In order to detect wildfire in its earliest stage and give warnings so the casualty and financial losses caused by the fire could be minimized or even avoided, a team developed an Autonomous Wildfire Detection and Warning System has been put into use.
It is known that the system relies on remote sensing quantitative inversion, spatio-temporal big data and other technical means to implement the forest grassland fire danger class to mountain plots.
The team has built a set of forest grassland fire early warning and monitoring theory and method system based on satellite remote sensing big data and key information inversion of combustibles, and developed the only spatio-temporal product of combustibles moisture content covering the whole world, forest and grassland fire danger space-time products and forest and grassland fire Early Warning and Monitoring System realize large-scale, near real-time and high-precision forest and grassland fire risk early warning and monitoring.
In order to detect wildfire in its earliest stage and give warnings so the casualty and financial losses caused by the fire could be minimized or even avoided, a team developed an Autonomous Wildfire Detection and Warning System has been put into use.
