Nowadays, cities are the most relevant type of human settlement and their population has been endlessly growing for decades. At the same time, we are witnessing an explosion of digital data that capture many different aspects and details of city life. This allows detecting human mobility patterns in urban areas with more detail than ever before. In this context, based on the fusion of mobility data from different and heterogeneous sources, such as public transport, transport‐network connectivity and Online Social Networks, this study puts forward a novel approach to uncover the actual land use of a city. Unlike previous solutions, our work avoids a time‐invariant approach and it considers the temporal factor based on the assumption that urban areas are not used by citizens all the time in the same manner. We have tested our solution in two different cities showing high accuracy rates.

中文翻译：

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基于异构移动源的土地利用动态发现

如今，城市是最相关的人类住区类型，其人口数十年来一直在不断增长。与此同时，我们正在目睹数字数据的爆炸式增长，这些数据捕捉到了城市生活的许多不同方面和细节。这允许比以往任何时候都更详细地检测城市地区的人员流动模式。在此背景下，本研究基于融合来自不同和异构来源（例如公共交通、交通网络连接和在线社交网络）的移动数据，提出了一种揭示城市实际土地使用情况的新方法。与以前的解决方案不同，我们的工作避免了时间不变的方法，它基于城市地区不会一直以相同的方式被市民使用的假设来考虑时间因素。