Landscape Ecology

, Volume 26, Issue 2, pp 211–224 | Cite as

Spatial and temporal heterogeneity of agricultural fires in the central United States in relation to land cover and land use

  • Mirela G. TulbureEmail author
  • Michael C. Wimberly
  • David P. Roy
  • Geoffrey M. Henebry
Research Article


Agricultural burning is an important land use practice in the central U.S. but has received little attention in the literature, whereas most of the focus has been on wildfires in forested areas. Given the effects that agricultural burning can have on biodiversity and emissions of greenhouse gasses, there is a need to quantify the spatial and temporal patterns of fire in agricultural landscapes of the central U.S. Three years (2006–2008) of the MODIS 1 km daily active fire product generated from the MODIS Terra and Aqua satellite data were used. The 2007 Cropland Data Layer developed by the U.S. Department of Agriculture was used to examine fire distribution by land cover/land use (LCLU) type. Global ordinary least square (OLS) models and local geographically weighted regression (GWR) analyses were used to explore spatial variability in relationships between fire detection density and LCLU classes. The monthly total number of fire detections peaked in April and the density of fire detections (number of fires/km2/3 years) was generally higher in areas dominated by agriculture than areas dominated by forest. Fire seasonality varied among areas dominated by different types of agriculture and land use. The effects of LCLU classes on fire detection density varied spatially, with grassland being the primary correlate of fire detection density in eastern Kansas; whereas wheat cropping was important in central Kansas, northeast North Dakota, and northwest Minnesota.


Agricultural burning Active fires Biodiversity Emissions Patterns of fire detections Cloud cover Local spatial analysis Fire detections 



This research was supported in part by a NASA EPSCoR project entitled Land cover dynamics, regional hydrometeorology, and the vulnerability of rain-fed agriculture to climate change under scenarios of extensive cultivation of biofuel feedstocks (NNX07AT61A) and by the US Department of Energy through the Sun Grant Initiative’s Regional Biomass Feedstock Partnership. We thank Dr. Luigi Boschetti for help with MODIS data processing. We thank two anonymous reviewers for helpful comments on an earlier draft.


