The collection 6 MODIS active fire detection algorithm and fire products.
The collection 6 MODIS active fire detection algorithm and fire products.
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DOI：
10.1016/j.rse.2016.02.054
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发表时间：
2016-06-01
影响因子：
13.5
通讯作者：
Justice CO
中科院分区：
文献类型：
--
作者：
Giglio L;Schroeder W;Justice CO
NASA的Terra和Aqua卫星上的两个中分辨率成像光谱仪（MODIS）仪器提供了十多年的全球火灾数据。在这里，我们描述了对火灾探测算法和条带级产品所做的改进，这些改进是作为2015年5月开始的第六批陆地产品再处理的一部分实施的。更新后的算法旨在解决以前的集合5火灾产品所观察到的局限性，特别是小森林清除引起的误报，以及被浓烟掩盖的大型火灾的遗漏。处理范围也扩大到海洋和其他大型水体，以便利监测近海天然气燃烧。此外，火灾辐射功率（FRP），现在检索使用辐射为基础的方法，一般减少FRP的所有，但相对较小的分数高强度火像素。我们使用来自2500多幅高分辨率高级星载热发射和反射辐射计（ASTER）图像的参考火灾图对第5和第6集Terra MODIS火灾产品进行了第3阶段验证。我们的研究结果表明，与Collection 5相比，Collection 6主动火灾检测算法的性能有针对性地改进，在大型火灾中减少了遗漏错误，并降低了热带生态系统的误报率。总体而言，MOD 14 Collection 6日间全球佣金误差为1.2%，而Collection 5为2.4%。从区域来看，与集合5相比，集合6的检测概率在北美北部和亚洲北部绝对增加约3%，在赤道亚洲和中亚绝对增加约1%，在赤道以上的南美洲绝对减少约1%，在考虑的其余区域几乎没有变化。毫不意外的是，观测到的检测概率的变化是由火灾规模的区域差异强烈驱动的。总体而言，Collection 6算法性能在全球范围内实现了净改善。
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.
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DOI：
10.1109/tgrs.2006.875941
发表时间：
2006-07-01
影响因子：
8.2
作者：
Csiszar, Ivan A.;Morisette, Jeffrey T.;Giglio, Louis
通讯作者：
Giglio, Louis
影响因子：
4.9
作者：
Kaiser, J. W.;Heil, A.;van der Werf, G. R.
通讯作者：
van der Werf, G. R.
影响因子：
11.6
作者：
Chuvieco, Emilio;Giglio, Louis;Justice, Chris
通讯作者：
Justice, Chris
影响因子：
3.4
作者：
Bromley, Lars
通讯作者：
Bromley, Lars
影响因子：
5.2
作者：
Koren, Ilan;Remer, Lorraine A.;Longo, Karla
通讯作者：
Longo, Karla