Automated burned area identification in real-time during wildfire events using WorldView imagery for the insurance industry

Christina Geller

doi:10.1117/12.2324458

9 October 2018 Automated burned area identification in real-time during wildfire events using WorldView imagery for the insurance industry

Christina Geller

Author Affiliations +

Proceedings Volume 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX; 1079015 (2018) https://doi.org/10.1117/12.2324458
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

In 2017, wildfires and bushfires caused an estimated 14 billion USD in losses worldwide with the most severe events occurring in the state of California during October and December. The October outbreak in northern California alone cost USD 10.9 billion to the insurance industry, constituting the fourth largest loss event due to a natural catastrophe in 2017. While catastrophe modeling has begun to help bridge the knowledge gap about the risk of wildfire to life and property, understanding the extent of a wildfire in near real-time allows insurance companies around the world to quantify the loss of property their clients face during an event and proactively respond. To develop this real-time analysis of affected areas and the losses associated with the event, a methodology utilizing optical multi-spectral imagery from DigitalGlobe’s WorldView satellite suite is proposed for delineation of burned and unburned areas. This methodology involves utilizing either the Normalized Burn Ratio or the Normalized Difference Vegetation Index, depending upon which satellite imagery is available. Full-automation of the methodology allows for rapid identification of affected areas to occur around the world based on industry request. The methodology has been tested and proven effective for the October 2017 Tubbs, Atlas, Oakmont, and Nuns fires in California, USA.

Conference Presentation

Citation Download Citation

Christina Geller "Automated burned area identification in real-time during wildfire events using WorldView imagery for the insurance industry", Proc. SPIE 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX, 1079015 (9 October 2018); https://doi.org/10.1117/12.2324458

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