Since the late 20th century, urbanization has become one of the leading anthropogenic activities transforming the Earth’s surface and consuming agricultural land; by 2000 about 88% of these areas were destroyed by urban conversion [1
]. Cities are home to more than 54% of the world’s population, and by 2050 this percentage is expected to reach 66% [4
]. To provide a favorable-living environment and housing units for the growing population, cities have rapidly grown beyond their peripheries, mostly on the primary agricultural lands [5
]. A low-intensity urban sprawl pattern has evolved as the reliance on the automobile and the desire for suburban living increase. The spatial extent of urban areas worldwide is expanding twice as fast as their population [6
Although urban sprawl was first recognized as an American phenomenon, it has become global with different levels of adaptations between and among the high and low-income countries [8
]. High-income countries have demonstrated better adaptation policies (i.e., compact planning policies and zoning policies) to minimize the negative impacts of sprawl, especially on primary farmlands and valuable soils [11
]. However, low-income countries struggle with sprawl as their urban population increases at rates much higher than their economic development rate [14
]. In these countries, urbanization governance lacks sustainable planning strategies while neglecting available natural resources (i.e., soils, physiography, and vegetation) as a baseline for land management and land-use conversion [21
]. As a result, consumption of farmland for urbanization has had profound impacts on the food security of low-income countries [23
] and has become a grand challenge, especially for the poorer countries suffering from scarcity of natural resources.
To properly manage and track land conversions and urban encroachment on primary lands it is critical to map urban dynamics over a long time and forecast future urban development under certain exclusion variables using spatially explicit models such as Cellular Automata (CA) urban growth models. They are a good example of the most popular models in urban mapping due to their capabilities for viewing urban areas as dynamic environments featuring the complex processes embedded within urban systems [24
]. Such models can avoid many shortcomings of traditional urban growth models due to their base of the cell, state, neighborhood, and transition rules [26
]. The SLEUTH (Slope, Land cover, Exclusion, Urban, Transportation, and Hillshade) model simulates four types of urban growth: spontaneous growth, new spreading center growth, edge growth, and road-influenced growth. These growth types are applied sequentially during each growth cycle and controlled through the interactions of growth coefficients: dispersion, breed, spread, slope resistance, and road gravity [12
Since its initial development in 1997, SLEUTH has undergone numerous technical modifications, since its initial days, to reach its current sophisticated state [29
]. SLEUTH’s source code was revised to reduce computation time and sensitivity. The development of the Optimal SLEUTH Metric (OSM) helped in determining the best goodness of fits measure [24
]. A parallel version of the model (pSLEUTH) was developed using a parallel raster processing programming library (pRPL) to enhance SLEUTH’s capabilities of processing massive raster datasets in a shorter computation time [30
]. A significant improvement was made to the SLEUTH model and a modified version (SLEUTH-3r) [28
]. SLEUTH-3r can capture dispersed settlement patterns more efficiently through modifying the diffusion multiplier value. In this modified version, the user can interactively set the diffusion coefficient multiplier after being static (0.005) in the early version. Furthermore, SLEUTH-3r creates new tabular files, including differences and ratio metrics (Population Fractional Difference (PFD) and Cluster Fractional Difference (CFD)), that directly compare the modeled variable with the observed variable for all control sets. These metrics allow for using two historic urban extents instead of four and can be used as an alternative for measures of fit used to evaluate simulated urban in the calibration phase.
