Classifying settlement types from multi-scale spatial patterns of building footprints

Urban settlements and urbanised populations continue to grow rapidly and much of this transition is occurring in less developed countries. Remote sensing techniques are now often applied to monitor urbanisation and changes in settlement patterns. In particular, increasing availability of very high resolution imagery (<1 m spatial resolution) and computing power is enabling complete sets of settlement data in the form of building footprints to be extracted from imagery.

This work demonstrates an approach to classifying settlement types through multi-scale spatial patterns of urban morphology visible in building footprint data extracted from very high resolution imagery.

Authors Warren C Jochem, Douglas R Leasure, Oliver Pannell, Heather R Chamberlain, Patricia Jones, Andrew J Tatem
Source Environment and Planning B
Published 01 May 2020
Full publication

More publications

Microplanning: A promising approach to identify and reach zero-dose children in Democratic Republic of Congo (DRC)

This case study examines microplanning approaches as a key component in the Mashako Plan 2.0 to revitalize routine immunization strategies in the Democratic Republic of Congo (DRC).

GRID3 Impact Report 2017-2022

This impact report provides an overview of GRID3’s activities and successes during the program’s first phase, between 2017 and 2022. It highlights key milestones, achievements, and selected use cases from the Democratic Republic of the Congo, Nigeria, and Zambia. The […]

The Population Seen from Space: When Satellite Images Come to the Rescue of the Census

Great steps have been made in recent decades in observing the Earth from the sky. Landscapes and infrastructure can now be mapped at an extremely fine spatial scale. These data—particularly useful to geographers—can also benefit demographers. By combining observations of […]