Unsupervised learning (UL) has a long and successful history in untangling the complexity
of cities. As the counterpart of supervised learning, it discovers patterns from intrinsic data …

The challenges for sustainable cities to protect the environment, ensure economic growth,
and maintain social justice have been widely recognized. Along with the digitization …

Map** the distribution, pattern, and composition of urban land use categories plays a
valuable role in understanding urban environmental dynamics and facilitating sustainable …

Evidence suggests that the proportion of the human population living in cities will continue to
grow, to the point where over 90% of the worldLs population will be living in one form of city …

Identifying urban building function plays a critical role in understanding the complexness of
urban construction and improving the effectiveness of urban planning. The emergence of …

The aggregation of the same type of socio-economic activities in urban space generates
urban functional zones, each of which has one function as the main (eg, residential …

It is meaningful to analyze urban spatial structure by identifying urban subcenters, and many
methods of doing so have been proposed in the published literature. Although these …

In this paper, we present a data-driven framework to support exploratory spatial, temporal,
and statistical analysis of intra-urban human mobility. We leveraged a new mobility data …

Scene classification is a means to interpret high-resolution remote sensing (HRS) imagery,
to obtain the high-level semantic information, which can provide a reliable reference for …

Dockless bike sharing (DBS) provides a sustainable and green travel mode, which also
enhances the connections with other travel modes. Understanding the travel mobility and …