Ambee’s air quality map give you visual representation of hyperlocal air quality data with the highest granularity, to understand pollution behavior.
Air Quality Map by Ambee are designed keeping in mind easy accessibility to environmental and climate intelligence. The proprietary algorithms, along with science-backed techniques, help make the maps accurate, easy to load and integrate with your solution too.
Air quality data to help understand the ambient environment
Pollen data to help your customers avoid seasonal allergies
Make informed decisions on agricultural and land with soil data
Weather data to optimize efficiency and second-order effects
Track forest fire data in real-time to avoid and reduce risks
Alerts on extreme weather events to take precautions and prepare for weather-related disasters
Curate plans to reclaim your land vegetation with NDVI data
Keep track of natural disasters in real time to reduce their risks on lives, properties, and environment.
Understand the level of emissions with CO2 data. Coming soon!
Instantly visualize the criteria pollutant levels with air quality map
Plan your operations according to the air quality forecast
Show your customers pattern of air quality with air quality map
Implement high-efficiency tasks with air quality map
Ambee’s extensive historical air quality data sets can help you gain crucial insights on environmental triggers from the past and plan ahead for the future.
An air quality map or an AQI map is a graphical representation of the current and forecasted air quality conditions in a specific area. It is typically based on measurements of pollutants in the air, such as particulate matter, ozone, and nitrogen dioxide.
Air quality is typically measured using air pollution monitors, which measure the concentration of various pollutants in the air. These monitors can be stationary, located at fixed locations, portable, carried by individuals, or mounted on vehicles. At Ambee, we use a multimodal system that combines open-source data, proprietary on-ground sensors, and satellite data. This combined data is then run through proprietary AI algorithms to generate AQI in current location and AQI index map.
Air quality maps are typically updated in real-time or near real-time, using data from air pollution monitors. Some maps may be updated hourly, while others may be updated less frequently.
The colors on an air quality map usually correspond to different levels of air quality, with green representing good air quality and red representing poor air quality. The specific range of colors and the corresponding air quality levels can vary depending on the map.
An air quality map can be a useful tool for understanding your current location AQI and for planning activities accordingly. For example, if the air quality is poor, you may want to limit your time outdoors or avoid strenuous activities.