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Beach hydromorphological classification through image classification techniques applied to remotely sensed data

机译：通过应用于遥感数据的图像分类技术对海滩水形态进行分类

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摘要

Evaluation of beach hydromorphological behavior and its classification is extremely complex. Several aerial photographs, using visual interpretation on a GIS environment, were previously used on the identification of coastal hydroforms and hydromorphologies, and to classify beach morphological stage in a selected area of the NW Portuguese coast. The goal of this study is to improve and develop new methodologies to identify coastal features and coastal patterns. In order to achieve that, pixel-based classification and object-oriented classification algorithms were employed, with the aim to identify and analyze morphological features and hydrodynamic patterns and to compare these results with the visual interpretation already performed. The dataset is composed by two aerial photographs (1996 and 2001) and one IKONOS-2 image (2004). The supervised classification algorithms presented good results both for aerial photographs and for IKONOS-2 image, demonstrated by its overall accuracy and Kappa coefficient values. For the two aerial photographs the best results were found for the maximum likelihood classifier and for the IKONOS-2 image the best result was archived with the parallelepiped classifier. The object-oriented classification performance for the aerial photographs was very good, identifying the classes of interest. The results obtained with the IKONOS-2 image were worst.
机译：对海滩水形态行为及其分类的评估非常复杂。以前，在GIS环境中使用了视觉解释的几张航拍照片被用于识别沿海水形和水形，并对葡萄牙西北海岸选定区域的海滩形态阶段进行分类。这项研究的目的是改善和发展新的方法论，以识别沿海特征和沿海格局。为了实现这一点，采用了基于像素的分类和面向对象的分类算法，目的是识别和分析形态特征和流体动力学模式，并将这些结果与已经进行的视觉解释进行比较。该数据集由两张航空照片（1996年和2001年）和一张IKONOS-2图像（2004年）组成。监督分类算法在航空照片和IKONOS-2图像上均显示出良好的结果，其总体准确性和Kappa系数值证明了这一点。对于两张航空照片，找到了最大似然分类器的最佳结果，对于IKONOS-2图像，使用平行六面体分类器存储了最佳结果。航空照片的面向对象分类性能非常好，可以识别感兴趣的类别。用IKONOS-2图像获得的结果最差。

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