Large-area inventory of species composition using airborne laser scanning and hyperspectral data

Tree species composition is an essential attribute in stand-level forest management inventories and remotely sensed data might be useful for its estimation. Previous studies on this topic have had several operational drawbacks, e.g., performance studied at a small scale single tree-level with large fieldwork costs. The current study presents the results from large-area inventory providing following area-based approach. utilizes combination of airborne laser scanning hyperspectral 97 field sample plots 250 m collected over 350 km productive Norway. show that, availability data, species-specific volume proportions can provided acceptable 90% cases plot level. Dominant were classified overall accuracy 91% kappa-value 0.73. Species-specific volumes estimated relative root mean square differences 34%, 87%, 102% Norway spruce ( (L.) Karst.), Scots pine L.), deciduous species, respectively. A novel tree-based approach selecting pixels improved compared to traditional based normalized difference vegetation index.22Picea abiesPinus sylvestris