ACCURACY ASSESSMENT ISSUES IN THE SIBERIA PROJECT

Russia’s boreal forests host 11% of the world’s live forest biomass. They play a critical role in Russia’s economy, as well as in stabilising the global climate.The boreal forests of Central and Western Siberia represent the largest unbroken tracts of forest in the world, and are listed as “Last Frontier Forests” by the World Resources Institute. The EU-funded SIBERIA project aimed at producing a forest map covering an area of 1.2 million square kilometres. Two operational Synthetic Aperture Radars (SAR) on board of the satellites ERS-1, ERS-2 and JERS-1 are used to provide remote sensing data. The objective was to combine data from two different wavelengths with SAR interferometry to deliver a large-scale forest map from SAR. The development of an appropriate classification algorithm proved difficult because of large variation in image features between images. An accuracy assessment of the classification results was carried out using spatial forest inventory data from several Russian Forestry Enterprises. Issues of geometric, radiometric, and classification accuracy are discussed and a method for accuracy assessment is presented.

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