Pan-European forest/non-forest mapping with Landsat ETM+ and CORINE Land Cover 2000 data |
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| Authors: | Anssi Pekkarinen Lucia Reithmaier Peter Strobl |
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| Institution: | 1. Remote Sensing Division, National Institute for Space Research, Av. dos Astronautas 1758, 12227-010 São José dos Campos, SP, Brazil;2. Institute of Informatics, Federal University of Rio Grande do Sul, Av. Bento Gonçalves 9500, 91509-900 Porto Alegre, RS, Brazil;3. National Institute for Science, Education and Technology, R. Eng. Alfredo Huch 475, 96201-460 Rio Grande, RS, Brazil;4. Geosciences Institute, University of Campinas, R. João Pandiá Calógeras 51, 13083-870 Campinas, SP, Brazil;1. Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden;2. Swedish Forest Agency, Jönköping, Sweden;1. Dipartimento di Bioscienze e Territorio, University of Molise, Contrada Fonte Lappone, Pesche, IS 86090, Italy;2. Northern Research Station, U.S. Forest Service, Saint Paul, Minnesota 55108, USA;3. Department of Agricultural, Food and Forestry Systems, University of Florence, Florence 50145, Italy;1. Pacific Northwest Research Station, USDA Forest Service, 3200 SW Jefferson Way, Corvallis, OR 97331, USA;2. Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA;1. Stinger Ghaffarian Technologies, contractor to the U.S. Geological Survey, Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198, USA;2. College of Environmental Science and Forestry, State University of New York, Syracuse, NY 13210, USA;3. Innovate! Inc., contractor to the U.S. Geological Survey EROS Center, Sioux Falls, SD 57198, USA;4. U.S. Forest Service Southern Research Station, Knoxville, TN 37919, USA;5. Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA;6. U.S. Forest Service, Pacific Northwest Research Station, 3200 SW Jefferson Way, Corvallis, OR 97331, USA;7. U.S. Forest Service, Rocky Mountain Research Station, 507 25th Street, Ogden, UT 84401, USA;8. U.S. Geological Survey EROS Center, Sioux Falls, SD 57198, USA |
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| Abstract: | This paper describes a simple and adaptive methodology for large area forest/non-forest mapping using Landsat ETM+ imagery and CORINE Land Cover 2000. The methodology is based on scene-by-scene analysis and supervised classification. The fully automated processing chain consists of several phases, including image segmentation, clustering, adaptive spectral representativity analysis, training data extraction and nearest-neighbour classification. This method was used to produce a European forest/non-forest map through the processing of 415 Landsat ETM+ scenes. The resulting forest/non-forest map was validated with three independent data sets. The results show that the map’s overall point-level agreement with our validation data generally exceeds 80%, and approaches 90% in central European conditions. Comparison with country-level forest area statistics shows that in most cases the difference between the forest proportion of the derived map and that computed from the published forest area statistics is below 5%. |
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