DRYADS ecosystem uses a quad fire ignition monitoring system to minimize detection time and re-utilise the Pre-event DRYADS facility. This system consists of: • SENSOR NETWORK: High temperatures and CO detection can be fire ignition indicators • SURVEILLENCE DRONES in high danger index locations • CAMERAS /IR CAMERAS NETWORK: Cameras located in fixed and appropriate places will monitor and detect fires in real time by using a Computer Vision Framework based on Cutting-Edge Deep Learning Technologies. • LIDAR SCANNERS FOR SMOKE DETECTION: LIDAR is also a promising tool for forest-fire monitoring because, due to its very high sensitivity and spatial resolution, this active detection technique enables efficient location of small smoke plumes that originate from forest fires in the early stages of development during both day and night over a considerable range (tens of kilometres). By using suitable rastering methods, very accurate location of the smoke source is also possible. Another important characteristic of a LIDAR surveillance system is the promptness of the fire alarm. CREATION OF A PRE-FIRE STATUS MODEL OF ANY FOREST FOR ACCURATE POST-FIRE RESTORATION: Wildfires are a recurrent disturbance in the Mediterranean and Europe. However, administrators from this region are confronted with a lack of information on the effects of fire on most woody species, which is required for defining sustainable forest management strategies. DRYADS as a holistic fire management systems will utilise pre-fire data stemming from a variety of data sources as explain above in order to improve First Order Fire Effects Model (FOFEM) softwares, and compared their performance to locally-parameterised models based on five different forms. DRYADS will enhance current Post-fire tree mortality models for assisting forest land managers to predict fire effects, estimate delayed mortality and develop management prescriptions.
Project leader: Jochen Haenisch
Institution: JOTNE EPM TECHNOLOGY AS