Discriminating Native and Nonnative Grasses in the Dry Mixedgrass Prairie With MODIS NDVI Time Series

Separating native grasses from tame pastures is an important mapping exercise that assists in the assessment of biodiversity, delineation of species' habitat, and appraisal of rangeland health. However, native grasslands (primarily naturally occurring species) and tame pastures (primarily nonnative grasses planted for hay, pasture, or seed) are spectrally similar and therefore difficult to differentiate with traditional remote sensing techniques and with air-photo interpretation. We used seasonal profiles of the normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments to examine the separability of native grasslands and tame pastures (where both types employ the C3 photosynthetic pathway) in the Dry Mixedgrass natural subregion of Alberta, Canada. The two classes were found to have different rates of spring green up at the pixel level that allowed for separation with a simple linear discriminant function. We achieved an overall accuracy of 73% (n = 100 independent test cases) with the MODIS time series-a statistically significant improvement of the photo-interpretation-based Grassland Vegetation Inventory (52%): the current standard for vegetation information in Alberta's agricultural zone. We also found that the multitemporal method was able to select dates for single-date classifications that provided relatively high classification accuracies (up to 71% overall). In addition to achieving higher levels of overall accuracy than more conventional methods, the MODIS time series produced much more reliable identification of abandoned pastures: formerly planted rangelands that lack many of the visual cues used by photo interpreters.