A Remote Sensing Image Processing Framework for Damage Assessment in a Forest Fire Scenario

Abstract

In natural hazards management applications Earth Observation (EO) image processing methods are based on segmentation and classification. The result primary consists of thematic maps which are readily interpretable. We propose a complete EO image processing chain, which generates an end product with increased information content organized in thematic layers. The processing chain integrates four main components: image classification, identification of high anomaly areas relative to the entire scene context, spectral and texture change detection, and the integration of different information layers. The processing chain was tested in a fire management scenario, using a pair of Landsat5-TM images for the Pagami Creek forest fire which was active from August to October 2011.