IEIE Transactions on Smart Processing and Computing

The Institute of Electronics and Information Engineers (대한전자공학회)
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Burned Area Detection After Wildfire Using Landsat 7 ETM+ SLC-off Images

  • Quoc, Khanh Le (Human - Machine Interaction Laboratory, University of Engineering and Technology, Vietnam National University) ;
  • Sy, Tan Nguyen (Human - Machine Interaction Laboratory, University of Engineering and Technology, Vietnam National University) ;
  • Nhat, Thanh Nguyen Thi (Human - Machine Interaction Laboratory, University of Engineering and Technology, Vietnam National University) ;
  • Thanh, Ha Le (Human - Machine Interaction Laboratory, University of Engineering and Technology, Vietnam National University)
  • Received : 2012.07.14
  • Accepted : 2012.08.14
  • Published : 2013.06.30
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Abstract

The increasing demand for monitoring wildfires and their impact on the land surface have prompted studies of burned area extraction and analysis. To differentiate burned and unburned area, the earlier method of the Moderate Resolution Imaging Spectro-radiometer (MODIS) Burned Area Detection Algorithm was proposed to estimate the change in land surface based on the reflectance energy. The energy, whose wavelengths are sensitive to burning, was selected to calculate the change parameter $Z_{score}$. This method was applied using the MODIS images to produce a MODIS Burned Area product. The approach was to simplify this algorithm to make it compatible with the Landsat 7 ETM+ SLC-off images. To extract the refined version of burned regions, post-processing was carried out by applying a median filter, dilation morphology algorithm, and finally a gap filling method. The experimental results showed that the detailed burned areas extracted from the proposed method exhibited more spatial details than those of the MODIS Burned products in the large U.S areas. The results also revealed the discontinuous distribution of burned regions in Vietnam forests.

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