The Nightfire algorithm detects and characterizes sub-pixel hot sources using multispectral data collected globally, each night, by the Suomi National Polar Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS). The spectral bands utilized span visible, near-infrared (NIR), short-wave infrared (SWIR), and mid-wave infrared (MWIR). The primary detection band is in the SWIR, centered at 1.6 μm. Without solar input, the SWIR spectral band records sensor noise, punctuated by high radiant emissions associated with gas flares, biomass burning, volcanoes, and industrial sites such as steel mills. Planck curve fitting of the hot source radiances yields temperature (K) and emission scaling factor (ESF). Additional calculations are done to estimate source size (m 2), radiant heat intensity？(W/m 2), and radiant heat (MW). Use of the sensor noise limited M7, M8, and M10 spectral bands at night reduce scene background effects, which are widely reported for fire algorithms based on MWIR and long-wave infrared. High atmospheric transmissivity in the M10 spectral band reduces atmospheric effects on temperature and radiant heat retrievals. Nightfire retrieved temperature estimates for sub-pixel hot sources ranging from 600 to 6,000 K. An intercomparison study of biomass burning in Sumatra from June 2013 found Nightfire radiant heat (MW) to be highly correlated to Moderate Resolution Imaging Spectrometer (MODIS) Fire Radiative Power (MW).
References
[1]
Dozier, J. A method for satellite identification of surface temperature fields of sub-pixel resolution. Remote Sens. Environ 1981, 11, 221–229.
[2]
Giglio, L.; Kendall, J.D. Application of the Dozier retrieval to wildfire characterization—A sensitivity analysis. Remote Sens. Environ 2001, 77, 34–49.
[3]
Peterson, D.; Wang, J. A sub-pixel-based calculation of fire radiative power from MODIS observations: 2. Sensitivity analysis and potential fire weather application. Remote Sens. Environ 2013, 129, 231–249.
[4]
Peterson, D.; Wang, J.; Ichoku, C.; Hyer, E.; Ambrosia, V. A sub-pixel-based calculation of fire radiative power from MODIS observations: 1. Algorithm development and initial assessment. Remote Sens. Environ 2013, 129, 262–279.
[5]
Zhukov, B.; Lorenz, E.; Oertel, D.; Wooster, M.; Roberts, G. Spaceborne detection and characterization of fires during the bi-spectral infrared detection (BIRD) experimental small satellite mission (2001–2004). Remote Sens.Environ 2006, 100, 29–51.
[6]
Justice, C.; Giglio, L.; Boschetti, L.; Roy, D.; Csiszar, I.; Morisette, J.; Kaufman, Y. MODIS Fire Products: Algorithm Technical Background Document. 2.3.1 Version;; University of Maryland: College Park, MD, USA, 2006.
[7]
Giglio, L.; Csiszar, I.; Justice, C.O. Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. J. Geophys. Res 2006, 111, G02016.
[8]
Kaufman, Y.J.; Justice, C.O.; Flynn, L.P.; Kendall, J.D.; Prins, E.M.; Giglio, L.; Ward, D.E.; Menzel, W.P.; Setzer, A.W. Potential global fire monitoring from EOS-MODIS. J. Geophys. Res 1998, 103, 32215–32238.
[9]
Elvidge, C.D.; Ziskin, D.; Baugh, K.E.; Tuttle, B.T.; Ghosh, T.; Pack, D.W.; Erwin, E.H.; Zhizhin, M. A fifteen year record of global natural gas flaring derived from satellite data. Energies 2009, 2, 595–622.
[10]
Casadio, S.; Arino, O. ATSR-WFA New Algorithms for Hot Spot Detection. Proceedings of the 2nd MERIS/(A)ATSR User Workshop, European Space Agency SP-666, Frascati, Italy, 22–26 November 2008.
[11]
Casadio, S.; Arino, O.; Serpe, D. Gas flaring monitoring from space using the ATSR instrument series. Remote Sens. Environ 2012, 116, 239–249.
[12]
Cao, C.; DeLuccia, F.; Xiong, X.; Wolfe, R.; Weng, F. Early on-orbit performance of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. IEEE Trans. Geosci. Remote Sens. 2013, doi:10.1109/TGRS.2013.2247768.
Baker, N. Joint Polar Satellite System (JPSS) Operational Algorithm Description (OAD) Document for Cross-track Infrared and Advanced Technology Microwave Sounder Suite (CrIMSS) Environmental Data Record (EDR) Software. C Revision;; NASA-GSFC: Greenbelt, MD, USA, 2013.
[15]
Zhizhin, M.; Elvidge, C.D.; Hsu, F-C.; Baugh, K.E. Using the short-wave infrared for nocturnal detection of combustion sources in VIIRS data. Proc. Asia-Pacific Adv. Netw 2013, 35, 49–61.
[16]
Lagarias, J.C.; Reeds, J.A.; Wright, M.H.; Wright, P.E. Convergence properties of the Nelder-Mead simplex method in low dimensions. Siam J. Optim 1998, 9, 112–147.
[17]
Ichoku, C.; Kaufman, Y.J. A method to derive smoke emission rates from MODIS fire radiative energy measurements. IEEE Trans. Geosci. Remote Sens 2005, 43, 2636–2649.
[18]
Bussman, W.; Hong, J. Flare Radiation. In Industrial Combustion Testing; Charles, E.B., Jr., Ed.; CRC Press: Boca Raton, NY, USA, 2010; pp. 595–611.
[19]
Baker, N. Joint Polar Satellite System (JPSS) VIIRS Cloud Mask (VCM) Algorithm Theoretical Basis Document (ATBD). Revision B;; NASA-GSFC: Greenbelt, MD, USA, 2008.
[20]
Xenon Short Arc Lamps. Available online: http://www.sqpuv.com/PDFs/TechnicalSpecificationGuide.pdf (accessed on 9 July 2013).
