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International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Fire spread from MODIS burned area data: obtaining fire dynamics information for every single fire

David Frantz A B , Marion Stellmes A , Achim Röder A and Joachim Hill A
+ Author Affiliations
- Author Affiliations

A Environmental Remote Sensing and Geoinformatics, Faculty of Spatial and Environmental Sciences, Trier University, Campus II, Behringstrasse 21, 54296 Trier, Germany.

B Corresponding author. Email: frantz@uni-trier.de

International Journal of Wildland Fire 25(12) 1228-1237 https://doi.org/10.1071/WF16003
Submitted: 5 January 2016  Accepted: 13 September 2016   Published: 8 November 2016

Abstract

Fire spread information on a large scale is still a missing key layer for a complete description of fire regimes. We developed a novel multilevel object-based methodology that extracts valuable information about fire dynamics from Moderate Resolution Imaging Spectroradiometer (MODIS) burned area data. Besides the large area capabilities, this approach also derives very detailed information for every single fire regarding timing and location of its ignition, as well as detailed directional multitemporal spread information. The approach is a top–down approach and a multilevel segmentation strategy is used to gradually refine the individual object membership. The multitemporal segmentation alternates between recursive seed point identification and queue-based fire tracking. The algorithm relies on only a few input parameters that control the segmentation with spatial and temporal distance thresholds. We present exemplary results that indicate the potential for further use of the derived parameters.

Additional keywords: fire regime, ignition point, Southern Africa.


References

Archibald S, Roy DP (2009) Identifying individual fires from satellite-derived burned area data. In ‘2009 IEEE international geoscience and remote sensing symposium proceedings’, 12–17 July 2009, Cape Town, South Africa. pp. 160–163. (IEEE: Piscataway, NJ) 10.1109/IGARSS.2009.5417974

Archibald S, Roy DP, Van Wilgen BW, Scholes RJ (2009) What limits fire? An examination of drivers of burnt area in southern Africa. Global Change Biology 15, 613–630.
What limits fire? An examination of drivers of burnt area in southern Africa.Crossref | GoogleScholarGoogle Scholar |

Bond WJ, Keeley JE (2005) Fire as a global ‘herbivore’: the ecology and evolution of flammable ecosystems. Trends in Ecology & Evolution 20, 387–394.
Fire as a global ‘herbivore’: the ecology and evolution of flammable ecosystems.Crossref | GoogleScholarGoogle Scholar |

Boschetti L, Roy DP, Justice CO, Giglio L (2010) Global assessment of the temporal reporting accuracy and precision of the MODIS burned area product. International Journal of Wildland Fire 19, 705–709.
Global assessment of the temporal reporting accuracy and precision of the MODIS burned area product.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXhtFOkur%2FO&md5=4904199a9648e23a9cb78eb620bc5504CAS |

Clark JD, Bakker EMVZ (1964) Prehistoric culture and Pleistocene vegetation at the Kalambo Falls, northern Rhodesia. Nature 201, 971–975.
Prehistoric culture and Pleistocene vegetation at the Kalambo Falls, northern Rhodesia.Crossref | GoogleScholarGoogle Scholar |

Cruz MG, Sullivan AL, Gould JS, Sims NC, Bannister AJ, Hollis JJ, Hurley RJ (2012) Anatomy of a catastrophic wildfire: the Black Saturday Kilmore East fire in Victoria, Australia. Forest Ecology and Management 284, 269–285.
Anatomy of a catastrophic wildfire: the Black Saturday Kilmore East fire in Victoria, Australia.Crossref | GoogleScholarGoogle Scholar |

Dwyer E, Pinnock S, Gregoire JM, Pereira JMC (2000) Global spatial and temporal distribution of vegetation fire as determined from satellite observations. International Journal of Remote Sensing 21, 1289–1302.
Global spatial and temporal distribution of vegetation fire as determined from satellite observations.Crossref | GoogleScholarGoogle Scholar |

Finney MA (2004) FARSITE: Fire Area Simulator – model development and evaluation. USDA Forest Service, Rocky Mountain Research Station, Research Paper RMRS-RP-4. (Ogden, UT)

Giglio L, Descloitres J, Justice CO, Kaufman YJ (2003) An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment 87, 273–282.
An enhanced contextual fire detection algorithm for MODIS.Crossref | GoogleScholarGoogle Scholar |

Hantson S, Pueyo S, Chuvieco E (2015) Global fire size distribution is driven by human impact and climate. Global Ecology and Biogeography 24, 77–86.
Global fire size distribution is driven by human impact and climate.Crossref | GoogleScholarGoogle Scholar |

Kantzas EP, Quegan S, Lomas M (2015) Improving the representation of fire disturbance in dynamic vegetation models by assimilating satellite data: a case study over the Arctic. Geoscientific Model Development 8, 2597–2609.
Improving the representation of fire disturbance in dynamic vegetation models by assimilating satellite data: a case study over the Arctic.Crossref | GoogleScholarGoogle Scholar |

le Roux J (2011) The effect of land-use practices on the spatial and temporal characteristics of savanna fires in Namibia. PhD dissertation, Friedrich-Alexander-Universität, Erlangen-Nürnberg, Germany.

