An intercomparison of burnt area estimates derived from key operational products: the Greek wildland fires of 2005–2007
- 1Department of Natural Resources Development and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 118 55 Athens, Greece
- 2Institute of Geography & Earth Sciences, University of Aberystwyth, Old College, King Street, SY23 2DB Aberystwyth, Wales, UK
Abstract. With the support of new technologies such as of remote sensing, today's societies have been able to map and analyse wildland fires at large observational scales. With regards to burnt area mapping in particular, two of the most widely used operational products are offered today by the United States National Aeronautics and Space Administration (NASA) and the European Forest Fires Information System (EFFIS) of the European Commission. In this study, a rigorous intercomparison of the burnt area estimates derived by these two products is performed in a geographical information system (GIS) environment for the Greek fires that occurred from 2005 to 2007. For the same temporal interval, the relationships of the burnt area estimates by each product are examined with respect to land use/cover and elevation derived from CORINE 2000 and the ASTER global digital elevation model (GDEM), respectively. Generally, noticeable differences were found in the burnt area estimates by the two products both spatially and in absolute numbers. The main findings are described and the differences in the burnt area estimates between the two operational datasets are discussed. The lack of precise agreement between the two products which was found does not necessarily mean that one or the other product is inaccurate. Rather, it underlines the requirement for their calibration and validation using high-resolution remote sensing data in future studies. Our work not only builds upon a series of analogous studies evaluating the accuracy of the same or similar operational products worldwide, but also contributes towards the development of standardised validation methodologies required in objectively evaluating such datasets.