In this commentary, we describe the current state of the art of points of interest (POIs) as
digital, spatial datasets, both in terms of their quality and affordings, and how they are used …

Self-supervised representation learning (SSRL) concerns the problem of learning a useful
data representation without the requirement for labelled or annotated data. This …

POI configuration of a region indicates a combination of POI counts on various types inside
the region. Exploring POI configurations of urban regions facilitates to understand their …

When various urban functions are integrated into one location, they form a mixture of
functions. The emerging big data promote an alternative way to identify mixed functions …

Population spatialization is widely used for spatially downscaling census population data to
finer-scale. The core idea of modern population spatialization is to establish the association …

Urban functional regions are essential information in parsing urban spatial structure. The
rapid and accurate identification of urban functional regions is important for improving urban …

The task of identifying similar regions within and between cities is an important aspect of
urban data science as well as applied domains such as real estate, tourism, and urban …

Points-of-interest (POIs) are an important carriers of location text information in smart cities
and have been widely used to extract and identify urban functional regions. However, it is …

Anthropogenic interferences through various intensive social-economic activities within
construction land have induced and strengthened the Urban Heat Island (UHI) effects in …

Whenever companies plan to enter new geographical areas, they need disaggregated sales
in each location. To make such predictions, sales time series or final customers' data in …