Towards monitoring post-fire vegetation cover dynamics in the Mediterranean with the use of object-based image analysis of Landsat images

Abstract

Up to date information on vegetation cover is essential to assess daily fire potential danger. Since satellite sensors are able to cover wide areas at a high frequency and are also able to provide information about non-visible spectral regions, they represent a very valuable tool for monitoring vegetation recovery and vegetation succession after fire. The aim of this work was to develop a model for an operational monitoring of vegetation cover dynamics in fire-prone Mediterranean ecosystem with the use of multi-temporal Landsat images. The specific objectives were 1) to map the extent of burned areas, and 2) to monitor post-fire vegetation recovery within the fire affected areas. The work involved the development of an Object-Based Image Analysis (OBIA) model with the use of multi-temporal Landsat images covering North-Lebanon. In this approach, instead of processing all areas of an image with the same algorithms, a differentiated procedure would be more appropriate. The results of the classification showed the extent of burned areas (objects classified as burned) in one specific year. Subsequently, pixels located within objects previously classified as burned areas were monitored 16 years and 20 years of the fire events. It was found that the developed approach was flexible enough to be employed for a continuous monitoring of post-fire vegetation dynamics. In future work, it will be possible to 1) narrow the monitoring down to a yearly basis by importing multi-temporal satellite data acquired on every year after the fire event, and 2) assess the accuracy of the results by conducting field visits.