 This study examined the effectiveness of various combinations of lands at 8 surface reflectance, L8SR, data and time series images and producing accurate land cover maps. It found that the best performing combination was a time series dataset of summer images, June-September, with an overall accuracy of 89.8%, followed by a median composite of the same images at 88.74%. The difference between these two approaches was not statistically significant according to the McNemar test, p greater than 0.05%. However, significant differences were observed between each pair of combinations, indicating that the selection of the dataset used in any classification on G is an important and crucial step, since the input images for the composition can have a large impact on the accuracy of the final map. This article was authored by Tan Noi Fan, Berina Kuch, and Lucas W. Leonard.