Article
Computer Science, Information Systems
Jinqu Zhang, Yu Ling, A-Xing Zhu, Hongyun Zeng, Jia Song, Yunqiang Zhu, Lang Qian
Summary: Cellular Automata (CA) models are widely used for simulating urban expansion. This study develops a method to measure the spatial anisotropy (SA) of urban areas and integrates it into a CA model. The case study in Huizhou, China, demonstrates that considering SA improves the accuracy of the model.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2022)
Article
Computer Science, Interdisciplinary Applications
Wenyu Jiang, Fei Wang, Linghang Fang, Xiaocui Zheng, Xiaohui Qiao, Zhanghua Li, Qingxiang Meng
Summary: This study developed a fire spread model based on the heterogeneous Cellular Automata model for large-scale complex wildland-urban interface (WUI) areas, and successfully validated its high simulation efficiency, timeliness, and accuracy.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Engineering, Multidisciplinary
Jinghui Wang, Wei Lv, Yajuan Jiang, Guangchen Huang
Summary: This study proposes an improved cellular automata model for modeling mixed pedestrian-vehicle traffic scenes. The analysis of the model shows high simulation accuracy. By applying the model to simulate real-life situations, the research results reveal the impact of pedestrian intrusion behavior on traffic flow and the changes in vehicles' speed and flow rate caused by pedestrian intrusion behavior. Additionally, the study finds that lower speeds and wider sidewalks can effectively reduce the frequency of conflicts between pedestrians and vehicles.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Engineering, Civil
Tsang-Jung Chang, Hsiang-Lin Yu, Chia-Ho Wang, Albert S. Chen
Summary: A new approach for urban inundation modeling integrating 2D and 1D models with a cellular automata framework has been proposed in this study. It showed improved accuracy and computational efficiency compared to traditional approaches, making it a useful tool for real-time urban inundation modeling.
JOURNAL OF HYDROLOGY
(2021)
Article
Engineering, Multidisciplinary
Jian Tang, Siddhant Kumar, Laura De Lorenzis, Ehsan Hosseini
Summary: We propose Neural Cellular Automata (NCA) for simulating microstructure development in the solidification process of metals. NCA, based on convolutional neural networks, can learn essential features of solidification and are much faster than conventional Cellular Automata (CA). Notably, NCA can make reliable predictions beyond their training range, indicating their understanding of the physics of solidification. While CA data is used for training in this study, NCA can be trained on any microstructural simulation data, such as phase-field models.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Article
Environmental Sciences
Bright Addae, Suzana Dragicevic
Summary: Existing geosimulation land-use change models are mainly designed for local or regional spatial scales, but they lack considerations for spatial distortions and land suitability analysis at the global level. This study integrates multi-criteria evaluation with spherical cellular automata to develop a novel modeling approach for simulating global urban land-use change.
GEOCARTO INTERNATIONAL
(2022)
Article
Energy & Fuels
Mingxuan Mao, Siyu Chen, Jinyue Yan
Summary: This paper proposes a dynamic modelling of two-lane pavement photovoltaic arrays based on cellular automata theory, and explores the influence of random vehicle shadows on the output characteristics. A mathematical model of two-lane pavement PV arrays considering bypass diodes and blocking diodes is established. An asymmetric two-lane Nagel-Scheckenberg (ATNS) model is introduced to characterize the change of irradiation intensity caused by vehicle shadows. Simulations and experiments show that the slowing probability and shading degree significantly affect the output characteristics, and the dynamic random vehicle shadows result in a changing multi-peak state of the power-voltage curve.
