Remote sensing technology has great potential for mapping weed distributions. Fine-scale weed distribution maps can provide means to evaluate the success of weed control methods, to guide selection of future control methods, and to examine factors that influence the creation and persistence of monotypic weed patches. Here I examined the effectiveness of different classification approaches in detecting dense monotypic patches of the late-phenology weeds Taeniatherum caput-medusae (medusahead) and Aegilops triuncialis (barbed goatgrass), among cool-season forage grasses (Bromus spp. and Avena spp.) across multiple years in semi-arid rangelands in northern California (USA). I found that color infrared photographs acquired at two key phenological periods produced more accurate classifications than those based on one image alone, and that inclusion of training sites did not improve the overall accuracy of a classification. I also examined the association of remnant litter with transitions in species dominance in medusahead, goatgrass or forage patches. Persistence of goatgrass-dominated patches was correlated with the amount of remnant litter present, but surprisingly that of medusahead was not, suggesting a potential need for different strategies in control of these two noxious species. Overall, this study shows that remote sensing can be used to create weed distribution maps of phenologically distinct species, and help us further understand community response to invasion and evaluate the effectiveness of management treatments.
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