Urban Land Cover Change Modelling Using Time-Series Satellite Images: A Case Study of Urban Growth in Five Cities of Saudi Arabia

Title
Urban Land Cover Change Modelling Using Time-Series Satellite Images: A Case Study of Urban Growth in Five Cities of Saudi Arabia
Publication Date
2016
Author(s)
Alqurashi, Abdullah
Kumar, Lalit
( author )
OrcID: https://orcid.org/0000-0002-9205-756X
Email: lkumar@une.edu.au
UNE Id une-id:lkumar
Sinha, Priyakant
( author )
OrcID: https://orcid.org/0000-0002-0278-6866
Email: psinha2@une.edu.au
UNE Id une-id:psinha2
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
MDPI AG
Place of publication
Switzerland
DOI
10.3390/rs8100838
UNE publication id
une:20220
Abstract
This study analyses the expansion of urban growth and land cover changes in five Saudi Arabian cities (Riyadh, Jeddah, Makkah, Al-Taif and the Eastern Area) using Landsat images for the 1985, 1990, 2000, 2007 and 2014 time periods. The classification was carried out using object-based image analysis (OBIA) to create land cover maps. The classified images were used to predict the land cover changes and urban growth for 2024 and 2034. The simulation model integrated the Markov chain (MC) and Cellular Automata (CA) modelling methods and the simulated maps were compared and validated to the reference maps. The simulation results indicated high accuracy of the MC-CA integrated models. The total agreement between the simulated and the reference maps was >92% for all the simulation years. The results indicated that all five cities showed a massive urban growth between 1985 and 2014 and the predicted results showed that urban expansion is likely to continue going for 2024 and 2034 periods. The transition probabilities of land cover, such as vegetation and water, are most likely to be urban areas, first through conversion to bare soil and then to urban land use. Integrating of time-series satellite images and the MC-CA models provides a better understanding of the past, current and future patterns of land cover changes and urban growth in this region. Simulation of urban growth will help planners to develop sustainable expansion policies that may reduce the future environmental impacts.
Link
Citation
Remote Sensing, 8(10), p. 1-24
ISSN
2072-4292
Start page
1
End page
24

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