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Managing, assessing and monitoring urban sprawl using remote sensing; change detection, urban expansion intensity index (ueii), and shannon entropy: a case study of amman city, jordan (1990–2022)

Journal of Southwest Jiaotong University(2022)

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Abstract
Mapping and monitoring of land use land cover (LULC) changes in Amman city are important for sustainable regional development, urban planning, and environmental and land use management. To comprehend the temporal and the spatial variability of LULC change, six time-period satellite images of the study area have been examined based on remote sensing (RS) and geographic information system (GIS) techniques. The changes in LULC patterns of Amman city were monitored for the periods 1990-1995, 1995-1999, 1999-2004, 2004-2013, 2013-2017 and 2017-2022. Employing Spatio-temporal Landsat TM and ETM imagery acquired from 1990 to 2022 to comprehend, detect, and quantify the spatial pattern of urban sprawl. Supervised classification was used to extract built-up areas and measure changes in urban land-use class across the metropolis. The result of the urban expansion intensity index shows that urban expansion hits its peak between 2013 and 2017, with a 1.75 index resulting in high-speed development between the time frames. Shannon’s entropy approach was quantified to detect the urban sprawl phenomenon. The results showed that the Relative Shannon entropy values are above 0.5, indicating dispersedly spread-urban sprawl. Land Absorption Coefficient (LAC) and Land Consumption Ratio (LCR) were also used. A strong positive correlation between road networks and urban sprawl (0.7) indicates that urbanization plays a major role in the occurrence of urban sprawl. The findings obtained from this work would provide urban planners and decision-makers in Amman the tools and data they need, to implement planning interventions for sustainable future development and to mitigate the impacts of urban sprawl on different aspects on the environment.
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Key words
monitoring urban sprawl,urban expansion intensity index,remote sensing,,amman city,change detection
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