Academic journal article Theoretical and Empirical Researches in Urban Management

Simulation and Prediction of Urban Spatial Expansion in Highly Vibrant Cities Using the Sleuth Model: A Case Study of Amman Metropolitan, Jordan

Academic journal article Theoretical and Empirical Researches in Urban Management

Simulation and Prediction of Urban Spatial Expansion in Highly Vibrant Cities Using the Sleuth Model: A Case Study of Amman Metropolitan, Jordan

Article excerpt

1. INTRODUCTION

Urbanisation refers to the social process of physical conversion of rural land into urban space as a result of population growth either due to migration or conversion of peri-urban areas into cities (United Nations, 2015; UNFPA, 2007). Urbanisation is therefore both socioeconomic and physical, although it is inclusive of land use changes, wherein areas categorised as rural become used for urban activities or constructions (Pham et al., 2011). Additionally, the 'urbanisation level' refers to the proportion of the total population residing in urban areas, expressed as a percentage; whilst the 'urbanisation rate' refers to the predicted average speed of urban population growth within a specific period (UNFPA, 2007).

Over the last 100 years, populations in developing countries have grown rapidly alongside increased urbanisation. In Jordan, large proportions of the rural population have migrated to urban areas in response to a series of significant political events and socioeconomic developments. Driven largely by the Syrian refugee crisis, Jordan has also absorbed above of 2 million new residents over the past five years. Consequently, Jordan has experienced urban growth at a faster rate than it has been equipped to cope with over the recent years. In 2014, Jordan demonstrated an annual urbanisation rate of 3.79%, with its urbanisation level rising to 83.7% (DOSJ, 2015). This has caused serious problems nationwide--for instance, scarcity of natural resources, environmental concerns, the creation of slum housing, road traffic congestion, and infrastructural pressure--due to rapid urban land growth (Al-Batoush, 2012).

Urban planners and key decision makers can only make effective decisions if they have access to the right data and forecasts regarding urban growth and land use, which necessitates continuous urban growth tracking and reporting (Cerreta and Toro, 2010). With effective and precise urbanisation modelling, effective planning and analysis can be carried out successfully (Al-shalabi et al,2012). In order to achieve accurate modelling, it is essential that the underlying methods and strategies are robust and up-to-date. Numerous statistics-based theoretical frameworks have been explored over the years, covering factors such as sociocultural patterns, economic functions, and urban geometry, for this purpose. However, such frameworks overlook spatial features, meaning that only regional economics and demographic characteristics are represented in the models built from these frameworks. Time series data gathered through the use of Digital Elevation Models (DEMs), geographic information systems (GIS) and remote sensing (RS) allow us to explore change dynamics (,Moeller, 2004), and analyse environmental changes such as hot spot changes, land use features, long-term monitoring, and land cover mapping. Spatial change analysis and modelling have therefore benefited greatly from the use of GIS and RS, and the high-quality satellite images, past spatiotemporal insights and reduced data costs they provide (Feng,2009).

Urban sprawl can be forecasted, modelled and mapped using the data provided by GIS, with remote sensing satellite images allowing for better tracking, design and execution of urban growth developments on both a temporal and spatial level. This supports sustainable development as a key element of regional planning (Bhatta, 2012). Urban research and management primarily adopts the use of remote sensing for the purpose of estimating urban growth variables (directly) and/or parameters (indirectly), as well as to map urban characteristics and regions. Using suitable remotely-sensed spatial and temporal data, GIS tools can be highly valuable given the vast body of RS imagery available; with RS itself having been found to be successful in obtaining and analysing different spatial data resolutions for the purpose of urban growth tracking. The Landsat Multispectral Scanner (Weismiller et al. …

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