The last urban frontier—assessing hotspots of urban change associated with LCLUC in Africa

Urbanization is one of the leading drivers of Land Cover Land Use Change (LCLUC) globally, and African countries are at the forefront of urban expansion trends, specifically in small and medium sized cities. Multiresolution spatial datasets can be used to guide sustainable urban management and assess progress towards the U.N. Sustainable Development Goals (SDGs), specifically SDG 11.3.1 indicator (the relationship between land consumption rate and population growth rate) to track urban change. We present a two-tiered land imaging approach identifying urban change hotspots in three African countries between 2016 and 2020 and characterize urban expansion in three secondary cities that have an SDG 11.3.1 indicator ratio greater that two (Mekelle, Ethiopia; Polokwane, South Africa, Benin City, Nigeria). This ratio indicates that land consumption outpaces population growth where patterns of urban expansion include leapfrog development, infill, and corridors revealing a dynamic urban expansion that outpaces administrative boundaries. We propose a “pixels to people” approach that defines not only urban form but includes urban function in secondary cities at multiple spatial scales where fine resolution depictions and local engagement create more robust, comprehensive datasets for urban planning.

Authors

Publication Details

Journal
Frontiers in Sustainable Cities
Published
2025-02-28
DOI
https://doi.org/10.3389/frsc.2025.1529440
Citations
3
Primary Topic
Impact of Light on Environment and Health
Type
article
Field-Weighted Citation Impact
3.32
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The last urban frontier—assessing hotspots of urban change associated with LCLUC in Africa

Shahriar Shah Heydari, Melinda Laituri, Jody C. Vogeler, Melissa R. McHale et al.
3 citations
Frontiers in Sustainable Cities
Impact of Light on Environment and Health
3.32
article

The last urban frontier—assessing hotspots of urban change associated with LCLUC in Africa

Shahriar Shah Heydari, Melinda Laituri, Jody C. Vogeler, Melissa R. McHale, Orion S. E. Cardenas-Ritzert
article en
3 citations

Abstract

Urbanization is one of the leading drivers of Land Cover Land Use Change (LCLUC) globally, and African countries are at the forefront of urban expansion trends, specifically in small and medium sized cities. Multiresolution spatial datasets can be used to guide sustainable urban management and assess progress towards the U.N. Sustainable Development Goals (SDGs), specifically SDG 11.3.1 indicator (the relationship between land consumption rate and population growth rate) to track urban change. We present a two-tiered land imaging approach identifying urban change hotspots in three African countries between 2016 and 2020 and characterize urban expansion in three secondary cities that have an SDG 11.3.1 indicator ratio greater that two (Mekelle, Ethiopia; Polokwane, South Africa, Benin City, Nigeria). This ratio indicates that land consumption outpaces population growth where patterns of urban expansion include leapfrog development, infill, and corridors revealing a dynamic urban expansion that outpaces administrative boundaries. We propose a “pixels to people” approach that defines not only urban form but includes urban function in secondary cities at multiple spatial scales where fine resolution depictions and local engagement create more robust, comprehensive datasets for urban planning.

Frontiers in Sustainable CitiesVol. 7
Openalex Percentile: Top 10%
Impact of Light on Environment and Health
3.32
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.