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 sen...
| Publicado en: | Cogent Social Sciences Vol. 11; no. 1; pp. 1 - 20 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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Taylor & Francis Ltd
Dec2025
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=190433546&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 190433546 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 23311886 JX4W jtl: Cogent Social Sciences issn: 23311886 maglogo: N pubinfo: dt: Dec2025 vid: 11 iid: 1 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 190433546 10.1080/23311886.2025.2555384 ppf: 1 ppct: 19 formats: tig: atl: Analysing four decades of urban growth in Greater Khartoum, Sudan, using Earth observation data and Google Earth Engine. aug: au: Abdalla Idris, Ismail Adam, Elhadi Abubakr Ali Abutaleb, Khaled O. I. Abaker, Abdelgalal affil: School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg, South Africa Geo-Information Division, Agricultural Research Council-Natural Resource and Engineering (ARC-NRF), Pretoria, South Africa Applied College, King Khalid University, Khamis Mushait, Saudi Arabia su: Khartoum (Sudan) Sudan Urban growth Cities & towns Sustainable development Remote sensing Landsat satellites Geographic information systems sug: subj: Urban growth Cities & towns Sustainable development Khartoum (Sudan) Sudan Land Subdivision Administration of General Economic Programs Remote sensing Landsat satellites Geographic information systems keyword: change detection Khartoum Landsat random forest Urban expansion change detection Khartoum Landsat random forest Urban expansion ab: 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. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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