  1. Anderson R (1990) The historic role of fire in the North American grassland. In: Collins SL, Wallace LL, American Institute of Biological Sciences, Ecological Society of America, Botanical Society of America (eds), Fire in North American tallgrass prairies, 1st edn. University of Oklahoma Press, Norman [Okla.], pp 8–18Google Scholar
  2. Archibald S, Roy DP, van Wilgen BW, Scholes RJ (2009) What limits fire? An examination of drivers of burnt area in Southern Africa. Glob Chang Biol 15(3):613–630CrossRefGoogle Scholar
  3. Bivand R, Yu D (2008) spgwr: geographically weighted regression. available from
  4. Bond WJ (2005) Large parts of the world are brown or black: a different view on the “Green World” hypothesis. J Veg Sci 16:261–266CrossRefGoogle Scholar
  5. Bond WJ, Keeley JE (2005) Fire as a global “herbivore”: the ecology and evolution of flammable ecosystems. Trends Ecol Evol 20:387–394CrossRefPubMedGoogle Scholar
  6. Bragg TB (1982) Seasonal variations in fuel and fuel consumption by fires in a bluestem prairie. Ecology 63:7–11CrossRefGoogle Scholar
  7. Bragg TB (1995) The physical environment of the Great Plains grasslands. In: Joern A, Keeler KH (eds) The changing prairie: North American grasslands. Oxford University, New York; Oxford, pp 49–81Google Scholar
  8. Brockett BH, Biggs HC, van Wilgen BW (2001) A patch mosaic burning system for conservation areas in southern African savannas. Int J Wildland Fire 10(2):169–183CrossRefGoogle Scholar
  9. Brunsdon C, Fotheringham S, Chariton M (1998) Geographically weighted regression-modeling spatial non-stationarity. The Statistician 47:431–443Google Scholar
  10. Chen Y, Tessier S, Cavers C, Xu X, Monero E (2005) A survey of crop residue burning practices in Manitoba. Appl Eng Agric 21(3):317–323Google Scholar
  11. Cook JG, Hershey TJ, Irwin LL (1994) Vegetative response to burning on Wyoming mountain-shrub big game ranges. J Range Manag 47(4):296–302CrossRefGoogle Scholar
  12. Csiszar I, Justice CO, McGuire AD, Roy DP, Brown F, Conard SG, Frost PGH, Giglio L, Elvidge C, Flannigan MD, Kasischke E, McRae DJ, Rupp TS, Stocks BJ, Verbyla DL (2004) Land use and fires. In: Gutman G (ed), Land change science: observing, monitoring and understanding trajectories of change on the Earth’s surface, vol 6. Kluwer Academic Publishers, Dordrecht; London, pp xix, 459 pGoogle Scholar
  13. Dickson BG, Prather JW, Xu Y, Hampton HM, Aumack EN, Sisk TD (2006) Mapping the probability of large fire occurrence in northern Arizona, USA. Landscape Ecol 21:747–761CrossRefGoogle Scholar
  14. Eva H, Lambin EF (1998) Remote sensing of biomass burning in tropical regions: sampling issues and multisensor approach. Remote Sens Environ 64(3):292–315CrossRefGoogle Scholar
  15. Fotheringham AS, Brunsdon C, Charlton M (2002) Geographicallyweighted regression: the analysis of spatially varying relationships. Wiley, Hoboken, NJGoogle Scholar
  16. Fuhlendorf SD, Engle DM (2004) Application of the fire-grazing interaction to restore a shifting mosaic on tallgrass prairie. J Appl Ecol 41(4):604–614CrossRefGoogle Scholar
  17. Fuhlendorf SD, Harrell WC, Engle DM, Hamilton RG, Davis CA, Leslie DM (2006) Should heterogeneity be the basis for conservation? Grassland bird response to fire and grazing. Ecol Appl 16(5):1706–1716CrossRefPubMedGoogle Scholar
  18. Giglio L (2005) MODIS collection 4 active fire product user’s guide version 2.2. 42 ppGoogle Scholar
  19. Giglio L (2007) Characterization of the tropical diurnal fire cycle using VIRS and MODIS observations. Remote Sen Environ 108(4):407–421CrossRefGoogle Scholar
  20. Giglio L, Descloitres J, Justice CO, Kaufman YJ (2003) An enhanced contextual fire detection algorithm for MODIS. Remote Sens Environ 87(2–3):273–282CrossRefGoogle Scholar
  21. Hawbaker TJ, Radeloff VC, Syphard AD, Zhu Z, Stewart SI (2008) Detection rates of the MODIS active fire product in the United States. Remote Sens Environ 112(5):2656–2664CrossRefGoogle Scholar
  22. Higgins KF (1986) Interpretation and compendium of historical fire accounts in the northern Great Plains [microform]. U.S. Dept. of the Interior, Fish and Wildlife Service, Washington, D.CGoogle Scholar
  23. Howe HF (1994) Response of early-flowering and late-flowering plants to fire season in experimental prairies. Ecol Appl 4(1):121–133CrossRefGoogle Scholar
  24. Johnson County Environmental Department Air Quality Program (2009) Available from Accessed 23 Feb 2009
  25. Justice CO, Giglio L, Korontzi S, Owens J, Morisette JT, Roy DP, Descloitres J, Alleaume S, Petitcolin F, Kaufman Y (2002) The MODIS fire products. Remote Sens Environ 83(1–2):244–262CrossRefGoogle Scholar
  26. Kaufman YJ, Justice CO, Flynn LP, Kendall JD, Prins EM, Giglio L, Ward DE, Menzel WP, Setzer AW (1998) Potential global fire monitoring from EOS-MODIS. J Geophys Res-Atmos 103(D24):32215–32238CrossRefGoogle Scholar
  27. Korontzi S, McCarty J, Loboda T, Kumar S, Justice C (2006) Global distribution of agricultural fires in croplands from 3 years of Moderate Resolution Imaging Spectroradiometer (MODIS) data. Global Biogeochem Cycles 20(2):15CrossRefGoogle Scholar
  28. Korontzi S, McCarty J, Justice C (2008) Monitoring agricultural burning in the mississippi River Valley Region from the moderate resolution imaging spectroradiometer (MODIS). J Air Waste Manag Assoc (1995) 58(9):1235–1239CrossRefGoogle Scholar
