Model response reach using time, speed, and networks. Estimate coverage, gaps, and station counts. Make better placement decisions across growing service districts.
| Scenario | Response time (min) | Speed (km/h) | Travel factor | Area (km²) | Stations | Goal (%) | Estimated radius (km) | Stations needed |
|---|---|---|---|---|---|---|---|---|
| Urban core | 6 | 35 | 0.70 | 75 | 4 | 90 | ~2.27 | ~5 |
| Suburban mix | 8 | 45 | 0.80 | 180 | 5 | 90 | ~4.80 | ~5 |
| Rural district | 12 | 60 | 0.85 | 650 | 4 | 85 | ~10.20 | ~6 |
Response targets translate policy into measurable reach. A shorter target limits radius but improves equity and reduces severity. Use separate targets for structural fires, medical calls, and special hazards when local standards differ. The calculator treats one target as a planning baseline and lets turnout and buffer refine it. Document your “response time” definition so stakeholders compare consistently.
Average speed should reflect emergency driving under typical conditions, not peak performance. Congestion, signals, gates, bridges, and grades reduce effective movement. The travel factor compresses the theoretical radius to represent routing inefficiency and delay. Calibrate it using recent run data or a small GIS travel‑time sample. If you track 90th percentile travel times, set the factor so estimates align with that reliability level.
Overlapping service areas are not wasted; they support simultaneous incidents, apparatus downtime, and resilience during closures. However, overlap reduces unique area covered per station. The overlap input estimates that tradeoff so a growth plan can balance redundancy with expansion. Higher overlap suits dense, high‑risk zones. Pair overlap with minimum staffing rules to ensure coverage persists when one crew is already committed.
Real districts are not circles. Coastlines, rivers, industrial belts, and jurisdiction boundaries distort coverage. The geometry adjustment scales the circular area to reflect these constraints. Values below one model fragmented shapes; values near one represent compact regions. Use a conservative value when expansion corridors create long edges. When annexations occur, revisit the adjustment because boundaries can shift gaps.
Station counts are only one decision layer. Staffing levels, apparatus mix, and call demand shape true performance. Combine the station estimate with demand forecasting, risk mapping, and mutual‑aid agreements. Use the additional stations output to stage phased projects, then test candidate sites with detailed network analysis. Track response compliance quarterly and update inputs so capital plans stay tied to measured outcomes and growth.
Service radius is the estimated reach within the available travel time, adjusted by the travel factor. It is a planning approximation, not a guaranteed boundary for every street and condition.
Turnout and buffer reduce the time available for driving. Including them helps align the travel segment with dispatch realities, shift change effects, and operational delays that reduce on-road minutes.
Start with 0.70 to 0.85, then calibrate using recent incident travel times. Lower values fit congested grids or barriers. Higher values fit strong road connectivity and consistent emergency routing.
Overlap estimates shared coverage between stations. It is beneficial when reliability matters, such as high demand, simultaneous incidents, or apparatus downtime. It reduces unique coverage but improves redundancy.
Yes, but use realistic speeds and conservative factors. Rural roads, terrain, and long distances can create large gaps. Validate outputs with mapped travel times before committing to a site plan.
No. Staffing, unit availability, risk, and call distribution also drive placement. Use the estimate as a starting point, then complete GIS network modeling, risk scoring, and operational reviews.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.