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Integration of forest inventory and satellite imagery:: a Canadian status assessment and research issues
Institution:1. Department of Geography, University of Toronto at Mississauga, 3359 Mississauga Road, Mississauga, Ont., Canada L5L 1C6;2. Department of Geography and Environmental Studies, Carleton University, B349 Loeb Building, 1125 Colonel By Drive, Ottawa, Ont., Canada K1S 5B6;3. Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 Burnside Road, Victoria, BC, Canada V8Z 1M5;1. University of Agder, Department of Engineering and Science, Kristiansand, Norway;2. Sørlandet Hospital Health Enterprise, Research Unit, Kristiansand, Norway;3. Stavanger University Hospital, Department of Pediatrics, Stavanger University Hospital, Stavanger, Norway;1. Chaire industrielle CRSNG UQAT-UQAM en aménagement forestier durable, Centre d’Étude de la Forêt, Département des Sciences Biologiques, Université du Québec à Montréal, Montréal, Québec H3C 3P8, Canada;2. Institut de Recherche sur les Forêts, Université du Québec en Abitibi-Témiscamingue, Rouyn-Noranda, Québec J9X 5E4, Canada;1. Laboratorio de Ecología de Enfermedades (LEcEn), Instituto de Ciencias Veterinarias del Litoral (ICiVet-Litoral), Universidad Nacional del Litoral (UNL)/Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), R.P Kreder 2805, CP: 3080, Esperanza, Santa Fe, Argentina;2. Instituto Nacional de Tecnología Agropecuaria (INTA), Estación Experimental Agropecuaria Rafaela, and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CC 22, CP 2300 Rafaela, Santa Fe, Argentina;1. Institute for Resources, Environment and Sustainability, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada;2. Department of Anthropology, 1218, University of Oregon, Eugene, OR, 97403, USA;3. Department of Archaeology, Hakai Institute, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada;4. Department of Anthropology, San Diego State University, 5500 Campanile Dr., San Diego, CA, 92182-6040, USA;1. Department and Institute of Microbiology and Virology, The School of Pharmacy and Division of Laboratory Medicine, Medical University of Silesia, Katowice, Poland;2. Division of Infectious Disease Control, Department of Virology, Norwegian Institute of Public Health, Oslo, Norway
Abstract:Canada's ability to sustainably manage approximately 10% of the global forest cover is a critical environmental and economic issue. The capacity to meet such demands and to deliver on national and international commitments regarding forest management is enabled through collaboration between federal, provincial, and territorial agencies. A principal collaborator is the National Forest Inventory (NFI); a systematic photo-plot based monitoring system designed specifically for reporting purposes and as an important input for scientific models. Satellite imagery is illustrated here as a support data set to ensure the quality of the NFI, for auditing the photo-plot contents, and to detect spatial biases. The Canadian Forest Service, in collaboration with the Canadian Space Agency and other federal and provincial agencies, is producing a national land cover database of the forested area of Canada (Earth Observation for Sustainable Development of Forests (EOSD)) using Landsat-7 ETM+ data for circa 2000 conditions. The integration between the plot-based NFI with classified EOSD data is presented for central British Columbia, an area comprising 6 Landsat scenes and 324 2 km × 2 km photo-plots. Traditional accuracy assessment measures based on the analysis of coincidence matrices are reported as levels of agreement for hierarchically aggregated land cover categories (overall agreements of 91%, 79%, 64% and 26% for 3, 4, 6 and 20 classes respectively) to demonstrate coincidence between the different data products. Local agreement between NFI and EOSD is demonstrated as a means of photo-plot auditing while spatial biases are detected through investigations of geographic pattern in the coincidence values. The illustrated approaches may be expanded or applied to different mapped attributes (e.g., biomass) that are of utility to those attempting to characterize large areas in a consistent and rigorous fashion.
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