Article
Construction & Building Technology
Lucia Saganeiti, Ahmed Mustafa, Jacques Teller, Beniamino Murgante
Summary: This paper proposes a spatiotemporal analysis method for simulating and predicting urban expansion using cellular automata (CA) and multinomial logistic regression (MLR) model. Through analyzing regional building datasets and identifying causative factors, the study reveals a decoupled growth pattern between demographic trend and urban expansion in the Basilicata region of Italy. The results show the largest variations in low density builtup patches, corresponding to urban sprinkling, in the forecasted urban expansion for 2030.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Urban Studies
Wanru He, Xuecao Li, Yuyu Zhou, Xiaoping Liu, Peng Gong, Tengyun Hu, Peiyi Yin, Jianxi Huang, Jianyu Yang, Shuangxi Miao, Xi Wang, Tinghai Wu
Summary: Cellular automata (CA) based models are widely used in urban sprawl modeling for sustainable urban planning. However, most existing urban CA models only consider abrupt conversion, ignoring the difference in urbanization levels among grids and the gradual increase in urban densities. In this study, we proposed an impervious surface area (ISA) based urban CA model that can simulate urban fractional change within each grid. The model was implemented in Beijing and evaluated through comparison and scenario analyses. Results showed that the ISA-based urban CA model captures the dynamics of urban sprawl better than the traditional urban CA model and has great potential in supporting sustainable urban development.
Article
Chemistry, Physical
Jaroslaw Opara, Boris Straumal, Pawel Zieba
Summary: This study presents the fundamentals of modelling discontinuous precipitation (DP) reactions using cellular automata method, defining cell states, internal variables, equations, and transition rules to predict mass transport and relate microstructural changes with chemical composition changes. The developed CA model successfully simulated the DP reaction and visualized migrating reaction fronts and associated chemical composition changes in the microstructure.
Article
Engineering, Geological
Rene Gomez, Raill Castro
Summary: This article proposes a model for simulating the vertical stresses of granular material under static and dynamic flow conditions, developed within a gravity flow simulator based on cellular automata. After testing and calibration, the model can accurately simulate the vertical stresses under different flow setups and has the potential to be applied at block caving scale.
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
(2022)
Article
Ecology
Jianxin Yang, Wenwu Tang, Jian Gong, Rui Shi, Minrui Zheng, Yunzhe Dai
Summary: This study proposes a new urban cellular automata (CA) modeling framework that incorporates a spatiotemporally explicit urban demand modeling scheme. The framework uses spatiotemporal Gaussian-based models to represent the heterogeneity of urban demand. The application of the framework to Wuhan, China demonstrates the ability to capture the wave-shaped propagation pattern of new urban land demand and improve model performance at both macro and micro levels.
LANDSCAPE AND URBAN PLANNING
(2023)
Article
Ecology
Jianxin Yang, Wenwu Tang, Jian Gong, Rui Shi, Minrui Zheng, Yunzhe Dai
Summary: This study proposes a new urban cellular automata modeling framework that incorporates spatiotemporally explicit urban demand modeling to guide micro-level urban land allocation for simulating urban expansion. The results demonstrate that this framework can capture urban dynamics at both macro and micro levels, improving model performance.
LANDSCAPE AND URBAN PLANNING
(2023)
Article
Engineering, Civil
Stephen J. Birkinshaw, Greg O'Donnell, Vassilis Glenis, Chris Kilsby
Summary: The research introduces a new method to calculate sewer fractions in urban river catchments and uses them to improve hydrological models, which can be applied to urban and peri-urban catchments without fine resolution sewer and hydrological data.
JOURNAL OF HYDROLOGY
(2021)
Article
Geography
Yan Liu, Michael Batty, Siqin Wang, Jonathan Corcoran
Summary: The study of land use change in urban and regional systems has been significantly transformed by the emergence of cellular automata models in the last four decades. There are still gaps between urban processes simulated in CA models and actual urban dynamics, leading to the need for comprehensive models that capture multi-dimensional processes, incorporation of human decision behaviors, utilization of big data for calibration and validation, and strengthening of theory-based models to explain urban change mechanisms comprehensively. Cellular automata embedded with agent-based models and big data input are seen as the most promising analytical framework to enhance understanding and planning of contemporary urban change dynamics.
