Measuring the Effect of Stochastic Perturbation Component in Cellular Automata Urban Growth Model

The global urban population is expected to grow by 2.5 billion over the next three decades, and 90% of this growth will occur in African and Asian countries. Urban expansion in these regions is often characterised by ‘informal urbanization’ whereby households self-build without planning permission in contexts of ambiguous, insecure or disputed property rights. Despite the scale of informal urbanization, it has received little attention from scholars working in the domains of urban analytics and city science. Towards addressing this gap, we introduce TI-City, an urban growth model designed to predict the locations, legal status and socio-economic status of future residential developments in an African city. In a bottom-up approach, we use agent-based and cellular automata modelling techniques to predict the geospatial behaviour of key urban development actors, including households, real estate developers and government. We apply the model to the city-region of Accra, Ghana, drawing on local data collection, including a household survey, to parameterise the model. Using a multi-spatial-scale validation technique, we compare TI-City’s ability to simulate historically observed built-up patterns with SLEUTH, a highly popular urban growth model. Results show that TI-City outperforms SLEUTH at each scale, suggesting the model could offer a valuable decision support tool in similar city contexts.

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Brains versus Brawn — Comparative Strategies for the Calibration of a Cellular Automata-Based Urban Growth Model

GeoDynamics ◽

10.1201/9781420038101.ch18 ◽

2004 ◽

pp. 249-272 ◽

Cited By ~ 16

Author(s):

Noah Goldstein

Keyword(s):

Cellular Automata ◽

Growth Model ◽

Urban Growth ◽

Urban Growth Model

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A Cellular Automata Urban Growth Model for Water Resources Strategic Planning

10.29007/w43g ◽

2018 ◽

Cited By ~ 1

Author(s):

Dionysios Nikolopoulos ◽

Konstantina Risva ◽

Christos Makropoulos

Keyword(s):

Water Resources ◽

Strategic Planning ◽

Cellular Automata ◽

Growth Model ◽

Urban Growth ◽

Management Practices ◽

High Reliability ◽

Population Increase ◽

Water Quality Control ◽

Urban Growth Model

The alarming rate of urbanization poses immediate problems to water resources management, mainly, but not limited to water supply, flood risk management, wastewater treatment and water quality control. Ideally, strategic planning of water systems should be fully aware of the prospects of future urban growth in order to maintain high reliability of services provided and satisfy customers in the long term. Typically, urban growth is handled in a static manner via the development of future scenarios based on previous urban planning studies. Generally, these scenarios focus solely on population increase and ignore the spatial allocation dynamics. Modern urban water strategic thinking needs to incorporate robust tools and methodologies in management practices, able to predict and quantify the outcome possibility of future urban growth. To cope with the aforementioned challenge, this study proposes a novel cellular automata urban growth model as well as, a supplementary remote sensing methodology to preprocess input data.

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A Fuzzy Cellular Automata Urban Growth Model (FCAUGM) for the City of Riyadh, Saudi Arabia. Part 1: Model Structure and Validation

Applied Spatial Analysis and Policy ◽

10.1007/s12061-008-9020-6 ◽

2009 ◽

Vol 2 (1) ◽

pp. 65-83 ◽

Cited By ~ 24

Author(s):

Khalid Al-Ahmadi ◽

Alison Heppenstall ◽

Jim Hogg ◽

Linda See

Keyword(s):

Saudi Arabia ◽

Cellular Automata ◽

Growth Model ◽

Urban Growth ◽

Model Structure ◽

Urban Growth Model ◽

Fuzzy Cellular Automata ◽

The City

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Modeling Past, Present, and Future Urban Growth Impacts on Primary Agricultural Land in Greater Irbid Municipality, Jordan Using SLEUTH (1972–2050)

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10040212 ◽

2021 ◽

Vol 10 (4) ◽

pp. 212

Author(s):

Rana N. Jawarneh

Keyword(s):

Land Use ◽

Growth Model ◽

Urban Growth ◽

Agricultural Land ◽

Urban Land Use ◽

Agricultural Area ◽

Grand Challenge ◽

Negative Consequences ◽

Urban Growth Model ◽

Rate Of Increase

Urban expansion and loss of primarily agricultural land are two of the challenges facing Jordan. Located in the most productive agricultural area of Jordan, Greater Irbid Municipality (GIM) uncontrolled urban growth has posed a grand challenge in both sustaining its prime croplands and developing comprehensive planning strategies. This study investigated the loss of agricultural land for urban growth in GIM from 1972–2050 and denoted the negative consequences of the amalgamation process of 2001 on farmland loss. The aim is to unfold and track historical land use/cover changes and forecast these changes to the future using a modified SLEUTH-3r urban growth model. The accuracy of prediction results was assessed in three different sites between 2015 and 2020. In 43 years the built-up area increased from 29.2 km2 in 1972 to 71 km2 in 2015. By 2050, the built-up urban area would increase to 107 km2. The overall rate of increase, however, showed a decline across the study period, with the periods of 1990–2000 and 2000–2015 having the highest rate of built-up areas expansion at 68.6 and 41.4%, respectively. While the agricultural area increased from 178 km2 in 1972 to 207 km2 in 2000, it decreased to 195 km2 in 2015 and would continue to decrease to 188 km2 by 2050. The district-level analysis shows that from 2000–2015, the majority of districts exhibited an urban increase at twice the rate of 1990–2000. The results of the net change analysis of agriculture show that between 1990 and 2000, 9 districts exhibited a positive gain in agricultural land while the rest of the districts showed a negative loss of agricultural land. From 2000 to 2015, the four districts of Naser, Nozha, Rawdah, and Hashmyah completely lost their agricultural areas for urbanization. By 2050, Idoon and Boshra districts will likely lose more than half of their high-quality agricultural land. This study seeks to utilize a spatially explicit urban growth model to support sustainable planning policies for urban land use through forecasting. The implications from this study confirm the worldwide urbanization impacts on losing the most productive agricultural land in the outskirts and consequences on food production and food security. The study calls for urgent actions to adopt a compact growth policy with no new land added for development as what is available now exceeds what is needed by 2050 to accommodate urban growth in GIM.

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