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

Godwin Yeboah ORCID logo ; João Porto de Albuquerque ORCID logo ; Rafael Troilo ; Grant Tregonning ORCID logo ; Shanaka Perera ; Syed AK Shifat Ahmed ; Motunrayo Ajisola ORCID logo ; Ornob Alam ORCID logo ; Navneet Aujla ; Syed Iqbal Azam ; +40 more... Kehkashan Azeem ; Pauline Bakibinga ; Yen-Fu Chen ORCID logo ; Nazratun Nayeem Choudhury ; Peter J Diggle ORCID logo ; Olufunke Fayehun ORCID logo ; Paramjit Gill ; Frances Griffiths ORCID logo ; Bronwyn Harris ORCID logo ; Romaina Iqbal ; Caroline Kabaria ; Abdhalah Kasiira Ziraba ; Afreen Zaman Khan ; Peter Kibe ORCID logo ; Lyagamula Kisia ; Catherine Kyobutungi ; Richard J Lilford ; Jason J Madan ; Nelson Mbaya ; Blessing Mberu ; Shukri F Mohamed ORCID logo ; Helen Muir ; Ahsana Nazish ; Anne Njeri ; Oladoyin Odubanjo ; Akinyinka Omigbodun ORCID logo ; Mary E Osuh ORCID logo ; Eme Owoaje ; Oyinlola Oyebode ; Vangelis Pitidis ORCID logo ; Omar Rahman ORCID logo ; Narjis Rizvi ; Jo Sartori ; Simon Smith ; Olalekan John Taiwo ; Philipp Ulbrich ; Olalekan A Uthman ; Samuel I Watson ; Ria Wilson ; Rita Yusuf ; (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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