Publications

Giglio, L; Schroeder, W; Justice, CO (2016). The collection 6 MODIS active fire detection algorithm and fire products. REMOTE SENSING OF ENVIRONMENT, 178, 31-41.

Abstract
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 similar to 3% absolute increase in Boreal North America and Boreal Asia compared to Collection 5, a similar to 1% absolute increase in Equatorial Asia and Central Asia, a similar to 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. (C) 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

DOI:
10.1016/j.rse.2016.02.054

ISSN:
0034-4257