Mapping a burned forest area from Landsat TM data by multiple methods

Forest fire is one of the dominant disturbances in boreal forests. It is the primary process responsible for organizing the physical and biological attributes of the boreal biome, shaping landscape diversity and influencing biogeochemical cycles. The Greater Hinggan Mountain of China is rich in forest resources while suffers from a high incidence of forest fires simultaneously. In this study, focusing on the most serious forest fire in the history of P. R. China which occurred in this region, we made use of two Landsat-5 TM (Thematic Mapper) images, and proposed to map the overall burned area and burned forest area by multiple methods. During the mapping, the fire perimeter, as well as rivers, roads and urban areas were first extracted and masked visually, and then four indices of Normalized Difference Vegetation Index, Enhanced Vegetation Index, Vegetation Fractional Cover and Disturbance Index were calculated. For each index, the optimal threshold for separating burned from unburned forest area was determined using their histograms. For comparison, threshold segmentation using single-band reflectance was performed, in addition to a Maximum Likelihood Classifier (MLC) based supervised classification of all features and forest area alone; their accuracies were also evaluated and analysed. Among all the methods compared here, mapping by EVI threshold segmentation proved to be optimal by the comparisons of overall accuracy (99.78%) and the kappa coefficient (0.9946). Finally, the calculated burned area and burned forest area were compared with the values from official statistics. Compared with the classical methods used to report official statistics on burned areas, the remote sensing-based mapping is more objective and efficient, less labour- and time-consuming, and more repeatable.