Analysing four decades of urban growth in Greater Khartoum, Sudan, using Earth observation data and Google Earth Engine

Rapid urbanisation associated with population growth and economic development is a key driver of changes in local and global land use and land cover (LULC). Monitoring and modelling changes that occur in LULC are crucial for promoting sustainable urban development and advancing humankind. Remote sensing has been applied worldwide to map and monitor LULC changes, although mapping of the urbanisation of Khartoum (Sudan) has not yet been done. This study detects and analyses urban growth in Greater Khartoum in five-year intervals from 1982 to 2022 using nine temporal Landsat images. The images were classified using the random forest classification algorithm. Overall accuracy and the standard kappa coefficient were applied for accuracy assessment of the classification. The overall accuracies were 81.4–91.0% and the kappa coefficient ranged from 0.70 to 0.88. The built-up area expanded from 21,621 ha in 1982 to 121,741 ha in 2022. Bare land decreased from 497,730 ha in 1982 to 379,896 ha in 2022. Agricultural areas and water body varied, but the study area underwent rapid expansion during the same period. We believe this is the first detailed study offering insight into the growth of this city. These findings contribute to strengthening the planning and management of Sudan’s largest city.

Authors

Institutions

Publication Details

Journal
Cogent Social Sciences
Published
2025-09-10
DOI
https://doi.org/10.1080/23311886.2025.2555384
Primary Topic
Impact of Light on Environment and Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysing four decades of urban growth in Greater Khartoum, Sudan, using Earth observation data and Google Earth Engine

Elhadi Adam, Ismail Abdalla Idris, Abdelgalal O. I. Abaker
2 links
Cogent Social Sciences
Impact of Light on Environment and Health
article

Analysing four decades of urban growth in Greater Khartoum, Sudan, using Earth observation data and Google Earth Engine

Elhadi Adam, Ismail Abdalla Idris, Abdelgalal O. I. Abaker
article en

Abstract

Rapid urbanisation associated with population growth and economic development is a key driver of changes in local and global land use and land cover (LULC). Monitoring and modelling changes that occur in LULC are crucial for promoting sustainable urban development and advancing humankind. Remote sensing has been applied worldwide to map and monitor LULC changes, although mapping of the urbanisation of Khartoum (Sudan) has not yet been done. This study detects and analyses urban growth in Greater Khartoum in five-year intervals from 1982 to 2022 using nine temporal Landsat images. The images were classified using the random forest classification algorithm. Overall accuracy and the standard kappa coefficient were applied for accuracy assessment of the classification. The overall accuracies were 81.4–91.0% and the kappa coefficient ranged from 0.70 to 0.88. The built-up area expanded from 21,621 ha in 1982 to 121,741 ha in 2022. Bare land decreased from 497,730 ha in 1982 to 379,896 ha in 2022. Agricultural areas and water body varied, but the study area underwent rapid expansion during the same period. We believe this is the first detailed study offering insight into the growth of this city. These findings contribute to strengthening the planning and management of Sudan’s largest city.

Cogent Social SciencesVol. 11(1)
University of the Witwatersrand (ZA), Agricultural Research Council of South Africa (ZA), King Khalid University (SA)
Openalex Percentile: Top 77%
Impact of Light on Environment and Health
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.

Analysing four decades of urban growth in Greater Khartoum, Sudan, using Earth observation data and Google Earth Engine — Elhadi Adam, Ismail Abdalla Idris, et al. · Cogent Social Sciences (2025) | TGRS Research Map | TGRS