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On the potential of Google Street View for environmental waste quantification in urban Africa: an assessment of bias in spatial coverage

On the potential of Google Street View for environmental waste quantification in urban Africa: an assessment of bias in spatial coverage
On the potential of Google Street View for environmental waste quantification in urban Africa: an assessment of bias in spatial coverage
Mismanaged domestic waste threatens ecosystem health, with substantial increases predicted from developing country cities if current consumption and waste service collection trends continue. Google Street View (GSV) imagery has been used to quantify urban environmental waste in high-income countries. GSV availability is increasing elsewhere, but its coverage is variable. This study aims to evaluate bias in spatiotemporal GSV coverage relative to environmental waste in two case study cities. An environmental survey measured environmental waste in Greater Accra, Ghana and Kisumu, Kenya via 95 and 81 transects, respectively. Six summary metrics of environmental waste were calculated and compared for transects with full, partial, and no GSV coverage via multi-level regression. Multi-level regression indicated no significant differences in scattered waste density for transects with versus without GSV coverage. However, both cities had significantly lower waste burning densities along transects with GSV coverage (4.3 versus 24.2 burning sites/Ha in Kisumu; 1.7 versus 13.6 sites/Ha for Greater Accra) compared to those without Street View density of large waste piles was significantly lower in Kisumu transects with Street View coverage (1.4 versus 11.5 sites/Ha). Because of partial imagery coverage, GSV imagery analysis is likely to under-estimate waste indicators such as waste burning density. Future studies using GSV to quantify waste indicators in African cities should therefore correct for coverage bias.
Africa, mapping, municipal waste management, neighbourhood analysis, slum
2765-8511
Umar, Farouk
da34c47c-ab2f-4e68-8399-48591271e415
Amoah, Josephine
b87ccf3b-1009-48ad-9851-2ad371cdef29
Asamaoh, Moses
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Dzodzomenyo, Mawuli
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Igwenagu, Chidinma
f4e50fa4-7d52-45f1-89af-d04fd2660b0f
Okotto, Lorna-Grace
d2883684-8b63-4adb-abf0-088868d52cbd
Okotto-Okotto, Joseph
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Shaw, Peter
935dfebf-9fb6-483c-86da-a21dba8c1989
Wright, Jim
94990ecf-f8dd-4649-84f2-b28bf272e464
Bloor, Michelle
5ea3e3c8-b209-4ddb-96f7-d2fa20012682
Umar, Farouk
da34c47c-ab2f-4e68-8399-48591271e415
Amoah, Josephine
b87ccf3b-1009-48ad-9851-2ad371cdef29
Asamaoh, Moses
d35c2cf2-9df1-4a5d-acdc-398af510d293
Dzodzomenyo, Mawuli
f7969c6b-5999-448b-befa-e1c2e0287895
Igwenagu, Chidinma
f4e50fa4-7d52-45f1-89af-d04fd2660b0f
Okotto, Lorna-Grace
d2883684-8b63-4adb-abf0-088868d52cbd
Okotto-Okotto, Joseph
4f7216e9-6a2d-408f-948c-3767bae1bf67
Shaw, Peter
935dfebf-9fb6-483c-86da-a21dba8c1989
Wright, Jim
94990ecf-f8dd-4649-84f2-b28bf272e464
Bloor, Michelle
5ea3e3c8-b209-4ddb-96f7-d2fa20012682

Umar, Farouk, Amoah, Josephine, Asamaoh, Moses, Dzodzomenyo, Mawuli, Igwenagu, Chidinma, Okotto, Lorna-Grace, Okotto-Okotto, Joseph, Shaw, Peter and Wright, Jim , Bloor, Michelle (ed.) (2023) On the potential of Google Street View for environmental waste quantification in urban Africa: an assessment of bias in spatial coverage. Sustainable Environment, 9 (1), [2251799]. (doi:10.1080/27658511.2023.2251799).

Record type: Article

Abstract

Mismanaged domestic waste threatens ecosystem health, with substantial increases predicted from developing country cities if current consumption and waste service collection trends continue. Google Street View (GSV) imagery has been used to quantify urban environmental waste in high-income countries. GSV availability is increasing elsewhere, but its coverage is variable. This study aims to evaluate bias in spatiotemporal GSV coverage relative to environmental waste in two case study cities. An environmental survey measured environmental waste in Greater Accra, Ghana and Kisumu, Kenya via 95 and 81 transects, respectively. Six summary metrics of environmental waste were calculated and compared for transects with full, partial, and no GSV coverage via multi-level regression. Multi-level regression indicated no significant differences in scattered waste density for transects with versus without GSV coverage. However, both cities had significantly lower waste burning densities along transects with GSV coverage (4.3 versus 24.2 burning sites/Ha in Kisumu; 1.7 versus 13.6 sites/Ha for Greater Accra) compared to those without Street View density of large waste piles was significantly lower in Kisumu transects with Street View coverage (1.4 versus 11.5 sites/Ha). Because of partial imagery coverage, GSV imagery analysis is likely to under-estimate waste indicators such as waste burning density. Future studies using GSV to quantify waste indicators in African cities should therefore correct for coverage bias.

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On the potential of Google Street View for environmental waste quantification in urban Africa An assessment of bias in spatial coverage - Version of Record
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Accepted/In Press date: 21 August 2023
e-pub ahead of print date: 31 August 2023
Additional Information: Funding Information: This research was funded through a UKRI Collective Fund award via the Global Challenges Research Fund (ref: ES/T008121/1). The support of the UK Economic and Social Research Council (ESRC) is gratefully acknowledged. The study sponsor had no involvement in the study design collection analysis and interpretation of data, writing of the report and decision to submit the paper.
Keywords: Africa, mapping, municipal waste management, neighbourhood analysis, slum

Identifiers

Local EPrints ID: 481565
URI: http://eprints.soton.ac.uk/id/eprint/481565
ISSN: 2765-8511
PURE UUID: 748db3d6-56e3-4b4e-9aef-1520e6132ba3
ORCID for Farouk Umar: ORCID iD orcid.org/0000-0001-9613-2857
ORCID for Peter Shaw: ORCID iD orcid.org/0000-0003-0925-5010
ORCID for Jim Wright: ORCID iD orcid.org/0000-0002-8842-2181

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Date deposited: 01 Sep 2023 17:14
Last modified: 06 Jun 2024 02:13

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Contributors

Author: Farouk Umar ORCID iD
Author: Josephine Amoah
Author: Moses Asamaoh
Author: Mawuli Dzodzomenyo
Author: Chidinma Igwenagu
Author: Lorna-Grace Okotto
Author: Joseph Okotto-Okotto
Author: Peter Shaw ORCID iD
Author: Jim Wright ORCID iD
Editor: Michelle Bloor

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