Workflow Narrative

Service Area Planning and Coverage Optimization

Problem It Solves

Which facilities and scenarios provide the strongest service coverage, and where do unmet demand gaps remain?

Who It Is For

Accessibility planners, emergency coverage teams, and utility service design analysts.

Primary User

Municipal/public safety GIS teams, utilities, and logistics planners managing service-area targets.

What It Does

Builds network-based multi-ring service-area polygons from facility points over a line network.
Flags uncovered demand points outside baseline service coverage.
Produces scenario summary and candidate ranking CSV outputs for open/close planning workflows.

How It Works

Validates network/facility geometry types and parses ring costs.
Runs network service-area generation using the OSS network engine with polygon outputs.
Computes demand coverage and uncovered demand diagnostics against generated polygons.
Optionally evaluates scenario CSV variants (`scenario_id,facility_id,is_open[,capacity]`) and exports comparative KPI rows.
Indicative KPI formula: `coverage_pct = 100 * covered_demand / total_demand`.

Why It Wins

Replaces disconnected manual GIS steps with a reproducible network-derived coverage workflow and explicit planning artifacts.

Typical Buying Trigger

Teams need auditable facility coverage plans with scenario comparison outputs for governance or budget review.

Typical Presets

baseline-only: generate default service areas + uncovered demand.
scenario-planning: include open/close scenario CSV for option analysis.
candidate-screening: rank facilities by demand coverage proxy for expansion planning.

Inputs

Parameter	Optional	Description
network	no	Input line network layer (roads, trails, utility lines).
facilities	no	Input facility point layer used as service origins.
demand_points	yes	Optional demand point layer used for covered/uncovered diagnostics and KPI generation.
ring_costs	no	Numeric array of travel-cost ring thresholds (e.g., `[5, 10, 15]`).
scenarios	yes	Optional CSV with `scenario_id,facility_id,is_open[,capacity]` for open/close scenario runs.
service_areas	no	Output vector path for service-area polygons.
uncovered_demand	no	Output vector path for uncovered demand points.
scenario_summary_csv	no	Output CSV path for scenario KPIs.
ranked_candidates_csv	no	Output CSV path for candidate ranking metrics.

Outputs

Parameter	Type	Description
service_areas	GeoJSON/GeoPackage/Shapefile	Baseline network-derived multi-ring service-area polygons.
uncovered_demand	GeoJSON/GeoPackage/Shapefile	Demand points outside baseline service-area coverage.
scenario_summary_csv	CSV	Scenario-level KPI table (`scenario_id,total_demand_covered_pct,avg_accessibility,outlier_count`).
ranked_candidates_csv	CSV	Candidate ranking table (`candidate_id,coverage_gain_pct,avg_distance_improvement,rank`).

Python Example

import whitebox_workflows as wbw

wbe = wbw.WbEnvironment(include_pro=True, tier="pro")

result = wbe.service_area_planning_and_coverage_optimization(
    network="data/street_network.shp",
    facilities="data/facilities.shp",
    demand_points="data/demand_points.shp",
    ring_costs=[5.0, 10.0, 15.0],
    scenarios="data/service_scenarios.csv",
    service_areas="output/service_areas.geojson",
    uncovered_demand="output/uncovered_demand.geojson",
    scenario_summary_csv="output/scenario_summary.csv",
    ranked_candidates_csv="output/ranked_candidates.csv",
)

print(result)

License Notice

Use of this function requires a license for Whitebox Workflows Professional (WbW-Pro). Please visit www.whiteboxgeo.com to purchase a license.

Project Links

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