Despite the increased agricultural fields and food production, advances in agricultural technolgy and know-how have also caused significant environmental change in many regions. Monitoring irrigated lands and updating information about the use of each agricultural parcel is very valuable for a variety of agricultural-related agencies for research purposes. Additionally, many applications such as updating cadastral information, land-cover or land-use mapping, estimating agricultural subsidies require primarily a parcel-based study. Hence, a correct delineation of the parcels becomes very crucial. In this paper, we propose an algorithm for automatic delineation of agricultural parcels. We first apply watershed segmentation to high resolution remote sensing imagery. Applying watershed segmentation yields many superpixels which do not correspond to the actual parcels in the scene. We assume that the geometric and texture properties of parcels to be segmented are different from each other, but they are similar for the superpixels that fall into the same parcel. In order to improve segmentation, the superpixels are merged based on the assumptions that superpixels that have similar textural characteristics and which are also within close proximity of each other should be merged. In order to evaluate the performance of the proposed method, percentage of correctly segmented parcel areas are computed with respect to the manual ground truth delineation.