PROGRESS IN HUMAN GEOGRAPHY
(2021)
Article
Engineering, Civil
Milos Milasinovic, Damjan Ivetic, Milan Stojkovic, Dragan Savic
Summary: Climate change, energy transition, population growth, and outdated infrastructure can cause Dam and Reservoir Systems (DRS) to operate outside of their design envelope. To assess system performance under different scenarios, Digital Twins (DT) of DRSs are necessary. This paper presents a more realistic failure scenario generator based on a causal approach, utilizing fuzzy logic reasoning to create DRS failures based on hazard severity and subsystem reliability. The proposed method was demonstrated using a case study of the Pirot DRS in Serbia, showing that occasional hazards combined with outdated infrastructure can significantly reduce DRS performance and identify hidden failure risks.
WATER RESOURCES MANAGEMENT
(2023)
Article
Green & Sustainable Science & Technology
Mehdi Khoury, Barry Evans, Otto Chen, Albert S. Chen, Lydia Vamvakeridou-Lyroudia, Dragan A. Savic, Slobodan Djordjevic, Dimitrios Bouziotas, Christos Makropoulos, Navonil Mustafee
Summary: Understanding the circular economy for water is challenging due to the complexity of the urban water cycle and its interrelations with other factors. To address this challenge, the NextGen Serious Game was developed as an online educational tool to explore the implications of circular economy strategies in different virtual catchments. The game has been successfully used in classrooms, debate facilitation, and even as a competitive tournament for water professionals, contributing to public understanding of water issues.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
B. Evans, M. Khoury, L. Vamvakeridou-Lyroudia, O. Chen, N. Mustafee, A. S. Chen, S. Djordjevic, D. Savic
Summary: Climate change presents challenges in terms of water scarcity, environmental crisis, and economic uncertainty. The EU-funded NextGen project aims to enhance sustainability and maximize resource use in the water cycle through new technologies and approaches. It develops Serious Games enabled by System Dynamic Models for demonstrating the benefits of water-energy-material interactions in the circular economy of water. Evaluation: 9 points.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Interdisciplinary Applications
Guoxuan Liu, Dragan Savic, Guangtao Fu
Summary: Accurate water demand forecasting is crucial for urban water management in the face of urbanization, water scarcity, and climate change. This study evaluates the impact of training data length, temporal resolution, and data uncertainty on forecasting model results using a data-centric machine learning approach. The results show that data-centric machine learning approaches have the potential to improve the accuracy of short-term water demand forecasts, even with limited training data. The Random Forest and Neural Network models outperform other models when it comes to forecasting high-temporal resolution data, and improving data quality can achieve accuracy increase comparable to model-centric machine learning approaches.
JOURNAL OF HYDROINFORMATICS
(2023)
Article
Engineering, Civil
W. Addison-Atkinson, A. S. Chen, M. Rubinato, F. A. Memon, J. D. Shucksmith
Summary: The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields. The findings show that model performance was reduced as the scenario complexity increased, but most of the simulation error was < 10% (NRMSE). Additionally, the validated model with higher spatial resolution had more error compared to the lower resolution model due to less stringent calibration at lower spatial resolution. However, overall the study demonstrates the potential of using low-resolution datasets for model calibration.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Chris Sweetapple, Matthew J. Wade, Peter Melville-Shreeve, Albert S. S. Chen, Chris Lilley, Jessica Irving, Jasmine M. S. Grimsley, Joshua T. Bunce
Summary: Wastewater-based epidemiology (WBE) is a useful tool for monitoring the spread of COVID-19. This study investigates the impact of population normalisation on SARS-CoV-2 dynamics observed through wastewater monitoring. Data from 394 sites in England are analyzed, and normalisation is implemented based on specific concentrations. The study finds that normalisation has a limited impact on overall temporal trends but shows significant variability in local-level trends.
