During the last 20 years, fast urbanization activities have been highly concentrated in just few countries (e.g., China, India, and Nigeria) and have led to the emergence of large urban aggregations, with high population density. Still, very few researches have focused on this dynamic phenomenon with a global perspective using multisource remote sensing data. In this article, combining radar and spectral sensors of different spatial resolution, a novel approach based on a novel hierarchical biclustering technique is proposed and proved to be effective in discriminating the underlying change patterns without pre-estimating the number of clusters. To this aim, experimental results focused on newly emerging megalopolis in China, India, and Nigeria, as well as on the highly urbanized and stable Lombardy region in Italy, are presented. The analysis of the results allows us to understand, in a global and comparative perspective, the spatiotemporal differentiation of urban density and how cities are changing and evolving in the building volume and, to some extent, their economic level.
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