报告主题：Remotely sensing fuel properties: current state and future development for operational fire danger and behavior predictionn
报告人：澳大利亚国立大学MARTA YEBRA 博士
Understanding and predicting fire danger and behaviour is a priority for fire and land management agencies. Fuel condition (e.g. fuel load, moisture content, and horizontal and vertical continuity) influences fire ignition and propagation. Estimating these fuel properties is, therefore, critical for assessing ﬁre danger and behaviour but they are difﬁcult to estimate, especially at regional to sub-continental scales. Remote sensing methods have
quickly evolved, providing new opportunities to obtain up to date, spatially comprehensive estimates of fuel condition. For example, over larger areas, satellite observations are used to map forest fuel load and moisture content, while airborne and terrestrial Light Detection and Ranging (LiDAR) data, as well as photogrammetric range imaging techniques, are used at regional or local scales to derive information on fuel arrangement in structurally complex forest. In this lecture, I review the latest remote sensing technologies relevant to estimating fuel condition, with a particular focus on operational fire danger and behaviour prediction. I conclude with some recommendations on developments that are needed to address limits to these approaches and to further increase the usability of remote sensing derived products in fire management。
Dr Marta Yebra is a Senior Scientist at the Centre for Water and Landscape Dynamics (Fenner School of Environment and Society), Program Director of the ANU Institute for Space and Associate editor for Remote Sensing of Environment. Her research focuses on using remote sensing data to monitor, quantify and forecast natural resources, natural hazards, and landscape function and health at local, regional and global scales.