| Resumo: |
The main territorial challenge is in the prevention, detection and mapping of natural disasters, especially, the wildland fires. In this project is being presented a sustainable and innovative technology to make picosatellite remote sensing and UAVs a great useful tool in forest fire strategic plans.
One of the biggest threats and environmental disasters that occur annually in the territories covered by SUDOE INTERREG are forest fires (more than 42.777 ha burned areas in Portugal in 2014, and a highpeak of 77.000 ha in Galicia in 2006). Generally, a good prevention and rapid actuation is cheaper and environmentally profitable than investing in extinction.
FIRE- RS Project (acronym for wildland FIRE Remote Sensing) seeks through the synergy of different technologies achieve a effective way of managing them by implementing a platform network that will integrate these innovative features:
#Low-Cost Infrared Land Sensors for wildland fire detection.
#Remote sensing of land sensors via picosatellite with a higher frequency than other systemalready implemented. Emergency UAVs to provide high-accuracy fire mapping and real time information like video.
#UAVs and Picosatellites will share the same radio communication system, the SDR (Software&#?;defined Radio) to maximize compatibility with land-sensors and costs.
# Data Treatment, data interpretation and decision making based upon the information gathered.
# Wildland Fire management software with the capacity to help plan, organize, and manage all the data and serve as a tool for emergency agencies.
This platform will provide centralized and up to date information, adapted to the emergency departments that require the maximum information, security and reliability of the this data,
especially in case of fire emergency.
To achieve this objective it is intended to use the know-how achieved by the partnership members:
# ; University of Vigo allocated in Vigo(Spain) in aerospace sector.
# University of Porto alloc  |
Resumo
The main territorial challenge is in the prevention, detection and mapping of natural disasters, especially, the wildland fires. In this project is being presented a sustainable and innovative technology to make picosatellite remote sensing and UAVs a great useful tool in forest fire strategic plans.
One of the biggest threats and environmental disasters that occur annually in the territories covered by SUDOE INTERREG are forest fires (more than 42.777 ha burned areas in Portugal in 2014, and a highpeak of 77.000 ha in Galicia in 2006). Generally, a good prevention and rapid actuation is cheaper and environmentally profitable than investing in extinction.
FIRE- RS Project (acronym for wildland FIRE Remote Sensing) seeks through the synergy of different technologies achieve a effective way of managing them by implementing a platform network that will integrate these innovative features:
#Low-Cost Infrared Land Sensors for wildland fire detection.
#Remote sensing of land sensors via picosatellite with a higher frequency than other systemalready implemented. Emergency UAVs to provide high-accuracy fire mapping and real time information like video.
#UAVs and Picosatellites will share the same radio communication system, the SDR (Software&#?;defined Radio) to maximize compatibility with land-sensors and costs.
# Data Treatment, data interpretation and decision making based upon the information gathered.
# Wildland Fire management software with the capacity to help plan, organize, and manage all the data and serve as a tool for emergency agencies.
This platform will provide centralized and up to date information, adapted to the emergency departments that require the maximum information, security and reliability of the this data,
especially in case of fire emergency.
To achieve this objective it is intended to use the know-how achieved by the partnership members:
# ; University of Vigo allocated in Vigo(Spain) in aerospace sector.
# University of Porto allocated in Porto(Portugal) for UAV development.
# LAAS-CNRS (Laboratoire d'analyse et d'architecture des systèmes) allocated in Toulouse(France) for data interpretation and decision making. |