Three-fold urban expansion in Saudi Arabia from 1992 to 2013 observed using calibrated DMSP-OLS night-time lights imagery

Alahmadi, Mohammed and Atkinson, Peter M. (2019) Three-fold urban expansion in Saudi Arabia from 1992 to 2013 observed using calibrated DMSP-OLS night-time lights imagery. Remote Sensing, 11 (19). ISSN 2072-4292

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Abstract

Although Saudi Arabia has experienced very high rates of urbanization, little interest has been given to investigating national and provincial trends in urbanization in space and time. Night-time lights satellite sensor data are considered as a suitable source of imagery for mapping urban areas across large regions. This study uses night-time lights data to analyze the spatial and temporal patterns and dynamics of urban growth in Saudi Arabia between 1992 and 2013 at the national and provincial levels. A hybrid method was applied to ensure the continuity and consistency of the Defense Meteorological Satellite Program (DMSP) Operational Line-Scan System (OLS) of stable night-time (SNT) data through time. As a result of spatial variation in the character of urban areas across Saudi Arabia, different thresholds were used to derive urban areas from the imagery. The extracted urban morphology was assessed using socio-economic data and finer resolution imagery, and accuracy assessment revealed excellent agreement. Based on the rigorous stepwise calibration analysis undertaken here, urban areas in Saudi Arabia were found to have increased three-fold between 1992 and 2013, with most of the increase concentrated in three provinces (Makkah, Riyadh and Eastern). In addition, significant variation was observed in urbanization at the provincial level. The observed high rates of urban growth are aligned with the prosperity and socio-economic development of Saudi Arabia over the last 40 years. The research shows that DMSP-OLS SNT data can provide a valuable source of information for mapping the space'time dynamics of urban growth across very large areas. Such data are required by urban and regional planners, as well as policy makers, for characterizing urban growth patterns, interpreting the drivers of such dynamics and for forecasting future growth, as well as achieving sustainable development management. © 2019 by the authors.

Item Type: Journal Article
Journal or Publication Title: Remote Sensing
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/1900
Subjects:
Departments: Faculty of Science and Technology
ID Code: 138540
Deposited By: ep_importer_pure
Deposited On: 01 Nov 2019 14:20
Refereed?: Yes
Published?: Published
Last Modified: 22 Feb 2020 05:20
URI: https://eprints.lancs.ac.uk/id/eprint/138540

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