Description

As it is reported for the SDG indicator 11.1.1 and according to UN-Habitat the number of urban population living in slums, informal settlements or inadequate housing is around one billion [1,2]. However, for many countries, such statistics are either not available or not possible to obtain with conventional methods. For example, inadequate housing is defined as the percentage the household spends on housing, with a threshold of 30%, however data on this indicator are typical, if available at, only available as an aggregated estimate which does not allow to show city-level variations. The housing issue is not only a problem related to an economic perspective but also a livelihood issue that can affect social stability. Areas as slums, informal settlement and inadequate housing are very dynamic places in terms of their physical dynamic as well as socio-economic dynamic. For the physical dynamic, most studies, if done at all, only analyse the expansion but not densification nor vertical development processes. For the socio-economic dynamics, the issue of affordability is not well captured in its spatial dimension. Therefore, building a 3D model of such areas will provide critical information for housing management, policy-making and economic analysis.
There is recent research on using Remote Sensing data and innovative methods such as deep learning for estimations related to deprivation or housing in the slums [3-7]. However, research for slums including vertical dimension (3D) in this respect has not been done. With the increasing population and urbanization the only option for many cities is to grow in a vertical dimension. However, many factors related to property valuation and taxation have to be considered in relation to this which for slum areas are completely missing. Therefore, with this research topic, we aim in an investigation of 3D factors that need to be taken into account physical and socio-economic processes and 3D visualisation and analysis of this factors using Remote Sensing data and 3D modelling.

Objectives and Methodology

• Research the available Earth Observation and open data that would allow building a 3D model
• Investigate 3D factors that should affect the physical and socio-economic dynamics in slum areas
• Propose a framework for analysing the spatial patterns of affordability based on the findings of the research

Further reading

https://library.itc.utwente.nl/papers_2019/msc/la/li.pdf; https://library.itc.utwente.nl/papers_2019/msc/la/ying.pdf; https://library.itc.utwente.nl/papers_2019/msc/upm/zhang.pdf