What
Burn scar mapping and damage assessment

Where
Greece, Peloponnese region, summer 2007

Keywords
Fires, forest, agricultural land

Context
Every year, new forest fires occur in southern Europe, destroying thousands of hectares of forest, farmland, houses and infrastructures. In recent years, forest fires across the Mediterranean countries have burnt about half a million hectares of woodland per year. In Greece alone, some 200,000 hectares of forested lands and natural vegetation, including croplands and houses, were totally destroyed during the summer of 2007.
Knowledge of past fire events and mapping of burn scars and fire damage enable a better understanding of risks and fire prevention measures. Moreover, estimates of damaged areas are very useful to forestry services, to support reforestation and planting campaigns and to plan subsequent firefighting activities.
Remotely sensed data acquired at various spatial, spectral and temporal resolutions have proven viable for delineating burnt areas, determining species affected and assessing damage in affected areas.

Objectives
Two burn area classification methods were compared: one based on a fixed thresholding method using a set of specifically designed and combined image enhancements; the other on a decision-tree classification approach employing a wide range of biophysical parameters. The results helped to appreciate the economic value of burnt land, using a land-cover classification obtained with pre-fire imagery (more…).

Partners/clients
ISARS/NOA (Institute for Space Applications and Remote Sensing of the National Observatory of Athens) link

Methodology/Results
The two burn scar mapping methods were deployed and compared in operational mapping conditions, using sets of single or multidate satellite imagery. The evaluation of the two methods, based on existing validation data, showed that for single acquisitions or a multidate approach both methods can achieve high detection rates of the order of 80-91%, with a minimum burnt area size detected by either method of 0.9-1 ha.
The fixed thresholding method of ISARS/NOA referred to as BSM_NOA consists in detecting radiometric changes of damaged lands, while the decision tree approach of ITF (BSM_ITF) is detecting fire seeds based on biophysical parameters (green and brown vegetation, canopy shadow factor, soil cover fraction and soil brightness) and post-processed with a growing-region algorithm.
Either of the two burn scar mapping methods was able to generate objective and precise burn scar maps at local to national level.
Damage assessment maps were also derived from these results, helping to evaluate land-cover classes affected or burnt, such as farmlands, vineyards, olive trees and forests.


Figure 1: The BSM-NOA product corresponding to Parnitha fire in the north of the city of Athens- July 2007, Burnt Area Size= 4726 Ha, Input satellite data: SPOT 4 XS


Citations – Publication of the results
The methodological aspects of the two approaches, together with the results of their application in Greece, have been part of a scientific publication in the International Journal of Applied Earth Observation and Geoinformation magazine, entitled as “A Comparative Analysis of a Fixed Thresholding vs. a Classification Tree Approach for Operational Burn Scar Detection and Mapping”. The article is now available online at: http://dx.doi.org/10.1016/j.jag.2009.04.001

Full paper citation: Kontoes C.C., Poilvé H., Florsch G., Keramitsoglou I., Paralikidis S., A Comparative Analysis of a Fixed Thresholding vs. a Classification Tree Approach for Operational Burn Scar Detection and Mapping, submitted for publication in the International Journal of Applied Earth Observation and Geoinformation, in press, DOI: 10.1016/j.jag.2009.04.001

Data used
Landsat 5 TM and SPOT 4 HRV

Land-cover classification (pre-fire image), 12 classes
Discontinuous urban fabric, non-irrigated arable land, vineyards, olive groves, broad-leaved forest, coniferous forest, natural grasslands, sclerophyllous vegetation, sparsely vegetated areas, inland marshes, water bodies.