Forest species classification using Object Oriented Image Analysis – does CIR aerial imagery and Object Oriented Methods offer new possibilities?
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National Forest Inventories (NFI) in Britain such as the Forestry Commission’s National Inventory of Woodlands and Trees (NIWT) and the Native Woodland Survey of Scotland (NWSS) provide a synoptic view of the current extent, condition and location of forest resources. The NFI’s not only need to be accurate and precise but also up-to-date. Current methods of producing NFIs in Britain rely on manual photo-interpretation analysis of digital aerial photographs combined with field-based surveys. Development of a cost effective and reliable method to identify tree species as a semi- automated process would be of major benefit to forest management. This research explores object oriented image analysis methods for Forest Inventory classification on three levels: 1.Woodland/Non woodland, 2. Interpreted Forest Types (IFT) and 3. Species using 40cm resolution Colour InfraRed Imagery and Definiens Developer Software. A 17km2 study area within Clocaeanog Forest, Wales, was chosen with the intention of developing a robust classification ruleset. The area was flown throughout 2006, resulting in variations across the study area of sun angle, cloud cover, vegetation, intensity etc. However, a hierarchical image object classification scheme based on three levels has been generated and analysed to identify feature characteristics associated with individual species recognition and thereby aid production of NFIs