Rapid Burned Area Mapping (R-BAM) Algorithm Released to Wildfire Agencies
Mar 12, 2019
Hatfield is pleased to release its Rapid Burned Area Mapping (R-BAM) algorithm to provincial and territorial government wildfire agencies to support wildfire response and assessment. This release includes:
- R-BAM machine learning algorithm for wildfire burned area and perimeter delineation – under a free institutional license
- R-BAM webinar demonstrating how to use the R-BAM algorithm – tentatively scheduled 17 April at 10:00 PST
- R-BAM service for one selected fire in 2019 – an opportunity for wildfire agencies to evaluate Hatfield’s fully integrated R-BAM service for situations where agencies want or need external support to generate wildfire burned area, perimeters, and burn severity
The R-BAM algorithm uses the point location and date of a detected fire (e.g., hotspot detection from MODIS/VIIRS) and automatically downloads and processes multi-spectral Sentinel-2 satellite images. Image processing, machine learning, and geoprocessing are used to provide maps and geospatial data of the burned area, fire perimeter, and active fire. The R-BAM algorithm is written in Python and deployed in a docker container.
An overview of R-BAM products and services is provided on Hatfield’s website. R-BAM development was supported by the Canadian Space Agency from 2016-2018 with R-BAM services used by the BC Wildfire Service during the record 2017 and 2018 wildfire seasons. Our mission with R-BAM is to build collaborative partnerships to deliver innovation.
For more information, please contact:
Established in 1974 and based in Vancouver, Canada, Hatfield Consultants has built a worldwide reputation in environmental services with over 4,000 successful projects in Asia, Africa, Europe, and the Americas. We have established offices in Canada (British Columbia and Alberta), Indonesia, Laos, and Botswana and business partners in Chile and Thailand.
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