We present a novel approach for estimating the proportional distributions of function types
(ie functional distributions) in an urban area through learning semantics preserved …

Assigning detailed use categories to buildings is a challenging and relevant task in urban
land use classification with applications in urban planning, digital city modelling and …

Points-of-interests (POIs) have been proven to be indicative for sensing urban land use in
numerous studies. However, recent progress mainly relies on spatial co-occurrence patterns …

The diversification of business forms leads to functional and spatial complexity in cities. The
efficient determination of the complexity of an urban system is the basis for the scientific …

Monitoring and understanding urban development requires up-to-date information on
multiple urban land-use classes. Manual classification and deep learning approaches …

As the most important manifestation of the activities of the life service industry, the
reasonable layout of spatial agglomeration and dispersion of the accommodation and …

The past decade has witnessed the increasingly created point-of-interest (POI) data, which
are utilized to express the semantics of places. To understand the POI semantics, current …

Analyzing the spatial agglomeration and characteristics of urban functional elements and
effectively identifying the polycentric pattern of a city can provide a scientific basis for urban …

Human trajectories have explicit linkages to urban dynamics and functions. Therefore,
learning urban region representations from human trajectories could help understand cities …

Dynamic traffic flow, which can facilitate the efficient operation of traffic road networks, is an
important prerequisite for the application of reasonable assignment of traffic demands in an …