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Building on sustainable development goal indicator 11.3.1. for improved utility and guidance

Abstract

The increased production of broad-coverage spatial datasets and investigation of these datasets by spatial analysis techniques allows for consistent examinations of urbanization patterns across the globe. Spatial data and analyses have proven valuable for sustainable urban development initiatives, including Sustainable Development Goal (SDG) 11 under the United Nation's 2030 Agenda for Sustainable Development. SDG Indicator 11.3.1 is a geospatially measured indicator implemented under SDG 11 for monitoring rates of urban expansion and population growth in a specific area over a period of time. Current methodological approaches and data inputs may hinder the application of SDG Indicator 11.3.1 at certain scales and extents. The overarching goal of this research is to build on the utility of SDG Indicator 11.3.1 by enhancing an existing urban delineation method for automated function, examining urban change at the urban agglomeration level across broad extents, highlighting hotspots of SDG Indicator 11.3.1, and evaluating the impacts of the spatial resolution of data inputs on SDG Indicator 11.3.1 and related outputs. In Chapter 1, we advanced an existing urban delineation method for the automatic identification of individual urban agglomerations across broad extents. We accomplished this by integrating various open-source datasets and tools with spatial analysis techniques. We used this methodology to examine SDG Indicator 11.3.1 and additional urban change metrics for urban agglomerations in Ethiopia, Nigeria, and South Africa over the 2016 to 2020 period. In Chapter 2, we applied our delineation methodology and examined the influence of spatial resolution of land use data on urban delineation, urban change metrics, and urban related land use change in Ethiopia over the 2016 to 2020 period. The results of Chapter 1 revealed trends of urban change and highlighted hotspots of SDG Indicator 11.3.1 at multiple levels across the three African countries. Chapter 2 revealed the implications of using varied spatial resolutions of land use maps when delineating urban areas, assessing SDG Indicator 11.3.1 and other urban change metrics, and examining urbanization-driven land use change.

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