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

Capability Note (Open Tier)

Whitebox open tier provides advanced network tools directly in the QGIS plugin, including shortest path, k-shortest alternatives, service areas, OD matrices, closest facility, location-allocation, and multimodal OD/routes. Advanced impedance controls include one-way directionality, turn/u-turn penalties, optional node-entry costs, and optional temporal cost profiles.

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 Whitebox network-analysis tools in the Processing Toolbox.

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

Intersection Delay / Node Cost Modeling

For Whitebox network tools that support advanced impedance (for example service-area and closest-facility workflows), you can include node-entry costs to model intersection delay:

• node_cost_points: point layer of intersection/gate delay observations.
• node_cost_field: numeric field in node_cost_points with non-negative delay/cost values.
• node_cost_snap_distance: optional max assignment distance from each node-cost point to a network node.

Practical pattern:

1. Build/snap a clean network first.
2. Prepare an intersection delay points layer (signals, crossings, gates).
3. Run network tools with both edge impedance and node-cost parameters.

When node-cost parameters are omitted, routing uses edge impedance only.

Step 3 - Shortest Path and K-Shortest Alternatives

Processing Toolbox -> Whitebox Workflows -> Network Analysis:

• Shortest Path Network
• K Shortest Paths Network

Recommended parameters:

Use k-shortest outputs when teaching resilience, alternate routing, or choice-model concepts.

Step 4 - Service Area (Isochrone)

Processing Toolbox -> Whitebox Workflows -> Network Analysis -> Network Service Area

Recommended parameters:

Advanced options (recommended for realistic urban travel times):

• node_cost_points, node_cost_field, node_cost_snap_distance
• turn_penalty, u_turn_penalty, forbid_u_turns
• temporal_cost_profile, departure_time, temporal_mode

Step 5 - Closest Facility and OD Matrices

Processing Toolbox -> Whitebox Workflows -> Network Analysis:

• Closest Facility Network
• Network OD Cost Matrix
• Network Routes From OD

Use these for assignment, accessibility summaries, and route materialization. OD matrix output is ideal for downstream tabular analysis (Python/R/pandas).

Workflow C: Location-Allocation and Accessibility

Processing Toolbox -> Whitebox Workflows -> Network Analysis:

• Location Allocation Network
• Compute Network Accessibility

Recommended location-allocation pattern:

1. Prepare candidate sites and weighted demand points.
2. Select solver mode (minimize_impedance, maximize_coverage, or maximize_attendance).
3. Compare static-cost and peak-period temporal-profile runs.

Recommended accessibility pattern:

1. Provide origins and destination opportunities.
2. Set impedance cutoff and decay function.
3. Map/compare resulting accessibility scores across scenarios.

Workflow D: Multimodal Network Analysis

Processing Toolbox -> Whitebox Workflows -> Network Analysis:

• Multimodal Shortest Path
• Multimodal OD Cost Matrix
• Multimodal Routes From OD

Requirements:

• mode field on network edges (e.g., walk/bus/rail)
• allowed-modes and transfer-penalty configuration
• optional temporal profile for schedule/peak scenarios

Workflow E: 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',
})

# Whitebox network service area
processing.run('whitebox_workflows:network_service_area', {
  'input': '/data/roads_prepared.shp',
  'origins': '/data/facilities.shp',
  'max_cost': 5.0,
  'output_mode': 'polygon',
  'edge_cost_field': 'TIME_MIN',
  'one_way_field': 'ONEWAY',
  'turn_penalty': 0.4,
  'u_turn_penalty': 2.5,
  'output': '/data/service_area_5min.shp',
})

# Whitebox OD matrix
processing.run('whitebox_workflows:network_od_cost_matrix', {
  'input': '/data/roads_prepared.shp',
  'origins': '/data/origins.shp',
  'destinations': '/data/destinations.shp',
  'edge_cost_field': 'TIME_MIN',
  'one_way_field': 'ONEWAY',
  'output': '/data/od_costs.csv',
})

# 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.