Cellular Automata Urban Growth Model Research Articles

Modeling Dynamic Urban Growth Using Cellular Automata and Geospatial Technique: Case of Casablanca in Morocco

The rapid urbanisation contribute to the spatial expansion in cities.However, the rapid and unmanaged urban growth, degraded the urban environment. In casablanca the economic engine of Morocco, the rapid urbanization was a result of demographic explosion, rural exodus, and the introduction of new urban projects. Understanding the interdependencies between urban growth patterns, infrastructure, and socioeconomic indicators is a critical step in achieving a sustainable urban development. In order to help Casablanca's sustainable growth, this study used remote sensing data to evaluate past urban land use changes. This study was conducted to examine past urban land cover change on the basis of remote sensing data collected between 1989 and 2019. To forecast the city's expansion for the years 2019e2029, an integrated Cellular Automata urban growth model was used. The research looked into the CA algorithm's capacity to work independently for urban development modeling satellite data from four time periods at equal intervals, as well as population density, distance to the city center, slope, and distance to roadways, are used for this purpose. Between 1989 and 2019, the satellite-based LULC reported an increase of 61.77Km2 (an 88 percent increase). The principle component analysis (PCA) technique was used to analyze geographic variation and found good classification similarity ranging from 87 to 90%. Based on the anticipated LULC, the built-up area will grow to 131.88 km2 in 2019, mostly in the west and southwest. Urbanization will replace and transform other LULC (net loss of 15.348Km2) between 2019 and 2029, followed by plant cover (net loss of 1.608Km2).

Coupling of Cellular Automata Urban Growth Model and HEC-HMS to Predict Future Flood Extents in the Upper Klang Ampang Catchment

Urban areas in tropical regions have higher flood risks due to the more frequent occurrence of intense convective rainfalls. The rising urbanization process have caused more surfaces to be covered with impervious materials, resulting in increased runoff. Modelling urban growth and its impact on urban hydrology is essential to ensure informed decision in the sustainable management and planning of cities in developing country like Malaysia. The aim of this research is to develop an integrated system for simulating future flood extents by coupling flood and urban growth models for the Upper Klang Ampang catchment which includes Kuala Lumpurcapital city. HEC-HMS was used for flood modelling while SLEUTH cellular automata model was employed to analyse urban growth in the catchment. The results indicate that using historical satellite images from 1990, 2000, 2010 and 2016 as input data layers alongwith slope, land use, hill shade, road and restricted area layers, a slight increase in urban growth from 2020 until 2050 is predicted which can cause the peak discharge to increase by about 11-15%. The integrated flood estimation-urban growth system can be used as an effective tool in urban planning and management for the city.

AN ASSESSMENT OF SPATIAL VARIATION OF LAND SURFACE CHARACTERISTICS OF MINNA, NIGER STATE NIGERIA FOR SUSTAINABLE URBANIZATION USING GEOSPATIAL TECHNIQUES

AN ASSESSMENT OF SPATIAL VARIATION OF LAND SURFACE CHARACTERISTICS OF MINNA, NIGER STATE NIGERIA FOR SUSTAINABLE URBANIZATION USING GEOSPATIAL TECHNIQUES

Simulating urban expansion and scenario prediction using a cellular automata urban growth model, SLEUTH, through a case study of Karaj City, Iran

Understanding, analysis, monitoring and modeling of urban growth evolution as a major driving force of land use/land cover transformation, especially in developing countries, is of great importance for land managers in the process of sustainable development. Using spatial predictive models and change detection techniques can provide an additional level of knowledge of the causes and impacts of urban growth mechanisms, which finally provide comprehensive insight into urban chronology. Karaj, the capital of Alborz province, has been experiencing a substantial increase in total area of urban environments mainly due to its socioeconomic attractions during the last three decades. The present work aims to reveal how the historical trend of the urban growth can affect its future spatial pattern. For conducting this study, the SLEUTH cellular automata urban growth model was executed via three calibration steps including coarse, fine and final. Relying on the calibrated model, dynamics of the Karaj City were predicted under its historical trend as well as two different scenarios including compact and extensive growth up to year 2040. According to the findings of the present study, while extensive growth option indicates the most consumption of the vacant lands, the compact scenario dictates infill form of the urban growth in addition to saving spaces. Finally, urban growth forecasting based on its historical trend illustrates that total area of the human-constructed elements will be in the middle of other two predictive scenarios.

