A comprehensive land cover classification approach for the development of wildfire fuels layers

Christina Geller

doi:10.1117/12.2324459

9 October 2018 A comprehensive land cover classification approach for the development of wildfire fuels layers

Christina Geller

Proceedings Volume 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX; 107900J (2018) https://doi.org/10.1117/12.2324459
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

Land use and land cover (LULC) information is an important component for wildfire modeling as an understanding of the underlying vegetation conditions is needed to propagate fires accurately across the region. While government entities around the globe often create their own maps of available fuels, political boundaries within a country or across international borders can create inaccuracies and mismatched labeling that changes the speed, direction, and characteristics of the modeled fire. Government-generated fuels layers can also utilize different classification schemes with the United States relying on the 13 category Anderson Fire Behavior Fuel Model or the 46 category Scott Burgan Fire Behavior Fuel Model and Canada using a 19 category Fire Behavior Prediction System. To address these differences and provide a higher resolution understanding of conditions on the ground, a methodology based on the ISODATA Unsupervised Classification method was developed and applied to 30-meter Landsat 8 imagery. The methodology was utilized to create a fuels layer for Australia in 2016 and the western provinces of Canada in 2017 and will be used in future updates to wildfire models at AIR Worldwide.

Conference Presentation

Citation Download Citation

Christina Geller "A comprehensive land cover classification approach for the development of wildfire fuels layers", Proc. SPIE 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX, 107900J (9 October 2018); https://doi.org/10.1117/12.2324459

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