Quantification of MODIS fire radiative power (FRP) measurement uncertainty for use in satellite-based active fire characterization and biomass burning estimation

Geophysical Research Letters

Volumn 41, Issue 6, 2014, Pages 1988-1994

  Freeborn, Patrick H ^a,c   Wooster, Martin J ^b   Roy, David P ^a   Cochrane, Mark A ^a  

^a SOUTH DAKOTA STATE UNIVERSITY   (United States)

^b KING'S COLLEGE LONDON   (United Kingdom)

^c NATURAL ENVIRONMENT RESEARCH COUNCIL   (United Kingdom)

Author keywords

active fire characterization; biomass burning; bow tie effect; FRP; MODIS; uncertainty

Indexed keywords

BIOMASS; ESTIMATION; FIRES; NORMAL DISTRIBUTION; PIXELS; RADIOMETERS; SATELLITE IMAGERY;

ACTIVE FIRES; BIOMASS-BURNING; BOWTIE EFFECTS; FRP; MODIS; UNCERTAINTY;

UNCERTAINTY ANALYSIS;

BIOGEOCHEMISTRY; BIOMASS BURNING; CARBON BUDGET; EMISSION INVENTORY; FIRE BEHAVIOR; FLUX MEASUREMENT; MODIS; NADIR; PIXEL; QUANTITATIVE ANALYSIS; RADIATIVE FORCING; SATELLITE IMAGERY; UNCERTAINTY ANALYSIS;

EID: 84896690259     PISSN: 00948276     EISSN: 19448007     Source Type: Journal    
DOI: 10.1002/2013GL059086     Document Type: Article

References (27)