Li C (2000) Fire regimes and their simulation with reference to Ontario. In ‘Ecology of a managed terrestrial landscape: patterns and processes of forest landscapes in Ontario’. (Eds AH Perera, DL Euler and ID Thompson) pp. 115–140. (UBC Press: Vancouver, BC)

Loboda TV, Csiszar IA (2007) Reconstruction of fire spread within wildland fire events in northern Eurasia from the MODIS active fire product. Global and Planetary Change 56, 258–273.
Reconstruction of fire spread within wildland fire events in northern Eurasia from the MODIS active fire product.Crossref | GoogleScholarGoogle Scholar |

Lu D (2006) The potential and challenge of remote sensing‐based biomass estimation. International Journal of Remote Sensing 27, 1297–1328.
The potential and challenge of remote sensing‐based biomass estimation.Crossref | GoogleScholarGoogle Scholar |

Mbow C, Goïta K, Bénié GB (2004) Spectral indices and fire behavior simulation for fire risk assessment in savanna ecosystems. Remote Sensing of Environment 91, 1–13.
Spectral indices and fire behavior simulation for fire risk assessment in savanna ecosystems.Crossref | GoogleScholarGoogle Scholar |

Pereira JMC (2003) Remote sensing of burned areas in tropical savannas. International Journal of Wildland Fire 12, 259–270.
Remote sensing of burned areas in tropical savannas.Crossref | GoogleScholarGoogle Scholar |

Roy DP, Lewis PE, Justice CO (2002) Burned area mapping using multitemporal moderate spatial resolution data – a bi-directional reflectance model-based expectation approach. Remote Sensing of Environment 83, 263–286.
Burned area mapping using multitemporal moderate spatial resolution data – a bi-directional reflectance model-based expectation approach.Crossref | GoogleScholarGoogle Scholar |

Roy DP, Frost PGH, Justice CO, Landmann T, Le Roux JL, Gumbo K, Makungwa S, Dunham K, Du Toit R, Mhwandagara K, Zacarias A, Tacheba B, Dube OP, Pereira JMC, Mushove P, Morisette JT, Santhana Vannan SK, Davies D (2005a) The Southern Africa Fire Network (SAFNet) regional burned‐area product‐validation protocol. International Journal of Remote Sensing 26, 4265–4292.
The Southern Africa Fire Network (SAFNet) regional burned‐area product‐validation protocol.Crossref | GoogleScholarGoogle Scholar |

Roy DP, Jin Y, Lewis PE, Justice CO (2005b) Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data. Remote Sensing of Environment 97, 137–162.
Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data.Crossref | GoogleScholarGoogle Scholar |

Scholes R, Kendall J, Justice C (1996) The quantity of biomass burned in southern Africa Journal of Geophysical Research 101, 23 667–23 676.
The quantity of biomass burned in southern AfricaCrossref | GoogleScholarGoogle Scholar |

Snyder JP (1987) ‘Map projections – a working manual.’ (USGPO: Washington, DC)

Staver AC, Archibald S, Levin S (2011) Tree cover in sub-Saharan Africa: rainfall and fire constrain forest and savanna as alternative stable states. Ecology 92, 1063–1072.
Tree cover in sub-Saharan Africa: rainfall and fire constrain forest and savanna as alternative stable states.Crossref | GoogleScholarGoogle Scholar |

Stellmes M, Frantz D, Finckh M, Revermann R (2013) Fire frequency, fire seasonality and fire intensity within the Okavango region derived from MODIS fire products. In ‘Biodiversity & ecology 5 – special volume: environmental assessments in the Okavango region’. (Eds J Oldeland, C Erb, M Finckh and N Jürgens) pp. 351–362. (University of Hamburg: Hamburg, Germany)

Trollope WSW, de Ronde C, Geldenhuys CJ (2004) Fire behaviour. In ‘Wildland fire management handbook for sub-Sahara Africa’. (Eds JG Goldammer and C De Ronde) pp. 199–217. (Global Fire Monitoring Center: Freiburg, Germany)

Turner MG, Romme WH, Gardner RH, Hargrove WW (1997) Effects of fire size and pattern on early succession in Yellowstone National Park. Ecological Monographs 67, 411–433.
Effects of fire size and pattern on early succession in Yellowstone National Park.Crossref | GoogleScholarGoogle Scholar |

Van Langevelde F, Van De Vijver CADM, Kumar L, Van De Koppel J, De Ridder N, Van Andel J, Skidmore AK, Hearne JW, Stroosnijder L, Bond WJ, Prins HHT, Rietkerk M (2003) Effects of fire and herbivory on the stability of savanna ecosystems. Ecology 84, 337–350.
Effects of fire and herbivory on the stability of savanna ecosystems.Crossref | GoogleScholarGoogle Scholar |