Land cover mapping at BOREAS using red edge spectral parameters from CASI imagery

Scientific and technical challenges remain significant to accurate classifi cation of land cover and forest species as a result of the many spectral an d spatial variables influencing surface reflectance, coupled with the const raints imposed by the spectral and spatial characteristics of the remote se nsing instrumentation. The use of systematic differences in canopy pigment or chemistry by cover type or by species as a basis for land cover classifi cation has very recently emerged as a potentially new approach. In this stu dy, classification of land cover is investigated, based on chlorophyll cont ent variations as inferred from spectral bands in the red edge reflectance region. This analysis was carried out on data collected with the Compact Ai rborne Spectrographic Imager (CASI) for a 16 km x 12 km image mosaic over t he submodeling grid of the southern study area at the Boreal Ecosystem-Atmo sphere Study (BOREAS). The analysis demonstrates that land cover mapping, b ased solely on red edge spectral parameters, appears to be feasible, robust , and for some cover classes outperforms other current classification metho ds. Classification accuracy assessments of the derived land cover maps were performed using a forest inventory map provided by the Saskatchewan Enviro nment and Resource Management Forestry Branch-Inventory Unit (SERM-FBIU). T he red edge parameter-based land cover classification showed producer's acc uracies which exceeded 68.6% for all classes identified: conifers (however, without an ability to separate wet from dry conifers), mixed stands, fen, and disturbed and regeneration features. The corresponding user's accuracie s for these classes ranged between 58 and 66%, with the overall classificat ion accuracies of 61.15% and Kappa coefficient (K) of 0.52. In comparison, the corresponding Kappa coefficients for the cover classification using 16 channel CASI data and for a TM-based classification, were 0.36 and 0.29, re spectively. Results of this study suggest that whereas land cover classific ation accuracy improvements for the important but illusive fen cover type i n the boreal ecosystem are possible using classifications based on red edge parameters, significant uncertainties remain in the estimated aerial exten t.