The overall aim of this project is to develop hyperspectral and LiDAR techniques that will enable rapid and detailed characterisation of the surface structure of blanket peatland, from micro to macro scales. Blanket peatlands are complex landscape units that show distinct heterogeneity in surface elevation and vegetation/land cover at scales ranging from 1 to > 1000 m. Peatland hydrological and biogeochemical processes are both intimately related to heterogeneity in surface structure at the micro scale (1-100 m). The development of remote sensing techniques for quantifying surface attributes at the micro scale is the first, crucial step that will enable routine monitoring of peatland response to environmental change and the accurate estimation of peatland contributions to regional and global CH4 emissions. Multidate hyperspectral AISA sensor data are requested in support of two PhD studentships addressing separate but complementary issues of the spectral classification of microform abundance within discrete microtopes on blanket mires, and the scaling effects of methane emission 'hot spots' on reflectance. Two contrasting study sites are proposed (southwestern and far northeastern Scotland) allowing the generality of the results to be tested. Overflights will be supported by a detailed ground survey aimed at establishing spectral libraries of reflectance from peatland microforms and at the accurate geometric and atmospheric correction of the datasets. Analysis will be directed towards unmixing approaches for the accurate classification of microtope boundaries, and the scale dependencies in the peatland systems with a view to the best non-linear methods of scaling from high to coarser scale resolution.