Origin and destination used in path queries.
• Service area: All network locations reachable under a cost budget.
• Closest facility: Nearest destination by network cost, not straight-line distance.
• Connectivity: Whether all required features are in connected components.
• Directed network: Edge direction matters (one-way roads, downstream streams).

Typical Inputs

Workflow A: Transportation Network Preparation

Step 1 - Topology QA and Geometry Cleanup

Use standard QGIS cleanup first:

• Check validity
• Snap Geometries to Layer
• Fix Geometries

Then enrich network attributes with Whitebox tools:

Processing Toolbox -> Whitebox Workflows -> Vector Analysis -> Add Geometry Attributes

This provides segment length fields needed for distance-based routing.

If travel-time routing is required, compute a time field such as:

• TIME_MIN = LENGTH_M / SPEED_M_PER_MIN

using Field Calculator.

Step 2 - Build Cost-Aware Road Layer

Recommended fields:

• LENGTH_M (meters)
• SPEED_KMH (if available)
• TIME_MIN (derived)
• ONEWAY (optional directional control)

Use this prepared layer as the routing network for native QGIS algorithms.

Step 2.5 - Build Network Topology and Snap Points (Optional)

If your network lacks proper node structure or you need to snap facility/demand points to the network:

Processing Toolbox → Whitebox Workflows → Vector Analysis → Build Network Topology

Then snap your facilities and demand points:

Processing Toolbox → Whitebox Workflows → Vector Analysis → Snap Points to Network

Output includes SNAP_DIST (offset to network) for diagnostics.

Workflow B: Routing, Service Areas, and Closest Facility

Step 3 - Shortest Path

Processing Toolbox -> Network Analysis:

• Shortest Path (Point to Point)
• Shortest Path (Layer to Point)
• Shortest Path (Point to Layer)

Use the prepared cost field (distance or time) consistently.

Step 4 - Service Area (Isochrone)

Processing Toolbox -> Network Analysis -> Service Area (From Layer)

Recommended parameters:

Export output lines and optional polygons for reporting.

Step 5 - Closest Facility Pattern

Use Service Area and shortest-path tools together:

• Build candidate facilities
• Route demand points to nearest reachable facilities
• Summarize cost by facility catchment

For large batches, run model-builder or Python Console loops.

Workflow C: OD-Style Batch Analysis in QGIS

QGIS does not provide a single OD matrix tool equivalent to the Python/R chapters, so the standard QGIS pattern is:

• Iterate origins and destinations in batch
• Run shortest path for each pair
• Aggregate travel cost in an output table

Use this when you need accessibility summaries or assignment baselines directly inside QGIS projects.

Workflow D: Hydrologic Stream Networks

Hydrologic network tools remain an important part of network analysis and are included here as a dedicated sub-workflow rather than the entire chapter.

Step 6 - Stream Hierarchy

Processing Toolbox -> Whitebox Workflows -> Spatial Hydrology:

• Strahler Stream Order
• Shreve Stream Magnitude
• Hack Stream Order

These tools characterize stream position and downstream accumulation.

Step 7 - Stream Vectorization

Processing Toolbox -> Whitebox Workflows -> Spatial Hydrology -> Raster Streams to Vector

Convert ordered stream rasters to vector lines for cartography and further network operations.

QGIS Python Console Equivalent

import processing

# Add geometry attributes for road cost preparation
processing.run('whitebox_workflows:add_geometry_attributes', {
    'input': '/data/roads.shp',
    'output': '/data/roads_prepared.shp',
})

# Service area from facilities
processing.run('native:serviceareafromlayer', {
    'INPUT': '/data/roads_prepared.shp',
    'STRATEGY': 0,
    'START_POINTS': '/data/facilities.shp',
    'TRAVEL_COST': 5.0,
    'OUTPUT_LINES': '/data/service_area_lines.shp',
    'OUTPUT': 'TEMPORARY_OUTPUT',
})

# Stream order
processing.run('whitebox_workflows:strahler_stream_order', {
    'd8_pntr': '/data/d8_pointer.tif',
    'streams': '/data/streams.tif',
    'output': '/data/strahler.tif',
})

Common Pitfalls

Validation Checklist

• Routing network passes geometry validity and snapping checks.
• Cost field units are consistent across all analyses.
• Directionality assumptions are documented (directed vs undirected).
• Service-area outputs were spot-checked against known travel behavior.
• Stream-order outputs were checked at confluences.
• Workflow parameters were saved in model or processing history.