The majority of urban inhabitants in low-and middle-income country (LMIC) cities live in
deprived urban areas. However, policy efforts and the monitoring of global goals and …

Many cities in low-and medium-income countries (LMICs) are facing rapid unplanned
growth of built-up areas, while detailed information on these deprived urban areas (DUAs) is …

Over the past two decades, there has been increasing research on the use of artificial
intelligence (AI) and geographic information technologies for monitoring and mapping …

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

In the past two decades, Earth observation (EO) data have been utilized for studying the
spatial patterns of urban deprivation. Given the scope of many existing studies, it is still …

More than 50% of the world's population lives in cities. Since this proportion is expected to
increase enormously, especially in African and Asian cities, the question of the impact on the …

Housing forms of poverty are often associated with the Global South, especially through the
depiction of slums. In this study, we systemize physical housing forms representing poverty …

Slums are a structural feature of urbanization, and shifting urbanization trends underline
their significance for the cities of tomorrow. Despite their importance, data and knowledge on …

Informal areas in the Global South are still relatively under-researched. This is partly due to
the difficulties associated with accessing these areas, especially when it comes to more …

Artificial intelligence (AI) presents opportunities to develop tools and techniques for
addressing some of the major global challenges and deliver solutions with significant social …