Analysis of OpenStreetMap Data Quality at Different Stages of a Participatory Mapping Process: Evidence from Slums in Africa and Asia

Yeboah, GodwinORCID logo; Porto de Albuquerque, JoãoORCID logo; Troilo, Rafael; Tregonning, GrantORCID logo; Perera, Shanaka; Ahmed, Syed AK Shifat; Ajisola, MotunrayoORCID logo; Alam, OrnobORCID logo; Aujla, Navneet; Azam, Syed Iqbal; +40 more...Azeem, Kehkashan; Bakibinga, Pauline; Chen, Yen-FuORCID logo; Choudhury, Nazratun Nayeem; Diggle, Peter JORCID logo; Fayehun, OlufunkeORCID logo; Gill, Paramjit; Griffiths, FrancesORCID logo; Harris, BronwynORCID logo; Iqbal, Romaina; Kabaria, Caroline; Ziraba, Abdhalah Kasiira; Khan, Afreen Zaman; Kibe, PeterORCID logo; Kisia, Lyagamula; Kyobutungi, Catherine; Lilford, Richard J; Madan, Jason J; Mbaya, Nelson; Mberu, Blessing; Mohamed, Shukri FORCID logo; Muir, Helen; Nazish, Ahsana; Njeri, Anne; Odubanjo, Oladoyin; Omigbodun, AkinyinkaORCID logo; Osuh, Mary EORCID logo; Owoaje, Eme; Oyebode, Oyinlola; Pitidis, VangelisORCID logo; Rahman, OmarORCID logo; Rizvi, Narjis; Sartori, Jo; Smith, Simon; Taiwo, Olalekan John; Ulbrich, Philipp; Uthman, Olalekan A; Watson, Samuel I; Wilson, Ria; and Yusuf, Rita (2021) Analysis of OpenStreetMap Data Quality at Different Stages of a Participatory Mapping Process: Evidence from Slums in Africa and Asia. ISPRS International Journal of Geo-Information, 10 (4). p. 265. DOI: 10.3390/ijgi10040265
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This paper examines OpenStreetMap data quality at different stages of a participatory mapping process in seven slums in Africa and Asia. Data were drawn from an OpenStreetMap-based participatory mapping process developed as part of a research project focusing on understanding inequalities in healthcare access of slum residents in the Global South. Descriptive statistics and qualitative analysis were employed to examine the following research question: What is the spatial data quality of collaborative remote mapping achieved by volunteer mappers in morphologically complex urban areas? Findings show that the completeness achieved by remote mapping largely depends on the morphology and characteristics of slums such as building density and rooftop architecture, varying from 84% in the best case, to zero in the most difficult site. The major scientific contribution of this study is to provide evidence on the spatial data quality of remotely mapped data through volunteer mapping efforts in morphologically complex urban areas such as slums; the results could provide insights into how much fieldwork would be needed in what level of complexity and to what extent the involvement of local volunteers in these efforts is required.


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