  29. Lal R (2004) Agricultural activities and the global carbon cycle. Nutr Cycl Agroecosyst 70(2):103–116CrossRefGoogle Scholar
  30. Leff B, Ramankutty N, Foley JA (2004) Geographic distribution of major crops across the world. Global Biogeochem Cycles 18(1):33CrossRefGoogle Scholar
  31. Lemieux PM, Lutes CC, Santoianni DA (2004) Emissions of organic air toxics from open burning: a comprehensive review. Prog Energy Combus Sci 30(1):1–32CrossRefGoogle Scholar
  32. McCarty JL, Justice CO, Korontzi S (2007) Agricultural burning in the Southeastern United States detected by MODIS. Remote Sens Environ 108(2):151–162CrossRefGoogle Scholar
  33. McCarty JL, Loboda T, Trigg S (2008) A hybrid remote sensing approach to quantifying crop residue burning in the United States. Appl Eng Agric 24(4):515–527Google Scholar
  34. McCool DK, Pannkuk CD, Kennedy AC, Fletcher PS (2008) Effects of burn/low-till on erosion and soil quality. Soil Tillage Res 101(1–2):2–9CrossRefGoogle Scholar
  35. Moghaddas EEY, Stephens SL (2007) Thinning, burning, and thin-burn fuel treatment effects on soil properties in a Sierra Nevada mixed-conifer forest. For Ecol Manag 250(3):156–166CrossRefGoogle Scholar
  36. Morisette JT, Giglio L, Csiszar I, Justice CO (2005a) Validation of the MODIS active fire product over Southern Africa with ASTER data. Int J Remote Sens 26(19):4239–4264CrossRefGoogle Scholar
  37. Morisette JT, Giglio L, Csiszar I, Morisette JT, Giglio L, Csiszar I, Setzer A, Schroeder W, Morton D, Justice CO (2005b) Validation of MODIS active fire detection products derived from two algorithms. Earth Interact 9:25CrossRefGoogle Scholar
  38. NRCS (2007) National Resources Inventory 2003 NRI, land use. U.S. Department of Agriculture, Natural Resources Conservation Service, USAGoogle Scholar
  39. Park RJ, Jacob DJ, Logan JA (2007) Fire and biofuel contributions to annual mean aerosol mass concentrations in the United States. Atmos Environ 41(35):7389–7400CrossRefGoogle Scholar
  40. Perlack RD, Wright LL, Turhollow AF, Graham RL (2005) Biomass as feedstocks for a bioenergy and bioproducts industry: the technical feasability of a billion-ton annual supply. U.S. Department of Energy. Report: DOE/GO-102005-2135. Oak Ridge, TNGoogle Scholar
  41. R Development Core Team (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
  42. Reid SB, Funk TH, Sullivan DC, Stiefer PS, Arkinson HL, Brown SG, Chinkin LR (2004) Research and development of emission inventories for planned burning activities for the Central State Regional Air Planning Association. In: 13th international emission inventory conference proceedings, Clearwater, Fla. 2004. Available from Accessed 15 July 2010
  43. Reinking DL (2005) Fire regimes and avian responses in the central tallgrass prairie. Stud Avian Biol 30:116–126Google Scholar
  44. Roy DP, Boschetti L, Justice CO, Ju J (2008) The collection 5 MODIS burned area product—global evaluation by comparison with the MODIS active fire product. Remote Sens Environ 112(9):3690–3707CrossRefGoogle Scholar
  45. Smith R, Adams M, Maier S, Craig R, Kristina A, Maling I (2007) Estimating the area of stubble burning from the number of active fires detected by satellite. Remote Sens Environ 109(1):95–106CrossRefGoogle Scholar
  46. Steinauer EM, Collins SL (1996) Prairie ecology—the tallgrass prairie. In: Samson FB, Knopf FL (eds) Prairie conservation: preserving North America’s most endangered ecosystem. Island Press, Washington, DC, pp 39–52Google Scholar
  47. Stern AJ, Doraiswamy PC, Cook PW (2001) Spring wheat classification in an AVHRR image by signature extension from a landsat TM classified image. Photogramm Eng Remote Sens 67(2):207–211Google Scholar
  48. Syphard AD, Radeloff VC, Keuler NS, Taylor RS, Hawbaker TJ, Stewart SI, Clayton MK (2008) Predicting spatial patterns of fire on a southern California landscape. Int J Wildland Fire 17:602–613CrossRefGoogle Scholar
  49. USDA/JAWF (1994) Major world crop area and climatic profiles. Agricultural Handbook No. 664Google Scholar
  50. USDA-NASS (2005). USDA-NASS published estimates database. Available from Accessed 1 July 2009
  51. Wilgers DJ, Horne EA (2006) Effects of different burn regimes on tallgrass prairie herpetofaunal species diversity and community composition in the Flint Hills, Kansas. J Herpetol 40(1):73–84CrossRefGoogle Scholar
  52. Wolfe RE, Roy DP, Vermote E (1998) MODIS land data storage, gridding, and compositing methodology: level 2 grid. IEEE Trans Geosci Remote Sens 36(4):1324–1338CrossRefGoogle Scholar
  53. Yang J, He HS, Shifley SR, Gustafson EJ (2007) Spatial patterns of modern period human-caused fire occurrence in the Missouri Ozark Highlands. For Sci 53:1–15Google Scholar
  54. Yevich R, Logan JA (2003) An assessment of biofuel use and burning of agricultural waste in the developing world. Global Biogeochem Cycles 17(4):42CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Mirela G. Tulbure
    • 1
    Email author
  • Michael C. Wimberly
    • 1
  • David P. Roy
    • 1
  • Geoffrey M. Henebry
    • 1
  1. 1.Geographic Information Science Center of ExcellenceSouth Dakota State UniversityBrookingsUSA

Personalised recommendations