The effects of the Maputo ring road on the quantity and quality of nearby housing

Research output: Working paperResearch

Using convolutional neural networks applied to satellite images covering a 25 km x 12 km rectangle on the northern outskirts of Greater Maputo, we detect and classify buildings from 2010 and 2018 in order to compare the development in quantity and quality of buildings from before and after construction of a major section of ring road. In addition, we analyse how the effects vary by distance to the road and conclude that the area has seen large overall growth in both quantity and quality of housing, but it is not possible to distinguish growth close to the road from general urban growth. Finally, the paper contributes methodologically to a growing strand of literature focused on combining machine-learning image recognition and the availability of highresolution satellite images. We examine the extent to which it is possible to exploit these methods to analyse changes over time and thus provide an alternative (or complement) to traditional impact analyses.
Original languageEnglish
Number of pages18
DOIs
Publication statusPublished - 2019
SeriesW I D E R. Working Papers
Number2019/111
ISSN1798-7237

    Research areas

  • Faculty of Social Sciences - Mozambique, infrastructure, housing convolutional neural networks, remote sensing, impact assessment, O18q, R14

ID: 248555972