Modelling global urban land-use change process using spherical cellular automata

Addae, Bright; Dragićević, Suzana

doi:10.1007/s10708-022-10776-4

Cited by 4 publications

(3 citation statements)

References 53 publications

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“…Such improvements necessitate the need for utilizing high‐performance computing facilities due to the increased computational demands that come with improved spatial resolution of the system, number of datasets, and complexity of the system being modeled. Furthermore, the function of transition rules in the SGA model can be augmented by incorporating more comprehensive data and parameters (Addae & Dragićević, in press), spatial decision‐making methods such as spatial MCE (Addae & Dragićević, 2022) or machine learning techniques as well as considering multiple land‐use changes and transition rules representing human–environment processes at different spatial scales. This can be especially useful when simulating spatiotemporal processes where human decision‐making is important; thus the SGA models can be used in policy planning and management at the global level.…”

Section: Discussionmentioning

confidence: 99%

Enabling geosimulations for global scale: Spherical geographic automata

Addae

Dragićević

2023

Transactions in GIS

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Several complex dynamic spatial systems are operating on the global scale. Their representation with existing geosimulation models is limited to planar level and do not consider the curvature of the Earth's surface. Thus, the objective of this study is to propose and develop a spherical geographic automata (SGA) modeling approach to represent and simulate dynamic spatial processes at the global level. The proposed SGA model is implemented for three case studies including simulations of: (1) Game of Life as population dynamics; (2) urban land‐use growth; and (3) deforestation all operating on the spherical Earth's surface. Simulation results indicate that the proposed SGA modeling approach can represent spatial processes such as expansion and shrinkage dynamics on the Earth's surface. The proposed approach has the potential to be adopted to represent different complex systems such as ecological, epidemiological, socioeconomic, and Earth systems processes to support environmental management and policymaking at the global level.

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Section: Discussionmentioning

confidence: 99%

Enabling geosimulations for global scale: Spherical geographic automata

Addae

Dragićević

2023

Transactions in GIS

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“…Notably, despite cities encompassing a mere 3% of the globe's landmass, they accommodate a staggering 55% of the global populace, exacerbating the palpable tension between human habitation and environmental integrity [4]. Projections suggest a twofold increase in global urban areas by 2095 [5]. Furthermore, aside from the socioenvironmental disequilibrium induced by urban sprawl, the unrelenting urban sprawl encroaches incessantly upon urban ecological habitats, aquatic bodies, and protected natural reserves, progressively encumbering and infringing upon these vital resources [6].…”

Section: Introductionmentioning

confidence: 99%

Evolving Urban Expansion Patterns and Multi-Scenario Simulation Analysis from a Composite Perspective of “Social–Economic–Ecological”: A Case Study of the Hilly and Gully Regions of Northern Loess Plateau in Shaanxi Province

Zhang,

Liu,

Sheng

et al. 2024

Sustainability

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Over recent decades, the hilly and gully regions of the northern Loess Plateau in Shaanxi province have grappled with severe soil erosion and a precarious ecological milieu. Shaped by urbanization policies, this locale has encountered a gamut of issues, including an imbalance in human–environment dynamics and the degradation of ecological integrity. Consequently, the comprehension of how urban expansion impacts the optimization of regional landscape configurations, the alignment of human–environment interactions in the Loess Plateau’s hilly and gully domains, and the mitigation of urban ecological challenges assumes paramount importance. Leveraging data from land use remote sensing monitoring, alongside inputs from natural geography and socio-economic spheres, and employing methodologies such as landscape pattern indices, we conduct an exhaustive analysis of Zichang City’s urban fabric from 1980 to 2020. Furthermore, employing the CLUE-S model, we undertake multifaceted scenario simulations to forecast urban expansion in Zichang City through to 2035. Our findings delineate two distinct phases in Zichang City’s urban expansion trajectory over the past four decades. From 1980 to 2000, urban construction land in Zichang City experienced a phase of methodical and steady growth, augmenting by 64.98 hectares, alongside a marginal decrease in the landscape shape index (LSI) by 0.02 and a commensurate increase in the aggregation index (AI) by 1.17. Conversely, from 2000 to 2020, urban construction land in Zichang City witnessed an epoch of rapid and haphazard expansion, doubling in expanse, marked by a notable escalation in LSI (2.45) and a corresponding descent in the AI (2.85). The precision of CLUE-S model simulations for Zichang City’s land use alterations registers at 0.88, fulfilling the exigent demand for further urban expansion and land use change prognostication. Under the aegis of the natural development scenario, the augmentation of urban construction land in Zichang City primarily encroaches upon grassland, farmland, and woodland, effectuating an increase of 159.81 hectares. Conversely, under the ambit of urbanization development, urban construction land contends predominantly with farmland, grassland, and woodland, heralding an augmentation of 520.42 hectares. Lastly, under the mantle of ecological protection, urban construction land expansion predominantly encroaches upon grassland, farmland, and woodland, resulting in an augmentation of 4.27 hectares. Through a nuanced analysis of the spatiotemporal evolution of urban expansion and scenario-based simulations, this study endeavors to furnish multi-faceted, scenario-driven, and policy-centric insights for regional planning, urban spatial delineation, and regional ecological safeguarding.

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“…Urbanizing watersheds usually locate in the rapidly developing or urbanizing area. For the past century, the world is in constant urbanization (He et al, 2021;Addae and Dragicevic, 2023), and its urban population reached 50% in 2007 (United Nations, 2014). While for the developing countries, the urbanization trend is still rapidly going (Huang et al, 2022;Xue et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Parameter dynamics of distributed hydrological model in simulating or forecasting flood processes of urbanizing watersheds

Chen,

Liu,

Dong

2023

Preprint

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Abstract. In the past decades, the world has experienced rapid urbanization and observed the appearances of large amount urbanizing watersheds with enhanced flooding, which has a constant changing land use/cover(LUC) types as the most significant feature. Simulating and forecasting urbanizing watershed flood processes faces great challenges, one is how to relate model parameters with the changing LUCs to secure an accurately and reliable simulation and forecasting results. In this study, a methodology for simulating and forecasting urbanizing watershed flood processes is proposed, which employs Liuxihe model as the watershed hydrological model. This methodology sets up the Liuxihe model with latest terrain properties, then derives initial parameter look-up table based on terrain properties, and optimizes it if there is observed hydrological data. If there is LUC changes, then the parameters are updated with the changed LUCs based on the optimized parameter look-up tables. Case study in a highly urbanizing watershed in the Pearl River Delta Area in southern China has shown that this method acquires accurate and reliable flood processes simulation results. Further more, this study has proven an assumption that the hydrological model parameters are LUC stationary, i.e., with the LUC changes, the parameter look-up table will not change, parameter look-up table optimized in a specific time with current LUCs will not change even the LUCs changed. With this assumption, the parameter look-up table only needs to be optimized once. This is a science question that has not been not well answered yet by the scientific communities.

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Modelling global urban land-use change process using spherical cellular automata

Cited by 4 publications

References 53 publications

Enabling geosimulations for global scale: Spherical geographic automata

Enabling geosimulations for global scale: Spherical geographic automata

Evolving Urban Expansion Patterns and Multi-Scenario Simulation Analysis from a Composite Perspective of “Social–Economic–Ecological”: A Case Study of the Hilly and Gully Regions of Northern Loess Plateau in Shaanxi Province

Parameter dynamics of distributed hydrological model in simulating or forecasting flood processes of urbanizing watersheds

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