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

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.