Water and the city: exploring links between urban growth and water demand management

Urban water management is currently understood as a socio-technical problem, including both technologies and engineering interventions as well as socioeconomic dimensions and contexts vis-à-vis both end users and institutions. In this framework, perhaps the most important driver of urban water demand, at the intersection between engineering, social and economic domains, is urban growth. This paper examines aspects of the interplay between the dynamics of urban growth and the urban water cycle. Specifically, a cellular automata urban growth model is re-engineered to provide growth patterns at the level of detail needed by an urban water cycle model. The resulting toolkit is able to simulate spatial changes in urban areas while simultaneously estimating their water demand impact under different water demand management scenarios, with an emphasis on distributed technologies whose applicability depends on urban form. The method and tools are tested in the case study of Mesogeia, Greece, and conclusions are drawn, regarding both the performance of the urban growth model and the effectiveness of different urban water management practices.

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

Urban environments are complex dynamic systems whose prediction of the future states cannot exclusively rely on deterministic rules. Although several studies on urban growth were carried out using different modelling approaches, the measurement of uncertainties was commonly neglected in these studies. This paper investigates the effect of uncertainty in urban growth models by introducing a stochastic perturbation method. A cellular automaton is used to simulate predicted urban growth. The effect of stochastic perturbation is addressed by comparing series of urban growth simulations based on different degree of stochastic perturbation randomness with the original urban growth simulation, obtained with the sole cellular automata neighbouring effects. These simulations are evaluated using cell-to-cell location agreement and a number of spatial metrics. The model framework has been applied to the Ourthe river basin in Belgium. The results show that the accuracy of the model is increased by introducing a stochastic perturbation component with a limited degree of randomness, in the cellular automata urban growth model.

Applying Cellular Automata for Simulating and Assessing Urban Growth Scenario Based in Nairobi, Kenya

This research explores urban growth based scenarios for the city of Nairobi using a cellular automata urban growth model (UGM). African cities have experienced rapid urbanization over the last decade due to increased population growth and high economic activities. We used multi-temporal Landsat imageries for 1976, 1986, 2000 and 2010 to investigate urban land-use changes in Nairobi. Our UGM used data from urban land-use of 1986 and 2010, road data, slope data and exclusion layer. Monte-Carlo technique was used for model calibration and Multi Resolution Validation (MRV) technique for validation. Simulation of urban land-use was done up to the year 2030 when Kenya plans to attain Vision 2030. Three scenarios were explored in the urban modelling process; unmanaged growth with no restriction on environmental areas, managed growth with moderate protection, and a managed growth with maximum protection on forest, agricultural areas, and urban green. Thus alternative scenario development using UGM is useful for planning purposes so as to ensure sustainable development is achieved. UGM provides quantitative, visual, spatial and temporal information which aid policy and decision makers can make informed decisions.

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

Managing and modelling urban growth is a multi-faceted problem. Cities are now recognised as complex systems through which non-linear processes, emergence and self-organisation occur. The design of a system that can handle these complexities is a challenging prospect. This paper presents an urban planning application for the city of Riyadh, Saudi Arabia. At the core of the application is a Fuzzy Cellular Automata Urban Growth Model (FCAUGM) which is generally capable of simulating the complexities of urban growth. The chief components of the model are outlined and quantitative and qualitative methods of validation are described. The results of the validation show that the model is to a large extent successful at replicating the spatial patterns over time for Riyadh although closer examination reveals several minor anomalies which cannot readily be explained. The authors conclude that the model offers significant benefits for simulating urban growth and change, for urban planning and decision-support for policy makers and others, but further research will be necessary on methods of validating and interpreting the detailed results.