Monitoring road infrastructure from satellite images in Greater Maputo

Arianna Burzacchi (), Matteo Landrò () and Simone Vantini ()
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Arianna Burzacchi: Politecnico di Milano
Matteo Landrò: Politecnico di Milano
Simone Vantini: Politecnico di Milano

Statistical Methods & Applications, 2025, vol. 34, issue 1, No 4, 69-90

Abstract: Abstract The information about pavement surface type is rarely available in road network databases of developing countries although it represents a cornerstone of the design of efficient mobility systems. This research develops an automatic classification pipeline for road pavement which makes use of satellite images to recognize road segments as paved or unpaved. The proposed methodology is based on an object-oriented approach, so that each road is classified by looking at the distribution of its pixels in the RGB space. The proposed approach is proven to be accurate, inexpensive, and readily replicable in other cities.

Keywords: Classification; k-NN; Object-oriented; Road pavement; Maputo; Satellite images (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10260-024-00772-y

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