Fire Spread from MODIS Burned Area Data: Obtaining Fire Dynamics Information for Every Single Fire. Frantz, D., Stellmes, M., Röder, A., & Hill, J. International Journal of Wildland Fire, 25(12):1228–1237, January, 2017.
doi  abstract   bibtex   
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.
@article{frantzFireSpreadMODIS2017,
  title = {Fire Spread from {{MODIS}} Burned Area Data: Obtaining Fire Dynamics Information for Every Single Fire},
  shorttitle = {Fire Spread from {{MODIS}} Burned Area Data},
  author = {Frantz, David and Stellmes, Marion and R{\"o}der, Achim and Hill, Joachim},
  year = {2017},
  month = jan,
  volume = {25},
  pages = {1228--1237},
  issn = {1448-5516},
  doi = {10.1071/WF16003},
  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\textendash 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.},
  journal = {International Journal of Wildland Fire},
  keywords = {~INRMM-MiD:z-JSMTJHIT,burnt-area,modis,remote-sensing,spatial-spread,wildfires},
  language = {en},
  lccn = {INRMM-MiD:z-JSMTJHIT},
  number = {12}
}

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