An Algorithm for Extracting Burned Areas from Time Series of AVHRR GAC Data Applied at a Continental Scale.

Abstract

This study describes the methodology developed to detect burned surfaces using a large time series of low-resolution satellite data. NOAA-AVHRR-GAC 5 Km images were used because they constitute a very complete historical data set of satellite imagery over Africa. Preliminary results showed that indices that make use of the information contained in Channel 2 and Channel 3 are the most adequate to detect burned areas. The Burned Area Algorithm (BAA) relies on a multitemporal multithreshold approach, based on the spectral changes of the land surface after a fire occurrence. Validation of the algorithm was done through comparison with a number of Landsat TM images that were classified in terms of burned and unburned surfaces, showing an overall accuracy of 71%.