A way to use GIS (incl. geomasking) to understand homelessness: a focus on the spatial characteristics of and around sleeping locations of the homeless in Cape Town City Bowl

Background: The homeless individuals/groups are the most vulnerable and less dignified member of the society. The evidences lie in the nature of their sleeping locations in the urban spaces, amongst other aspects. An internationally unique and integrated approach (GIS/socio-spatial) is utilized to enhance the knowledge and understanding of homelessness through analyzing the spatial characteristics of and around the sleeping locations of the homeless community in the urban public spaces, Cape Town City Bowl (South Africa) case study. Data Source and Method: Through the quantitative approach, the individual sleeping locations of The Homeless, including their surrounding characteristics, are observed daily for two weeks, 13-26 Oct. 2018 (total of all locations: n = 9515, daily average, n = 680) between 06:00 am and 08:30am. The analyses entail sequential application of eight analytical methods; spatial distribution, attribute analysis, proximity analysis, weather analysis, and obfuscation/geographic masking Results: (a) The daily individual sleeping locations of the homeless individuals and groups increase over time but their geographic distributions are similar or display insignificant/little variations. (b) Majority of these locations are situated in marginalized urban spaces that deny The Homeless personal privacy/security, human dignity and perpetuate stigmatization and social isolation. (c) The sleeping locations of The Homeless are far from the sources of basic needs to enhance their livelihoods (e.g., water resources). (d) Although more data is needed, however, the limited data in this research show that weather conditions are (in)directly related to the changes in the numbers of sleeping locations. (d) The voronoi masking and weight rand perturbation are best presenting the sleeping location of The Homeless without compromising the spatial confidence of The Homeless, and the spatial distributions/patterns of these locations. Conclusion: GIS (geographic information system) is capable of enhancing the knowledge and understanding of homelessness, and therefore, it can inform establishments and improvements of initiatives/measures that seek to reduce the vulnerability of the homeless community and/or integrate them with the public community, especial in the urban spaces