Today satellite images are mostly exploited automatically due to advances in image classification methods. Manual visual image interpretation (MVII), however, still plays a significant role e.g., to generate training data for machine-learning algorithms or for validation purposes. In certain urban environments, however, of e.g., highest densities and structural complexity, textural and spectral complications in overlapping roof-structures still demand the human interpreter if one aims to capture individual building structures. The cognitive perception and real-world experience are still inevitable. Against these backgrounds, this article aims at quantifying and interpreting the uncertainties of mapping rooftop footprints of such areas. We focus on the agreement among interpreters and which aspects of perception and elements of image interpretation affect mapping. Ten test persons digitized six complex built-up areas. Hereby, we receive quantitative information about spatial variables of buildings to systematically check the consistency and congruence of results. An additional questionnaire reveals qualitative information about obstacles. Generally, we find large differences among interpreters’ mapping results and a high consistency of results for the same interpreter. We measure rising deviations correlate with a rising morphologic complexity. High degrees of individuality are expressed e.g., in time consumption, in-situ- or geographic information system (GIS)-precognition whereas data source mostly influences the mapping procedure. By this study, we aim to fill a gap as prior research using MVII often does not implement an uncertainty analysis or quantify mapping aberrations. We conclude that remote sensing studies should not only rely unquestioned on MVII for validation; furthermore, data and methods are needed to suspend uncertainty.

中文翻译：

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复杂城市环境下视觉图像解读中人类感知的不确定性

今天，由于图像分类方法的进步，卫星图像大多被自动利用。然而，手动视觉图像解释 (MVII) 仍然发挥着重要作用，例如，为机器学习算法或验证目的生成训练数据。然而，在某些城市环境中，例如，最高密度和结构复杂性、重叠屋顶结构中的纹理和光谱复杂性仍然需要人工翻译，如果一个人的目标是捕捉单个建筑结构。认知感知和现实世界的体验仍然是不可避免的。在这些背景下，本文旨在量化和解释绘制此类区域屋顶足迹的不确定性。我们专注于解释者之间的一致性以及图像解释的哪些方面和元素会影响映射。十名测试人员将六个复杂的建成区数字化。因此，我们接收有关建筑物空间变量的定量信息，以系统地检查结果的一致性和一致性。额外的问卷揭示了关于障碍的定性信息。通常，我们发现解释器的映射结果之间存在很大差异，并且同一解释器的结果一致性很高。我们测量上升的偏差与上升的形态复杂性相关。例如，在时间消耗、原位或地理信息系统 (GIS) 预知方面表现出高度的个性化，而数据源主要影响制图过程。通过这项研究，我们的目标是填补一个空白，因为使用 MVII 的先前研究通常没有实施不确定性分析或量化映射像差。我们得出的结论是，遥感研究不仅应该毫无疑问地依赖 MVII 进行验证；此外，需要数据和方法来暂停不确定性。