Location: Water Management and Systems ResearchTitle: Country-level fire perimeter datasets (2001-2021)
|LINDROOTH, E - University Of Colorado|
|COOK, M - University Of Colorado|
|BALCH, J - University Of Colorado|
Submitted to: Scientific Data - Nature
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/19/2022
Publication Date: 7/30/2022
Citation: Mahood, A.L., Lindrooth, E.J., Cook, M.C., Balch, J.K. 2022. Country-level fire perimeter datasets (2001-2021). Scientific Data - Nature. 9. Article e458. https://doi.org/10.1038/s41597-022-01572-3.
Interpretive Summary: Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is a crucial topic for the coming century. But many countries do not have accessible fire history data. Here we present a collection of fire event datasets for every country on the globe that we created. We created the data using an open source algorithm, FIREDpy. This provides researchers and land managers anywhere on earth with fire history data that is accessible, easy to use, and easy to recreate. This will facilitate the expansion of fire science beyond the developed world.
Technical Abstract: Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is an important topic for the coming century. But many countries do not have accessible fire history data. There are several satellite-based products available as gridded data, but these can be difficult to access and use, and require significant computational resources and time to convert into a usable product for a specific area of interest. We developed an open source software package called FIREDpy (Fire Event Delineation for python) which automatically downloads and processes all of the source files for an area of interest from the MODIS burned area product, and runs a spatiotemporal flooding algorithm that converts those hundreds of grids into a single fire perimeter shapefile. Here we present a collection of fire event perimeter datasets for every country on the globe that we created using the FIREDpy software. We will continue to improve the efficiency and flexibility of the underlying algorithm, and intend to update these datasets annually.