Sphagnum’s strong water-holding capacities, its dominance in bogs, and the overall importance of water in regulating photosynthesis make it a key ecosystem engineer. Though its effectiveness in this context has rarely been tested, Spectral Vegetation Indices (SVIs) derived from hyperspectral data allow for efficient modeling of Sphagnum gravimetric water content over large scales. This study tests whether a linear model relating a SVI to Sphagnum gravimetric water content (ie S. capillifolium, S. magellanicum, S. angustifolium/S. fallax, or all Sphagnum species pooled together) can be applied to the landscape level using airborne hyperspectral imagery taken over Mer Bleue Bog, near Ottawa, Ontario, Canada. The depth of a Sphagnum species sample contributing to the reflectance and the vertical distribution of water across a species sample was also analyzed to test the accuracy of water content measurements. Additionally, image SVI data were compared to field SVI data to test the effectiveness of image spectra. Results indicate that light penetrated 1.5 cm in S. capillifolium samples, 1.0 cm in S. magellanicum samples, and 2.5 cm in S. angustifolium/S. fallax samples. Water variability was highest in samples with elevated water contents for every Sphagnum species analyzed. The Normalized Difference Water Index (NDWI)(dimensionless) was the most effective in estimating Sphagnum gravimetric water content of all SVIs (Root Mean Square Error= 161.34%, P= 0.000). Image NDWI values mimicked field NDWI values (Root Mean Square Error= 0.000740, P= 0.0000). The application of the NDWI to areas identified as being favorable for Sphagnum growth in an image resulted in a map of Sphagnum gravimetric water content for a given day in a bog.