1. Barnes, W. L., T. S. Pagano, and, V. V. Salomonson, (1998), Pre-launch performance of the moderate resolution imaging spectroradiometer (MODIS) on EOS AM-1, IEEE Trans. Geosci. Remote Sens., 36 (4), 1088-1100.
2. Bowman, D. M. J. S., et al. (2009), Fire in the Earth System, Science, 324, 481-484, doi: 10.1126/science.1163886.
3. Ellicott, E., E. Vermote, L. Giglio, and, G. Roberts, (2009), Estimating biomass consumed from fire using MODIS FRE, Geophys. Res. Lett., 36, L13401, doi: 10.1029/2009GL038581.
4. Freeborn, P. H., M. J. Wooster, and, G. Roberts, (2011), Addressing the spatiotemporal sampling design of MODIS to provide estimates of the fire radiative energy emitted from Africa, Remote Sens. Environ., 115 (2), 475-489, doi: 10.1016/j.rse.2010.09.017.
5. Giglio, L., (2013), MODIS Collection 5 Active Fire Product User's Guide, Version 2.5, 61 pp., Dep. of Geogr., Univ. of Maryland, College Park, Md.
6. Giglio, L., J. Descloitres, C. O. Justice, and, Y. Kaufman, (2003), An enhanced contextual fire detection algorithm for MODIS, Remote Sens. Environ., 87, 273-282.
7. Ichoku, C., and, Y. J. Kaufman, (2005), A method to derive smoke emission rates from MODIS fire radiative energy measurements, IEEE Trans. Geosci. Remote Sens., 43 (11), 2636-2649, doi: 10.1109/TGRS.2005.857328.
8. Ichoku, C., L. Giglio, M. J. Wooster, and, L. A. Remer, (2008), Global characterization of biomass-burning patterns using satellite measurements of fire radiative energy, Remote Sens. Environ., 112, 2950-2962.
9. Kaiser, J. W., et al. (2012), Biomass burning emissions estimated with a global fire assimilation system based on observations of fire radiative power, Biogeosciences, 9, 527-554, doi: 10.5194/bg-9-527-2012.
10. Kaufman, Y. J., L. A. Remer, R. D. Ottmar, D. E. Ward, R. R. Li, R. Kleidman, R. S. Fraser, L. P. Flynn, D. McDougal, and, G. Shelton, (1996), Relationship between remotely sensed fire intensity and rate of emission of smoke: SCAR-C Experiment, in Global Biomass Burning, edited by, J. Levine, pp. 685-696, MIT Press, Cambridge, Mass.
11. Kaufman, Y. J., C. O. Justice, L. P. Flynn, J. D. Kendall, E. M. Prins, L. Giglio, D. E. Ward, W. P. Menzel, and, A. W. Setzer, (1998), Potential global fire monitoring from EOS-MODIS, J. Geophys. Res., 103 (D24), 32,215-32,338.
12. Kumar, S. S., D. P. Roy, L. Boschetti, and, R. Kremens, (2011), Exploiting the power law distribution properties of satellite fire radiative power retrievals-a method to estimate fire radiative energy and biomass burned from sparse satellite observations, J. Geophys. Res., 116, D19303, doi: 10.1029/2011JD015676.
13. Liu, R. G., J. Y. Liu, and, S. Liang, (2006), Estimation of Systematic Errors in MODIS Thermal Infrared Bands, IEEE Geosci. Remote Sens. Lett., 3 (4), 541-545.
14. Mazzoni, D., J. A. Logan, D. Diner, R. Kahn, L. Tong, and, Q. Li, (2007), A data-mining approach to associating MISR smoke plume heights with MODIS fire measurements, Remote Sens. Environ., 107, 138-148, doi: 10.1016/j.rse.2006.08. 014.
15. Nishihama, M., R. Wolfe, D. Solomon, F. Patt, J. Blanchette, A. Fleig, and, E. Masuoka, (1997), MODIS level 1A Earth location: Algorithm theoretical basis document version 3.0, MODIS Science Data Support Team, NASA Goddard Space Flight Center, Greenbelt, Md.
16. Peterson, D., J. Wang, C. M. Ichoku, E. Hyer, and, V. Ambrosia, (2013), A sub-pixel-based calculation of fire radiative power from MODIS observations: 1 Algorithm development and initial assessment, Remote Sens. Environ., 129, 262-279, doi: 10.1016/j.rse.2012.10.036.
17. Roberts, G. J., and, M. J. Wooster, (2008), Fire detection and fire characterization over Africa using Meteosat SEVIRI, IEEE Trans. Geosci. Remote Sens., 46 (4), 1200-1218.
18. Schroeder, W., I. Csiszar, L. Giglio, and, C. C. Schmidt, (2010), On the use of fire radiative power, area, and temperature estimates to characterize biomass burning via moderate to coarse spatial resolution remote sensing data in the Brazilian Amazon, J. Geophys. Res., 115, D21121, doi: 10.1029/2009JD013769.
19. Seiler, W., and, P. J. Crutzen, (1980), Estimates of gross and net fluxes of carbon between the biosphere and the atmosphere form biomass burning, Clim. Change, 2, 207-247.
20. Smith, A. M. S., and, M. J. Wooster, (2005), Remote classification of head and backfire types from MODIS fire radiative power observations, Int. J. Wildland Fire, 14, 249-254.
21. Val Martin, M., J. A. Logan, R. A. Kahn, F.-Y. Leung, D. L. Nelson, and, D. J. Diner, (2010), Smoke injection heights from fires in North America: Analysis of 5 years of satellite observations, Atmos. Chem. Phys., 10, 1491-1510, doi: 10.5194/acp-10-1491-2010.
22. Vermote, E., E. Ellicott, O. Dubovik, T. Lapyonok, M. Chin, L. Giglio, and, G. J. Roberts, (2009), An approach to estimate global biomass burning emissions of organic and black carbon from MODIS fire radiative power, J. Geophys. Res., 114, D18205, doi: 10.1029/2008JD011188.
23. Wenny, B. N., X. Geng, and, X. Xiong, (2009), MODIS thermal emissive band detector bias, in Proceedings of SPIE on Sensors, Systems, and Next-Generation Satellites XIII, vol. 7474, edited by, R. Meynart, S. P. Neeck, and, H. Shimoda, pp. 74740V-1-10, SPIE, Bellingham, Wash., doi: 10.1117/12.830080.
24. Wolfe, R., M. Nishihama, A. Fleig, J. Kuyper, D. Roy, J. Storey, and, F. Patt, (2002), Achieving sub-pixel geolocation accuracy in support of MODIS land science, Remote Sens. Environ., 83, 31-49.
25. Wooster, M. J., and, Y.-H. Zhang, (2004), Boreal forest fires burn less intensely in Russia than in North America, Geophys. Res. Lett., 31, L20505, doi: 10.1029/2004GL020805.
26. Wooster, M. J., B. Zhukov, and, D. Oertel, (2003), Fire radiative energy for quantitative study of biomass burning: Derivation from the BIRD experimental satellite and comparison to MODIS fire products, Remote Sens. Environ., 86 (1), 83-107.
27. Xu, W., M. J. Wooster, G. Roberts, and, P. Freeborn, (2010), New GOES imager algorithms for cloud and active fire detection and fire radiative power assessment across North, South and Central America, Remote Sens. Environ., 114 (9), 1876-1895, doi: 10.1016/j.rse.2010.03.012.