Automatic forest-fire measuring using ground stations and Unmanned Aerial Systems

Area of Science:

• Forestry Science
• Remote Sensing
• Geospatial Analysis

Background:

• Accurate real-time forest fire measurement is crucial for effective management and response.
• Existing methods face challenges due to environmental factors and limited data acquisition.
• The need for integrated systems combining ground and aerial perspectives is evident.

Purpose of the Study:

• To develop and validate a novel, automated system for real-time forest fire geometrical measurements.
• To address inherent errors in fire measurement by leveraging complementary sensor data.
• To integrate data from multiple sources for enhanced measurement accuracy.

Main Methods:

• Utilized a network of ground-based infrared and visual cameras, supplemented by Unmanned Aerial Systems (UAS) cameras.
• Applied advanced image processing and geo-location techniques for individual camera-based measurements.
• Employed statistical data fusion to integrate data from all sensors for robust fire characterization.

Main Results:

• The system successfully obtained real-time geometrical measurements, including fire front location, shape, flame height, and rate of spread.
• Integration of data from diverse camera types significantly improved measurement accuracy and reliability.
• Validation in near-operational conditions in Portugal and Spain demonstrated system efficacy.

Conclusions:

• The proposed system offers a significant advancement in automated forest fire monitoring and measurement.
• The fusion of ground and aerial sensor data provides a comprehensive and accurate approach to fire characterization.
• This technology holds potential for improved wildfire management and safety.