REAL-TIME WILDFIRE DETECTION FROM SPACE – A TRADE-OFF BETWEEN SENSOR QUALITY, PHYSICAL LIMITATIONS AND PAYLOAD SIZE

摘要

Wildfires cause large scale devastation to human settlements and forests every year and their frequency and severity is on the rise. A major reason for this devastation is the significant delay in their detection due to their remote locations in forests. To mitigate this, a constellation of nanosatellites in Low Earth Orbit (LEO) equipped with multi-spectral visible to Infrared (IR) cameras is proposed leveraging the modular and affordable architecture of CubeSats. Coupled with the payload design, meticulously planned constellation and a ground support system, all surface points on the planet will be revisited at least once in an hour. Capturing a surface location with a high resolution in MidWavelength Infrared (MWIR) and LongWavelength Infrared (LWIR) allows a precise estimation of thermal output of the surface. Simulations indicate that a fire of about four hundred square meters can be easily detected from this satellite payload. Through onboard data processing, wildfires can be already detected in space, minimizing bandwidth requirements for real-time alerts. This enables an early wildfire warning within 30 min by utilizing existing satellite internet networks. Additionally, compressed raw images will be transmitted on fixed ground station passes to provide a global thermal data updated every 90 min. The near real-time multi-spectral data provides opportunity for several other applications like weather forecasting besides wildfire detection.