Infrared Burnt Area Detection Using Multi-Resolution Satellite Imagery
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Solution Overview
Problem
Current burnt area detection methods are limited by low spatial resolution and high costs, making semi-automatic high-resolution mapping economically infeasible on a global scale, and existing systems lack the ability to provide high temporal resolution and require human intervention.
Innovation Solution
A satellite-based method using infrared (IR) imagery with high temporal but low spatial resolution for hotspot detection, combined with high spatial resolution imagery for burnt area analysis, employing independent stages for hotspot and burnt area detection, and automated processing to determine burnt area measures, including the use of normalized burn ratio and morphological snakes algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If semi-automatic high resolution mapping is performed manually, then mapping precision is improved, but cost increases making it economically infeasible on a global scale
Solution Approach 1:
The burnt area detection process is segmented into multiple stages: initial detection using low-resolution imagery to identify candidate areas, followed by detailed analysis using high-resolution imagery only for those candidate areas. This segmentation allows automated processing at global scale while maintaining high precision where needed, eliminating the need for costly manual interpretation everywhere.
Solution Approach 2:
Low-resolution satellite imagery serves as an intermediary to pre-identify candidate burnt areas before applying high-resolution analysis. This intermediary step filters out non-burnt areas, allowing the system to achieve global coverage with high precision at reduced cost by applying detailed analysis only where necessary.
2Measurement precision
If high spatial resolution imagery is used for global burnt area detection, then mapping precision is improved, but processing time increases reducing productivity
Solution Approach 1:
The detection process segments the vast global area into candidate regions identified by low-resolution imagery, then applies computationally intensive high-resolution analysis only to these segmented candidate areas. This approach maintains high spatial resolution for accurate mapping while dramatically improving productivity by avoiding processing of entire global regions at high resolution.
Solution Approach 2:
Instead of applying full high-resolution analysis to all areas, the system performs partial action by limiting detailed high-resolution processing only to candidate burnt areas identified in the preliminary screening stage, thus achieving necessary precision without excessive processing time.
3Productivity
If low spatial resolution imagery is used for global coverage, then productivity is improved, but measurement precision deteriorates
Solution Approach 1:
The system uses low-resolution imagery for initial global screening to maintain productivity and coverage, then segments out candidate burnt areas for enhanced analysis with high-resolution imagery, thereby achieving both global coverage efficiency and local measurement precision.
Solution Approach 2:
The system applies different image qualities to different regions: low-resolution imagery for most of the global area to maintain productivity, and high-resolution imagery locally for candidate burnt areas to ensure measurement precision where it matters most.
4Measurement precision
If manual interpretation is used for burnt area detection, then measurement precision is improved, but extent of automation deteriorates
Solution Approach 1:
The system segments the detection process into automated preliminary screening using low-resolution imagery and automated detailed analysis using high-resolution imagery, eliminating the need for manual interpretation while maintaining precision through multi-stage automated processing.
Solution Approach 2:
Manual mechanical interpretation is replaced by automated computer-based image analysis systems that process both low and high-resolution imagery, substituting human operators with automated algorithms that maintain precision while achieving full automation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Achieves high temporal resolution (days to hours) and high spatial resolution (10 m) burnt area detection globally, fully automated and cost-effective, without human intervention, providing accurate burnt area maps and severity metrics.
Implementation Method 1
obtaining first infrared (IR) image data based on one or more first IR images of an earth surface... determining, as a hotspot area, an area on the earth surface with high thermal emission in the one or more first IR images
Data Source
AI summary
A method of burnt area detection includes obtaining first infrared (IR) image data based on first IR images of the earth surface; determining, as a hotspot area, an area on the earth surface with high thermal emission in the first IR images; obtaining second IR image data based on second IR images of an area of the earth surface that at least partially overlaps with the hotspot area, taken after the one or more first IR images; obtaining third IR image data based on third IR images of an area of the earth surface that at least partially overlaps with the hotspot area, taken before the one or more first IR images; and determining a measure of a burnt area relating to the hotspot area based on the second IR image data and the third IR image data. The application further relates to corresponding apparatus, programs, and computer-readable storage media.