A countless number of studies worldwide have applied SLEUTH to capture and predict urban dynamics [31
]. In the US, the model was intensively used within the metropolitan counties for many eastern, western, and southern cities [24
]. In Europe, the model was implemented in many cities such as Lison and Porto [33
], Helsinki (Finland), Bilbao (Spain), and Palermo (Italy) [34
], and was used to model the impacts of urban growth on agriculture and natural land for the entire country of Italy [35
] In the Middle East, many case-studies utilized SLEUTH to map and quantify urban changes for the cities of Mashad (Iran) [36
], Cairo and Alexandria(Egypt) [37
], Muscat (Oman) [39
], and Sana’a (Yemen) [40
With nearly 68% of its population reside in cities, the Arab region is recognized among the scarcest water and agricultural resources per capita in the world [41
]. The Arab countries’ unplanned urban expansion adds another challenge in promoting sustainable development and sustaining limited agricultural resources, especially farmlands. From 1970 to 2010, the Arab urban population grew four times, and the number is expected to double by 2050 [42
]. Here, city planning is often challenged by the disconnection between national strategic planning cycles and spatial planning for urban development. This becomes more problematic when the Arab countries neglect the importance of proper management through balancing between available agricultural lands and conversion for urban use [44
]. Nevertheless, and due to increasing conversion rates of farmlands to urbanization, countless efforts have been paid towards modeling long-term land-use/cover dynamics, in general, and urbanization, in particular, in these countries [44
]. Jordan is categorized as a food deficit Arab country, where 0.5% of all households suffer from food insecurity. Jordan’s arable area has undergone considerable decline since 1975 mainly due to rapid urban growth and land degradation [48
]. Although the contribution of the agricultural sector to the GDP is small, farming remains a major source of food for nearly 25% of Jordan’s poor [51
]. While numerous studies were conducted to establish a linkage between urbanization and agricultural land consumption, the focus was yet on the capital city of Amman [53
Located to the north of Amman in the most fertile and productive agricultural zone of Jordan, Irbid city was neglected for years. In recent years and as land-use/cover began to change dramatically, built-up urban area rapidly has grown on the productive peripheral farmlands, forming a major metropolitan area in the north. To facilitate the problem of governance of such a vast area, the number of municipalities and village councils around the city of Irbid were amalgamated to form what is known today as the Greater Irbid Municipality [57
]. Accordingly, the municipal boundary of Irbid city was adjusted resulting in integrating agriculturally dominant rural districts to the city limits. Since 2001, the GIM area has undergone significant land cover changes to support the growing urban population resulting from (1) economic development (2) domestic rural-urban migration, (3) changing demographic structure, (4) changing lifestyle, and (5) the influx of Syrian refugees during the Arab Spring of 2011 [58
While numerous case-studies investigated urban growth in Irbid using remote sensing and GIS [59
], no study has yet used the SLEUTH model to predict urban dynamics and quantify the past, present, and future urban expansion on agricultural land of Jordan. The SLEUTH model is applied for the first time in Jordan, providing a robust approach for making long-term sustainable urban planning strategies that integrate spatially explicit models and geospatial technologies. In this study, the impact of past, present, and future urban development patterns and agricultural land consumption across a 324 km2
GIM area are examined. These transformations are analyzed at the district level for the first time to highlight the most affected districts and their agricultural values. The GIM was selected as a study area because (1) nearly 40% of Jordan’s primary croplands located in Irbid, (2) it is the second-fastest-growing urban area in the country, (3) it has been experiencing rapid socioeconomic and demographic transformations, and (4) its zoning and urban planning policies are not well designed, not fully enforced, and their sustainability perspectives are not pronounced.
This study investigated past, present, and future land cover transformations at both the municipality and district levels of Greater Irbid Municipality featuring the application of SLEUTH for the first time in Jordan. The magnitude of past land cover changes and the foreseen changes were examined. The findings of this research suggest that GIM landscape composition exhibited a significant change in the past decades and will continue to experience more changes mainly associated with urbanization. The amount of agricultural land lost for urban development is of great value for sustainable development. Both fragmentations of agricultural lands and urbanization have been recognized as the main challenges in sustaining and developing the agricultural sector in Irbid. GIM is in urgent need of the adoption of a compact policy by which no more new lands are added for urban development. Infill development patterns should be enforced, and the striking land prices should be regulated.
While past urban growth in GIM was mainly driven by changing lifestyles and rural-urban migration, present growth is highly driven by the influx of refugees from neighboring countries, changing municipal policies, and socioeconomic transformations. The present and future low-intensity growth patterns are shaped by arbitrarily urban planning policies, absence of an environmental land value, land speculation, and striking land prices. GIM suffers from uncontrolled land uses as there are no hierarchy of zones and most areas are mixed-uses. Irbid city is unique in its location, physiographic settings, and agricultural value. Yet, urban planning strategies did not preserve this value and its environmental assets. Urban planning strategies must be drawn within a more sustainable development model reflecting an official commitment to attaining the SDGs goals and targets towards achieving “sustainable urbanization and capacity for participatory, integrated and sustainable human settlement planning and management in all countries” (SDG 11 (11.3)). City municipal boundaries should have been adjusted at several stages over time and based on reliable demographic and socioeconomic variables. For a balanced development, municipal authorities need tools to monitor how the land is currently used, assess future demand, and take actions to assure adequacy of future supply. This research promotes and supports sustainable development planning through producing spatially explicit forecasts proving the efficiency and capability of forecasting to not only investigating the implications for agriculture, food security, and urban planning but also to use the results as input to other models to measure consequences on, for instance, land degradation and water quality. Such information is of great importance for decision-making in Jordan where there is an urgent need for proper land management practices and sustainable land-use policies.