Fusion of multi-platform Earth observation data for mapping of fire progression and post-fire vegetation recovery

The key innovation of this project is the development of robust methods for the integration of radar-based EO data into current and emerging systems for monitoring the impact of fire on vegetation. Rapid fire extent mapping, including fire progression of large wildfires, will be based on dense time-series of synthetic aperture radar (SAR), optical data and machine learning. The research will also explore the capabilities of SAR and LiDAR data, integrated with optical data, for distinguishing structural characteristics of post-fire recovery dynamics.

The overarching focus of the research is on the integration of multi-sensor EO data to fill key gaps in operational monitoring of the impacts of wildfire. The project aims to support land and fire managers to make more informed decisions, by developing more accurate and timely measures of burnt area extent and tools for monitoring post-fire recovery.


Project Leader:
Dr Michael (Hsing-Chung) Chang, Macquarie University