Automated Geospatial Approach for Assessing SDG Indicator 11.3.1

A Multi-Level Evaluation of Urban Land Use Expansion across Africa

Bibliographic Data

ID22034828
AuthorsOrion S E Cardenas-Ritzert (0009-0000-2530-2206, Colorado State University, corresponding author), Jody C Vogeler (0000-0002-3639-8984, Colorado State University), Shahriar Shah Heydari (0009-0005-2151-0928, Colorado State University), Patrick A Fekety (0009-0003-3225-2464, Colorado State University), Melinda Laituri (0000-0002-2268-6774, Colorado State University), Melissa R Mchale (0000-0001-7300-2988, University of British Columbia)
Year2024
Volume13
Issue7
Pages226
Publication date2024-06-28
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi13070226
OpenAlexW4400119922
LanguageEN
Citations received3
References cited37

Geospatial data has proven useful for monitoring urbanization and guiding sustainable development in rapidly urbanizing regions. The United Nations’ (UN) Sustainable Development Goal (SDG) Indicator 11.3.1 leverages geospatial data to estimate rates of urban land and population change, providing insight on urban land use expansion patterns and thereby informing sustainable urbanization initiatives (i.e., SDG 11). Our work enhances a UN proposed delineation method by integrating various open-source datasets and tools (e.g., OpenStreetMap and openrouteservice) and advanced geospatial analysis techniques to automate the delineation of individual functional urban agglomerations across a country and, subsequently, calculate SDG Indicator 11.3.1 and related metrics for each. We applied our automated geospatial approach to three rapidly urbanizing countries in Africa: Ethiopia, Nigeria, and South Africa, to conduct multi-level examinations of urban land use expansion, including identifying hotspots of SDG Indicator 11.3.1 where the percentage growth of urban land was greater than that of the urban population. The urban agglomerations of Ethiopia, Nigeria, and South Africa displayed a 73%, 14%, and 5% increase in developed land area from 2016 to 2020, respectively, with new urban development being of an outward type in Ethiopia and an infill type in Nigeria and South Africa. On average, Ethiopia’s urban agglomerations displayed the highest SDG Indicator 11.3.1 values across urban agglomerations, followed by those of South Africa and Nigeria, and secondary cities of interest coinciding as SDG Indicator 11.3.1 hotspots included Mekelle, Ethiopia; Benin City, Nigeria; and Polokwane, South Africa. The work presented in this study contributes to knowledge of urban land use expansion patterns in Ethiopia, Nigeria, and South Africa, and our approach demonstrates effectiveness for multi-level evaluations of urban land expansion according to SDG Indicator 11.3.1 across urbanizing countries

Cartography · Civil engineering · Economic geography · Economic growth · Environmental health · Environmental planning · Environmental resource management · Geography · Geospatial analysis · Land use · Political science · Population · Sustainable development · Urban agglomeration · Urban planning · Urbanization · Engineering · Environmental Science · Land Use and Ecosystem Services · Urban and Rural Development Challenges · Urban Transport and Accessibility

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