The collection 6 MODIS active fire detection algorithm and fire products

By Louis Giglio, W. Schroeder, C. Justice. Remote Sensing of Environment, 2016

1,318 citations recorded by the source corpus.

The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments, on-board NASA’s Terra and Aqua satellites, have provided more than a decade of global fire data. Here we describe improvements made to the fire detection algorithm and swath-level product that were implemented as part of the Collection 6 land-product reprocessing, which commenced in May 2015. The updated algorithm is intended to address limitations observed with the previous Collection 5 fire product, notably the occurrence of false alarms caused by small forest clearings, and the omission of large fires obscured by thick smoke. Processing was also expanded to oceans and other large water bodies to facilitate monitoring of offshore gas flaring. Additionally, fire radiative power (FRP) is now retrieved using a radiance-based approach, generally decreasing FRP for all but the comparatively small fraction of high intensity fire pixels. We performed a Stage-3 validation of the Collection 5 and Collection 6 Terra MODIS fire products using reference fire maps derived from more than 2500 high-resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. Our results indicated targeted improvements in the performance of the Collection 6 active fire detection algorithm compared to Collection 5, with reduced omission errors over large fires, and reduced false alarm rates in tropical ecosystems. Overall, the MOD14 Collection 6 daytime global commission error was 1.2%, compared to 2.4% in Collection 5. Regionally, the probability of detection for Collection 6 exhibited a ~3% absolute increase in Boreal North America and Boreal Asia compared to Collection 5, a ~1% absolute increase in Equatorial Asia and Central Asia, a ~1% absolute decrease in South America above the Equator, and little or no change in the remaining regions considered. Not unexpectedly, the observed variability in the probability of detection was strongly driven by regional differences in fire size. Overall, there was a net improvement in Collection 6 algorithm performance globally.

Subfields: Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/9f9c0f5fa7076a9388db22e5a18f6c0d170d33d3

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In Global and Planetary Change

Citations in the corpus

A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing (2020, background): “[99] and the VIIRS 375 m (VNP14IMG) active fire product described in Schroeder et al.”
Quantifying the influence of agricultural fires in northwest India on urban air pollution in Delhi, India (2018, background): “The Collection 6 MODIS fire product accounts for thick smoke from fires by relaxing the thresholds that determine whether a pixel is cloud-obscured (Giglio et al 2016).”
The unintended impacts of agricultural fires: Human capital in China (2019, background): “The fires are detected based on thermal anomalies, surface reflectance, and land use (Giglio et al., 2016).”
NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms (2021, background): “FRP is a standard product for MODIS, VIIRS, Sentinel-3, and even geostationary satellites (Wooster et al., 2012; Wooster et al., 2015; Giglio et al., 2016).”