The acorn is the fruit of the oak and is an important crop in the Spanish dehesa extreme\~na, especially for the value it provides in the Iberian pig food to obtain the "acorn" certification. For this reason, we want to maximise the production of Iberian pigs with the appropriate weight. Hence the need to know the area covered by the crowns of the acorn trees, to determine the covered wooded area (CWA, from the Spanish Superficie Arbolada Cubierta SAC) and thereby estimate the number of Iberian pigs that can be released per hectare, as indicated by the royal decree 4/2014. In this work, we propose the automatic estimation of the CWA, through aerial digital images (orthophotos) of the pastureland of Extremadura, and with this, to offer the possibility of determining the number of Iberian pigs to be released in a specific plot of land. Among the main issues for automatic detection are, first, the correct identification of acorn trees, secondly, correctly discriminating the shades of the acorn trees and, finally, detect the arbuscles (young acorn trees not yet productive, or shrubs that are not oaks). These difficulties represent a real challenge, both for the automatic segmentation process and for manual segmentation. In this work, the proposed method for automatic segmentation is based on the clustering algorithm proposed by Gustafson-Kessel (GK) but the modified version of Babuska (GK-B) and on the use of real orthophotos. The obtained results are promising both in their comparison with the real images and when compared with the images segmented by hand. The whole set of orthophotos used in this work correspond to an approximate area of 142 hectares, and the results are of great interest to producers of certified "acorn" pork.

翻译：橡树果实是西班牙埃斯特雷马杜拉牧场的重要作物，其价值尤其体现在为伊比利亚黑猪提供饲料以获得"橡果饲养"认证。因此，我们期望通过优化伊比利亚黑猪的体重来最大化其产量。根据皇家法令4/2014的规定，需要确定橡树冠层覆盖面积（CWA，源自西班牙语Superficie Arbolada Cubierta SAC），从而估算每公顷土地可放养的伊比利亚黑猪数量。本研究提出基于埃斯特雷马杜拉牧场航空数字正射影像的CWA自动估算方法，为特定地块确定伊比利亚黑猪放养数量提供依据。自动检测面临的主要挑战包括：首先需准确识别橡树；其次需正确区分橡树阴影；最后需检测灌木状幼树（尚未产果的幼龄橡树或非橡树灌木）。这些难题对自动分割和人工分割均构成实际挑战。本研究提出的自动分割方法基于Gustafson-Kessel（GK）聚类算法及其Babuska改进版本（GK-B），并采用真实正射影像进行验证。通过与原始影像及人工分割结果的对比，所获结果展现出良好前景。本研究所用正射影像对应约142公顷区域，其成果对获得"橡果饲养"认证的猪肉生产商具有重要参考价值。