Geographic Information System (GIS) for air quality monitoring turns readings from monitoring stations, sensors, and satellites into maps that show where fine particulate matter (PM2.5) builds up across a city. For Indian cities, where pollution can differ sharply from one neighbourhood to the next, these maps help officials find the worst spots and decide where to act first.
Introduction: Why PM2.5 Is a Spatial Problem for Indian Cities
Most people know their city’s air quality as a single number, the Air Quality Index (AQI). But one number can hide large differences inside a city. In its analysis of winter 2024-25 (1 October to 31 January), the Centre for Science and Environment found that the most polluted locations in six large cities were 19 percent (Hyderabad) to 60 percent (Mumbai) more polluted than the city’s own average.
This gap matters because people breathe the air of their own street, not the city’s average. In 2025-26, 65 Indian cities met the national annual standard for PM2.5, according to a Rajya Sabha reply by the Ministry of Environment, Forest and Climate Change (MoEFCC). For the rest, the question is where pollution is worst and where action will help most.
What Is GIS for Air Quality Monitoring?
GIS for air quality monitoring means placing air quality data on a map and analyzing it by location. It brings together readings from monitoring stations, low-cost sensors, and satellites with layers such as roads, industries, construction sites, and ward boundaries.
The result is a picture of where pollution is high, how it changes through the day and season, and which areas are affected most. A monitoring station only measures the air around it. Spatial analysis can estimate pollution levels between monitoring stations, helping create a more complete picture of the city, and can then look for clusters of high pollution that are unlikely to be random. ArcGIS Pro supports this analysis, and city teams can then share the results through ArcGIS Dashboards for daily decisions.
India’s Clean Air Framework: NCAP, CPCB’s Monitoring Network, and CAQM’s GRAP
India’s air quality work rests on three pieces: a national program, a monitoring network, and an emergency response plan. The National Clean Air Programme (NCAP), launched in 2019, now covers 130 cities. According to a PIB note from September 2026, ₹16,423.55 crore was allocated to these cities between 2019-20 and 2025-26, and 70.5 percent of it was used. NCAP tracks progress against PM10 levels from 2017-18, and in 2025-26, 108 cities recorded lower PM10 than in that base year. The data behind this comes from a large monitoring network.
As of March 2026, India had 1,646 air quality monitoring stations across 603 cities in 28 states and 7 union territories. The SAMEER app shares near real-time AQI for more than 292 cities, and the PRANA portal tracks each city’s clean air action plan. The national standard sets a limit for PM2.5 of 40 µg/m³ as an annual average and 60 µg/m³ over 24 hours.
In Delhi and the National Capital Region (NCR), the Commission for Air Quality Management (CAQM) runs the Graded Response Action Plan (GRAP). Under the plan revised in November 2025, Stage I applies when Delhi’s AQI is 201 to 300, Stage II at 301 to 400, and Stage III at 401 to 450, with Stage IV beyond that. The November 2025 revision moved several measures to earlier stages, so action now starts at lower pollution levels than before.
From Station Readings to Hotspot Maps: How GIS Builds a City-Wide PM2.5 Picture
Starting with Station Data
The journey begins with PM2.5 readings from continuous monitoring stations, each tied to an exact location. Adding low-cost sensor data, where available, gives more points across the city, though these sensors need regular checks against reference stations.
Filling the Gaps Between Stations
Most cities have only a few stations, so large areas have no direct reading. In ArcGIS Pro, the ArcGIS Geostatistical Analyst extension can use empirical Bayesian kriging to estimate PM2.5 for every location from the nearby stations. It also produces a map of how confident each estimate is, which is important when stations are far apart.
Adding Satellite Data
Satellites can also provide information for areas where monitoring stations are not available. ISRO’s EOS-6 satellite provides an aerosol optical depth product at 1 km resolution that helps show how PM2.5 spreads and moves over cities. Layering this with station-based maps gives a fuller picture, especially at the edges of a city.
Finding Real Hotspots
A single high reading does not make a hotspot. The Hot Spot Analysis (Getis-Ord Gi*) tool in ArcGIS Pro checks whether high values cluster together more than chance would explain. A 2025 study in Environmental Research used this method on 1 km satellite-based PM2.5 data for 2008 to 2019, and found consistent hotspots covering 9.9 percent of India’s area, home to about 16 percent of its population. It also pointed to 170 cities beyond the current non-attainment list that may need attention.
Linking Hotspots to Causes
Once hotspots are mapped, analysts can overlay roads, industries, construction sites, waste dumps, and land use to see what lies inside each one. A hotspot near a busy junction needs a different response from one near open waste burning or a cluster of brick kilns.
Sharing the Results
The final map is only useful if the right people see it. ArcGIS Dashboards can show current PM2.5 levels, hotspot zones, and trends on one screen, so city officials and pollution control teams work from the same picture. City and state teams planning air quality programs can explore Smart Cities solutions from Esri India.
