FIRED (Fire Events Delineation): An Open, Flexible Algorithm and Database of US Fire Events Derived from the MODIS Burned Area Product (2001–2019)

Harnessing the fire data revolution, i.e., the abundance of information from satellites, government records, social media, and human health sources, now requires complex and challenging data integration approaches. Defining fire events is key to that effort. In order to understand the spatial and te...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Vol. 12; no. 21; p. 3498
Main Authors: Balch, Jennifer K., St. Denis, Lise A., Mahood, Adam L., Mietkiewicz, Nathan P., Williams, Travis M., McGlinchy, Joe, Cook, Maxwell C.
Format: Journal Article
Language:English
Published: Basel MDPI AG 24.10.2020
MDPI
Subjects:
Algorithms
area
burn severity
Conus
data harmonization
Data integration
Delineation
ENVIRONMENTAL SCIENCES
event-builder algorithm
fire regime
fire regimes
Forest & brush fires
human health
information
Integration
MODIS
Monitoring
open fire science
Pixels
Remote sensing
satellite fire detections
satellites
social networks
spatial data
Trends
Wildfires
United States > US
ISSN:2072-4292, 2072-4292
Online Access:Get full text
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Summary:Harnessing the fire data revolution, i.e., the abundance of information from satellites, government records, social media, and human health sources, now requires complex and challenging data integration approaches. Defining fire events is key to that effort. In order to understand the spatial and temporal characteristics of fire, or the classic fire regime concept, we need to critically define fire events from remote sensing data. Events, fundamentally a geographic concept with delineated spatial and temporal boundaries around a specific phenomenon that is homogenous in some property, are key to understanding fire regimes and more importantly how they are changing. Here, we describe Fire Events Delineation (FIRED), an event-delineation algorithm, that has been used to derive fire events (N = 51,871) from the MODIS MCD64 burned area product for the coterminous US (CONUS) from January 2001 to May 2019. The optimized spatial and temporal parameters to cluster burned area pixels into events were an 11-day window and a 5-pixel (2315 m) distance, when optimized against 13,741 wildfire perimeters in the CONUS from the Monitoring Trends in Burn Severity record. The linear relationship between the size of individual FIRED and Monitoring Trends in Burn Severity (MTBS) events for the CONUS was strong (R2 = 0.92 for all events). Importantly, this algorithm is open-source and flexible, allowing the end user to modify the spatio-temporal threshold or even the underlying algorithm approach as they see fit. We expect the optimized criteria to vary across regions, based on regional distributions of fire event size and rate of spread. We describe the derived metrics provided in a new national database and how they can be used to better understand US fire regimes. The open, flexible FIRED algorithm could be utilized to derive events in any satellite product. We hope that this open science effort will help catalyze a community-driven, data-integration effort (termed OneFire) to build a more complete picture of fire.
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NREL-JA-6A20-78462
AC36-08GO28308
National Aeronautics and Space Administration (NASA), Terrestrial Ecology Program
ISSN:2072-4292
2072-4292
DOI:10.3390/rs12213498