Abstract. Nearshore bars are important coastal features that influence beach–dune dynamics and protect the coast from high-energy wave events. Historically, in situ methods were used to study beach–dune dynamics and nearshore bars. Video monitoring systems, such as Argus, have been the favored remote sensing approach for studying nearshore bars dynamics and evolution. These systems are costly to install and maintain, and a limited number of stations are available. Our study introduces a lower cost alternative to study these coastal features. A rule-based classification object-based image analysis approach is introduced to identify nearshore bars (and their characteristics, such as bar length, width, count, and distance from the wet/dry line) from very-high-resolution (VHR) multispectral imagery. Nearshore bars were successfully identified and characterized as single and multiple bar systems. Our study demonstrates that VHR satellite remote sensing is a viable alternative with comparative results to video monitoring systems. Their capability of acquiring high-resolution imagery in large spatial extent is superior in continuous observation and characterization of nearshore bars. The proposed approach provides information at a more relevant spatiotemporal scale at which these systems evolve, which is helpful to coastal scientists and managers.

中文翻译：

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将基于规则的基于对象的图像分析方法应用于近岸钢筋识别和表征

摘要。近岸酒吧是重要的海岸特征，影响海滩-沙丘动态并保护海岸免受高能波浪事件的影响。历史上，原位方法用于研究海滩-沙丘动力学和近岸酒吧。视频监控系统，如 Argus，一直是研究近岸酒吧动态和演化的首选遥感方法。这些系统的安装和维护成本很高，而且可用的站点数量有限。我们的研究引入了一种低成本的替代方法来研究这些沿海特征。引入了基于规则的分类基于对象的图像分析方法，以从超高分辨率 (VHR) 多光谱中识别近岸条带（及其特性，例如条带长度、宽度、计数和与湿/干线的距离）意象。近岸钢筋被成功识别并表征为单个和多个钢筋系统。我们的研究表明，VHR 卫星遥感是一种可行的替代方案，其结果可与视频监控系统进行比较。它们在大空间范围内获取高分辨率图像的能力在近岸酒吧的连续观察和表征方面具有优越性。提议的方法以更相关的时空尺度提供这些系统发展的信息，这对沿海科学家和管理人员很有帮助。它们在大空间范围内获取高分辨率图像的能力在近岸酒吧的连续观察和表征方面具有优越性。提议的方法以更相关的时空尺度提供这些系统发展的信息，这对沿海科学家和管理人员很有帮助。它们在大空间范围内获取高分辨率图像的能力在近岸酒吧的连续观察和表征方面具有优越性。提议的方法以更相关的时空尺度提供这些系统发展的信息，这对沿海科学家和管理人员很有帮助。