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 visual landscape plays a pivotal role in urban planning and healthy cities. Recent
studies of visual evaluation focus on either objective or subjective approach, while …

This paper presents the notion of spatial signatures as a characterisation of space based on
form and function designed to understand urban environments. The spatial configuration of …

Background Household survey data are frequently used to measure reproductive, maternal,
newborn, child and adolescent health (RMNCAH) service utilisation in low and middle …

Cities are complex products of human culture, characterised by a startling diversity of visible
traits. Their form is constantly evolving, reflecting changing human needs and local …

The national census is an essential data source to support decision-making in many areas
of public interest. However, this data may become outdated during the intercensal period …

The automatic classification of urban functional regions is vital for urban planning and
governance. The current methods mainly rely on single remote sensing image data or social …

The recent growth of geographic data science (GDS) fuelled by increasingly available open
data and open source tools has influenced urban sciences across a multitude of fields. Yet …

Most earth observation (EO) approaches only yield a binary delineation of deprived/non-
deprived areas–an oversimplified characterisation with little information inferred regarding …

Most studies of urban morphology rely on morphometrics, such as building area and street
length. However, these methods often fall short in capturing visual patterns that carry …