FireGrid

Evidence-grade fire service planning | Method: Dr. Priya Singh, VNIT Nagpur (3 SCIE publications, PhD 2022)

Fire Service Assessment Snapshot: Noida, Uttar Pradesh

Prepared 14 July 2026 | Based on publicly available data

Executive summary

Noida, Uttar Pradesh operates 3 fire station(s) serving a population of 642,381 (Census 2011; edit for a current estimate) across 203.16 km². Assessed against India's national provisioning norms, the city's largest deficit appears under the SFAC standard: a shortfall of 17.3 stations (85% service gap). Under the research-derived unified benchmark (3 km = 7 min = 30 km² per station), the city requires 6.8 stations against 3 existing. Spatial coverage analysis shows only 25% of the city's area lies within effective road reach of a fire station at the 7-minute response benchmark (and 12% at the stricter 5-minute benchmark).

25%

area within effective reach (7-min / 3 km benchmark)

17.3

station shortfall (worst norm: SFAC)

existing fire stations

1. Benchmark gap assessment

Method: availability-index benchmark assessment per Singh, Sabnani & Kapse (2021), International Journal of Disaster Risk Reduction 63:102432. The unified benchmark reconciles the SFAC response-time norm (5-7 min) with the URDPFI distance norm (3-4 km) using 1,75,056 real travel-time measurements.

2. Spatial coverage

*Effective road coverage applies the measured network-to-Euclidean service-area ratio (~70%) established in the underlying research: actual road-network reach is systematically smaller than the straight-line buffers conventionally used in planning documents.

Schematic coverage map: red rings = straight-line 3 km reach; green = effective road reach; dashed outline = city boundary.

3. Station registry used

3 stations geocoded from public directories (NEA/Justdial/Mappls) at sector level (approximate). Newer stations (e.g., Sector-168) omitted pending verified coordinates.

4. Recommendations

Norm	Required	Existing	Shortfall	Service gap
URDPFI (1 station per 200,000 population)	3.2	3	0.2	7%
SFAC (1 station per 10 km²)	20.3	3	17.3	85%
Unified benchmark (1 station per 30 km²; 3 km = 7 min)	6.8	3	3.8	56%

Response benchmark	Straight-line coverage	Effective road coverage*
5 minutes (2 km)	16%	12%
7 minutes (3 km)	34%	25%

Station	Coordinates	Position status
Fire Station Sector-2 (HQ)	28.58508, 77.31526	approximate
Fire Station Phase-2 (Sector 83)	28.52446, 77.39797	approximate
Fire Station Phase-3	28.61207, 77.37781	approximate

1. Close the benchmark gap: plan for 3.8 additional station(s) to meet the unified benchmark.
2. Commission a full assessment (network isochrones on the real road graph, incident-log hotspot analysis, population-weighted coverage, optimal siting) to convert this snapshot into a DPR/NDRF-proposal-grade evidence pack.
3. Funding alignment: the MHA "Scheme for Expansion and Modernization of Fire Services in the States" (launched July 2023, ₹5,000 Cr earmarked under NDRF) requires exactly this class of evidence-backed gap justification.

Method & credentials

Singh P.P., Sabnani C.S., Kapse V.S. (2021). Interpreting benchmark assessment of emergency fire service using geoinformation technology. Int. J. Disaster Risk Reduction 63:102432.

Singh P.P., Sabnani C.S., Kapse V.S. (2021). Hotspot analysis of structure fires in urban agglomeration. Fire (MDPI) 4:38.

Singh P.P., Sabnani C.S., Kapse V.S. (2021). Urbanization and urban fire dynamics using GIS and remote sensing. Arabian Journal of Geosciences 14:2172.

Singh P. (2022). Fire Service in Urban Area: A Case Study of Nagpur City. PhD thesis, VNIT Nagpur.

Disclaimer: This snapshot uses publicly available data (OpenStreetMap, Census of India, public directories); station positions flagged "approximate" are placed at locality level. It is indicative, intended to scope a full assessment, and is not a statutory fire audit. This copy is a SAMPLE for demonstration.