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

Fire type mapping using object-based classification of Ikonos imagery

George H. Mitri A and Ioannis Z. Gitas A B

A Laboratory of Forest Management and Remote Sensing, Aristotle University of Thessaloniki, PO Box 248, University Campus, Thessaloniki, Greece.

B Corresponding author. Email: igitas@for.auth.gr

International Journal of Wildland Fire 15(4) 457-462 https://doi.org/10.1071/WF05085
Published: 7 December 2006

Abstract

Distinguishing and mapping areas of surface and crown fire spread has significant applications in the study of fire behaviour, fire suppression, and fire effects. Satellite remote sensing has supplied a suitable alternative to conventional techniques for mapping the extent of burned areas, as well as for providing post-fire related information (such as the type and severity of burn). The aim of the present study was to develop an object-based classification model for mapping the type of fire using very high spatial resolution imagery (Ikonos). The specific objectives were: (i) to distinguish between surface burn and canopy burn; and (ii) to assess the accuracy of the classification results by employing field survey data. The methodology involved two consecutive steps, namely image segmentation and image classification. First, image objects were extracted at different scales using multi-resolution segmentation procedures, and then both spectral and contextual object information was employed to classify the objects. The accuracy assessment revealed very promising results (approximately 87% overall accuracy with a Kappa Index of Agreement of 0.74). Classification accuracy was mainly affected by the density of the canopy. This could be attributed to the inability of the optical sensors to penetrate dense canopy to detect fire-affected areas. The main conclusion drawn in the present study is that object-oriented classification can be used to accurately distinguish and map areas of surface and crown fire spread, especially those occurring in open Mediterranean forests.

Additional keywords: canopy burn; fuzzy analysis; image segmentation; surface burn.


References


Albini F , Stocks B (1986) Predicted and observed rates of spread of crown fires in immature jack pine. Combustion Science and Technology  48, 65–76.


Alexander M (2000) Fire behaviour as a factor in forest and rural fire suppression, Forest Research Bulletin No. 197, Forest and Rural Fire Science and Technology Series Report No. 5. Forest Research, Rotorua in association with New Zealand Fire Service Commission and National Rural Fire Authority, Wellington, New Zealand.

Baatz M, Schäpe A (2000) Multi-resolution segmentation – an optimization approach for high quality multi-scale image segmentation. In ‘Angewandte geographische Informationsverarbeitung XI. Beiträge zum AGIT-Symposium Salzburg 2000’, Karlsruhe. (Ed. J Strobl) pp. 12–23. (Herbert Wichmann Verlag: Heidelberg)

Beaty R , Taylor A (2001) Spatial and temporal variation of fire regimes in a mixed conifer forest landscape, Southern Cascades, California, USA. Journal of Biogeography  28, 955–966.
CrossRef |

Chuvieco E , Congalton RG (1988) Mapping and inventory of forest fires from digital processing of TM data. Geocarto International  4, 41–53.


Civanlar R , Trussell H (1986) Constructing membership functions using statistical data. Fuzzy Sets and Systems  18, 1–13.
CrossRef |

Definiens Imaging (2002) Object-oriented image analysis, eCognition user guide. Munich. Available at http://www.definiens-imaging.com [Verified 17 January 2005]

Escuin S, Navarro R , Fernandez P (2002) Using remote sensing and GIS to assess wildfire damage throughout the Mediterranean. Earth Observation Magazine  11, 19–22.


FAO (1999) Mediterranean forests. Unasylva  50, 35–41.


Gitas I (1999) Geographical information systems and remote sensing in mapping and monitoring fire-altered forest landscapes. PhD Thesis, University of Cambridge, UK.

Gitas I , Rishmawi K (2003) Burned area mapping with the use of low, medium-high and very high resolution satellite imagery. Geotechnical Scientific Issues  44, 4–15.


Gitas I, Mitri G , Ventura G (2004) Object-oriented image analysis for burned area mapping using NOAA-AVHRR imagery in Creus Cape, Spain. Remote Sensing of Environment  92, 409–413.
CrossRef |

Graham R (2003) ‘Hayman fire case study.’ USDA Forest Service, Rocky Mountain Research Station General Technical Report RMRS-GTR-114. (Ogden, UT)

Hadjimitsis D, Clayton C , Hope V (2004) An assessment of the effectiveness of atmospheric correction algorithms through the remote sensing of some reservoirs. International Journal of Remote Sensing  25, 3651–3674.
CrossRef |

Jakubauskas M, Lulla K , Mausel P (1990) Assessment of vegetation change in a fire-altered forest landscape. Photogrammetric Engineering and Remote Sensing  56, 371–377.


Karteris M (1995) Burned land mapping and post-fire effects. In ‘Remote sensing and GIS applications to forest fire management’. (Ed. E Chuvieco) pp. 35–44. (University of Alcala: Alcala de Henares, Spain)

Milne A (1986) The use of remote sensing in mapping and monitoring vegetational change associated with bushfire events in Eastern Australia. Geocarto International  1, 25–35.


Mitri G , Gitas I (2004a) A semi-automated object-oriented model for burned area mapping in the Mediterranean region using Landsat-TM imagery. International Journal of Wildland Fire  13, 367–376.
CrossRef |

Mitri G , Gitas I (2004b) A performance evaluation of a burned area object-based classification model when applied to topographically and non-topographically corrected TM imagery. International Journal of Remote Sensing  25, 2863–2870.
CrossRef |

Patterson MW , Yool SR (1998) Mapping fire-induced vegetation mortality using Landsat TM data: a comparison of linear transformation techniques. Remote Sensing of Environment  65, 132–142.
CrossRef |

Pausas J, Vallejo V (1999) The role of fire in European Mediterranean ecosystems. In ‘Remote Sensing of Large Wildfires’. (Ed. E Chuvieco) pp. 3–16. (Springer-Verlag: Berlin)

Pollet J , Omi P (2002) Effect of thinning and prescribed burning on crown fire severity in ponderosa pine forests. International Journal of Wildland Fire  11, 1–10.
CrossRef |

Rogan J , Yool S (2001) Mapping fire-induced vegetation depletion in the Peloncillo Mountains, Arizona and New Mexico. International Journal of Remote Sensing  22, 3101–3121.
CrossRef |

Scott J, Reinhardt E (2001) ‘Assessing crown fire potential by linking models of surface and crown fire behaviour.’ USDA Forest Service, Rocky Mountain Research Station Research Paper RMRS-RP-29. (Fort Collins, CO)

Smith R , Woodgate P (1985) Appraisal of fire damage and inventory for timber salvage by remote sensing in mountain ash forests in Victoria. Australian Journal of Forestry  48, 252–263.


Stephens S (1998) Evaluation of the effects of silvicultural and fuels treatments on potential fire behaviour in Sierra Nevada mixed conifer forests. Ecology and Management  105, 21–35.
CrossRef |

Tanaka S , Sugimura T (2001) Cover: a new frontier of remote sensing from IKONOS images. International Journal of Remote Sensing  22, 1–5.
CrossRef |

Tsatsoulis C (1993) Expert systems in remote sensing applications. IEEE Geoscience and Remote Sensing Newsletter  June, 7–15.


White J, Ryan K, Key C , Running S (1996) Remote sensing of forest fire severity and vegetation recovery. International Journal of Remote Sensing  6, 125–136.



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