Classification analyses of vegetation for delineating forest fire fuel complexes in a Mediterranean test site using satellite remote sensing and GIS

• Published in: International journal of remote sensing 2003-08, Vol.24 (15), p.3093-3104
• Main Authors: Koutsias, N., Karteris, M.
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; Earth sciences; Earth, ocean, space; Engineering and environment geology. Geothermics; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Pollution, environment geology; Teledetection and vegetation maps
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/0143116021000021152

If fuel, weather and topography are considered to be the most important determinants of wildfire occurrence, it is evident that only fuel can be kept under human control and modified to reduce fire potential. In the present study, forest fuel mapping is considered from a remote sensing perspective by the assessment and mapping of general vegetation complexes. The purpose is to delineate forest types which present a particular fire behaviour and to explore the use of Landsat TM data for their mapping. The spectral classes were derived by considering as key elements of the classification scheme the main species that prevail in the overstory layer, as well as meaningful mixtures of them, discriminated by their degree of density as indicated from vegetation indices. The study area, Halkidiki, Greece, which has strong spatial heterogeneity in both the composition and structure of its ecosystems, as well as of their spatial distribution and arrangement, is a characteristic area and representative of the majority of landscape types found across Greece. The overall classification accuracy of the original Landsat TM image (85.30%) was not improved significantly when other synthetic spectral channels or the digital elevation model were integrated with the satellite data, possibly because the detailed classification scheme adopted was determined using the overall spectral discrimination offered by the original satellite data.