EOF analysis of the data on grain-size distributions of sediments in the ¿-size class from the beach foreshore, backshore, dune, and nearshore environments of Colva and Calangute revealed that the first three ¿ -dependent eigenfunctions c1(¿), c2(¿), and c3(¿) account for more than 97% to 99% of variation in the data set, the largest variation being represented by the first ¿ dependent function c1(¿) alone. This function showed significant differences in the concentration of grain-size particles across the shore covering various physiographic units of Colva, i.e., dominance of very fine sands in the dunes and backshore, fine sands in the foreshore, and silt and clays in the offshore areas beyond 5-m water depths, reflecting the impact of the changing character of the transportational and depositional processes affecting the sediments, thus implying different energy environments. This analysis also showed marked along shore variations in the sediment distribution pattern in different sectors of the subaerial beach of Colva and suggests transportation of sediments from either ends to the central region. The three energetic eigenfunctions used to obtain the predictable or information rich part of the original signal are comparable with normalized input data and indicate the efficacy of this method.