Hyperspectral sensors offer an alternative to time-consuming wet chemistry techniques for measuring humification (degree of decomposition). SHAC results for the Dark Peak showed strong correlations between spectral indices developed for HyMap and the degree of humification of exposed peat, measured colorimetrically as percent transmission (McMorrow et al., 2002; Cutler et al., 2002; McMorrow et al,. 2004a, b). This application for the new hyperspectral sensor, with supporting LiDAR and aerial photos, aims to test the transferability of the relationships to another date and sensor at the Dark Peak site. A related bid by Cutler (Dundee) will test spatial transferability to a Scottish site. We will use data collected for SHAC and CASI-SWIR flights, plus additional sites within resources available. Humification indices developed for HyMap, and moisture indices developed with the ASD (McMorrow et al., 2003), will be calculated for the new sensor. Correlation, stepwise regression and artificial neural networks will be used to investigate relationships with humification and gravimetric moisture content. The analysis will be repeated with ASD spectra in contact probe and field mode to investigate sensitivity to spatial resolution. The best models will be used to produce images of exposed peat humification and surface moisture content. Results will be compared with those for the Scottish site.