Products / Fire Predictions
The datasets use satellite data and machine learning models to predict the location and number of likely fire events (e.g., forest fires, wildfires, etc.) over the next seven days on a weekly rolling basis.
Predicted biomass fire hotspots for Brazil and neighbouring regions.
The fire predictions data offers several benefits:
- Early warning: Authorities can identify the potential for a fire event to occur early on, allowing them to take preventive measures and alert the communities at risk on time.
- Resource management: By tracking the progress of a fire event, authorities can more effectively deploy resources, such as firefighters and equipment, to areas where they are needed most.
- Damage minimization: By providing early warning and enabling effective resource management, the prediction data can help minimize a fire event's impact on the public and property and reduce the overall damage caused by the fire.
Parameters
Fire Count
An indication of where fires are likely to occur.
Features
Methodology
Fire hotspot prediction leverages machine learning to predict likely fire events. The model considers various factors, including historical fire data, weather conditions, vegetation characteristics, and land use.
Frequency
Weekly
Spatial resolution
25 kilometer
Coverage
Global
Data type
Vector
Availability