Inside Varanasi’s Kashi Environmental Monitoring System
Varanasi shows how air quality can become one layer of a city-wide GIS. According to an Esri India case study, Varanasi Smart City Ltd (VSCL) used ArcGIS to build an enterprise-wide integrated City GIS. Within it, the Kashi Environmental Monitoring System maps a real-time feed of air pollution across different parts of the city, and air quality sensors warn citizens of health-threatening conditions. The same platform holds other city services.
The Kashi Solid Waste Management System uses smart sensors on bins, and the Kashi Integrated Command and Control Centre (ICCC) manages traffic safety and city security. Because these systems share one set of base maps, air quality readings sit next to traffic, waste, and ward data, which helps officials see how one affects the other. Varanasi also publishes this data openly. VSCL built Kashi GeoHub on ArcGIS Hub, with layers covering ward boundaries, public services, and transportation. It connected these layers to sensor feeds for solid waste management, pollution, safety, and traffic control through application programming interfaces (APIs).
From Hotspot Map to Action: Dashboards, GRAP Stages, and Ward-Level Response
A hotspot map becomes useful when it leads to action. GRAP already links each AQI band to a set of response measures, which become stricter at higher stages. A dashboard can show which parts of a city have crossed each AQI band, so officials can see where measures apply and check if the AQI falls after they act. Live data can make this faster.
ArcGIS Velocity can read live sensor feeds and send an alert when PM2.5 in an area crosses a set limit. Teams can also start from a ready-made option: the Air Quality Index solution in Indo ArcGIS, developed by Esri India, brings sensor feeds and APIs from the Central Pollution Control Board (CPCB) and other sources into one dashboard. The ward can be a useful unit for action because municipal teams often organize local activities by ward. Swachh Vayu Sarvekshan 2026, the national clean air ranking of cities, looked at more than 7,400 wards across the country.
Mapping hotspots by ward lets municipal teams assign dust control, road sweeping, or waste burning checks to the wards that need them most. Field teams complete the picture. With ArcGIS Survey123, inspectors can log construction dust, open burning, or road dust complaints with photos and locations. These reports appear on the same map as sensor readings, so teams can check whether action in a ward is bringing PM2.5 down.
Challenges and the Road Ahead
Uneven Station Coverage
India has 1,646 monitoring stations across 603 cities, but they are not spread evenly, with more in large cities and fewer in smaller towns and on city outskirts. Interpolated maps become less certain where stations are far apart, so a gap in coverage can hide a real hotspot. The 2025 hotspot study, which pointed to 170 cities beyond the current non-attainment list, shows why monitoring needs to reach further, with satellite data helping to fill gaps in the meantime.
Checking Low-Cost Sensors
Low-cost sensors can add many more data points across a city, often at street and ward level. Their readings need regular checks against nearby reference stations before they can be used for decisions. Without these checks, one faulty sensor can create a false hotspot on the map or hide a real one.
Sharing Data Across Agencie
Air quality data is held by CPCB, state pollution control boards, and city bodies, often in different formats and at different update intervals. Bringing it onto one map needs common data standards, shared ward and city boundaries, and clear agreement on who updates what. Without this, each agency works from its own picture, and hotspot maps cannot be compared over time.
Pollution Beyond City Limits
Some PM2.5 comes from outside a city, from regional sources such as crop residue burning. During the 2025 season, satellites recorded 5,114 paddy residue burning events in Punjab and 662 in Haryana, tracked using a standard ISRO method. City maps work best when they connect with this kind of regional data, so local action is planned alongside wider efforts across the airshed.
FAQs
1.What is GIS for air quality monitoring?
GIS for air quality monitoring places readings from stations, sensors, and satellites on a map, and analyzes them by location. It shows where pollution is highest, how it changes over time, and which areas need action first.
2.How do Indian cities monitor PM2.5 levels?
Indian cities use a national network of 1,646 monitoring stations across 603 cities, as of March 2026. Near real-time AQI for more than 292 cities is available on the SAMEER app, and some cities add low-cost sensors and satellite data.
3.What is India’s national PM2.5 standard?
India’s national ambient air quality standard sets a PM2.5 limit of 40 µg/m³ as an annual average and 60 µg/m³ over 24 hours. Levels above these limits count as exceeding the standard.
4.How does ArcGIS Dashboards help cities track air quality?
ArcGIS Dashboards can show PM2.5 readings, hotspot zones, AQI bands, and field reports on one screen. This helps city officials see where pollution is rising and track whether actions in each ward are working.
5.How is satellite data used to map PM2.5 in India?
Satellites measure aerosol optical depth, which shows how much haze is in the air. ISRO’s EOS-6 satellite provides this at 1 km resolution, helping estimate PM2.5 in areas without monitoring stations.
Written by
Esri India Marketing
