The development of information and communication technologies has produced massive human sensing data sets, such as point of interest, mobile phone data, and social media data sets. These data sets provide alternative human perceptions of urban spaces; therefore, they have become effective supplements for remote sensing tasks. This letter presents an exploratory framework to examine the scale effect of fusing remote sensing and human sensing. The physical and social semantics are extracted from raw remote sensing images and human sensing data, respectively. A dynamic weighting strategy is developed to explore the fusion of remote sensing and human sensing. Taking urban function inference as an example, the scale effect is evaluated by weighting remote sensing and human sensing. The experiment demonstrates that fusing remote sensing and human sensing enables us to recognize multiple types of urban functions. Meanwhile, the results are significantly affected by the scale.

中文翻译：

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融合遥感和人类感知以描绘城市功能的尺度效应

信息通信技术的发展产生了海量的人类感知数据集，如兴趣点、手机数据和社交媒体数据集。这些数据集提供了人类对城市空间的不同看法；因此，它们已成为遥感任务的有效补充。这封信提出了一个探索性框架来检查融合遥感和人类感知的规模效应。物理语义和社会语义分别从原始遥感图像和人类感知数据中提取。开发了一种动态加权策略来探索遥感和人类感知的融合。以城市功能推断为例，通过加权遥感和人类感知来评估尺度效应。实验表明，融合遥感和人类感知使我们能够识别多种类型的城市功能。同时，结果受量表的影响显着。