JOURNAL OF WATER AND HEALTH
(2023)
Article
Engineering, Civil
Chloe Grison, Stef Koop, Steven Eisenreich, Jan Hofman, I-Shin Chang, Jing Wu, Dragan Savic, Kees van Leeuwen
Summary: Water scarcity and accessibility continue to be significant global challenges that require attention. This paper provides a comprehensive analysis of water-related challenges in cities, including water, wastewater, municipal solid waste, and climate change. By evaluating the performance of 200 cities, representing over 95% of the global urban population, the study identifies the existing gaps in achieving water-related Sustainable Development Goals (SDGs). Most cities are not effectively managing their water resources and face challenges in achieving targets for drinking water supply, sanitation, solid waste management, climate adaptation, and informal settlements.
WATER RESOURCES MANAGEMENT
(2023)
Article
Engineering, Environmental
Jessica Penny, Priscila B. R. Alves, Yenushi De-Silva, Albert S. Chen, Slobodan Djordjevic, Sangam Shrestha, Mukand Babel
Summary: Despite the growing research and applications of nature-based solutions (NBS), there is a lack of application and quantitative assessment of NBS in South East Asia. This study addresses this gap by using MCDA-GIS analysis to map the potential impact of NBS on flood hazard reduction in the Mun River Basin, Thailand. Wetlands, re/afforestation, and changing crop types were found to be effective strategies for mitigating flood and drought hazards. The results show that implementing NBS in the catchment decreases flood hazard, particularly through reforestation, and even more so when a combination of NBS is applied.
WATER SCIENCE AND TECHNOLOGY
(2023)
Article
Biodiversity Conservation
Mahdi Nakhaei, Pouria Nakhaei, Mohammad Gheibi, Benyamin Chahkandi, Stanislaw Waclawek, Kourosh Behzadian, Albert S. Chen, Luiza C. Campos
Summary: This paper introduces a new framework for intelligent comprehensive risk management in arid regions. The framework combines flash flood modeling, statistical methods, artificial intelligence, geographic evaluations, risk analysis, and decision-making modules to enhance community resilience. The practicality of the methodology is demonstrated through a real case study in the Khosf region of Iran.
ECOLOGICAL INDICATORS
(2023)
Article
Computer Science, Interdisciplinary Applications
Farzad Piadeh, Kourosh Behzadian, Albert S. Chen, Luiza C. Campos, Joseph P. Rizzuto, Zoran Kapelan
Summary: This study proposes a novel event-based decision support algorithm for real-time flood forecasting, which achieves higher accuracy in forecasting water level rise, especially for longer lead times (e.g., 2-3 hrs), compared to traditional models.
ENVIRONMENTAL MODELLING & SOFTWARE
(2023)
Article
Environmental Sciences
Yuntao Wang, Chi Zhang, Albert S. Chen, Guoqiang Wang, Guangtao Fu
Summary: The assessment of flood risk and resilience in urban areas is becoming more important for effective flood management. This study investigates the relationship between flood risk and resilience at the grid cell level. A performance-based flood resilience metric is proposed, and flood risk is calculated considering multiple storm events. The results show a complex relationship between flood risk and resilience, with different land uses showing different levels of resilience for the same risk level.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Environmental Sciences
Barry Evans, Arthur Lam, Charles West, Reza Ahmadian, Slobodan Djordjevic, Albert Chen, Maria Pregnolato
Summary: This paper proposes a methodology to assess the risks faced by vehicle occupants and pedestrians in urban areas. By considering the stability functions of different vehicle types and pedestrians, a risk assessment profile for vehicle occupants was derived. The findings indicate that remaining inside a flooded vehicle may increase the level of risk for individuals. Therefore, this study is of great significance in reducing flood risks.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Article
Environmental Sciences
Tommaso Lazzarin, Albert S. Chen, Daniele P. Viero
Summary: The effective communication of flood hazard and risk is crucial in reducing the detrimental impacts of flooding events. Traditional flood maps are often difficult to understand, leading to the use of color maps for better communication. However, these hazard indexes have inherent limitations. Therefore, the use of a physics-based and data-consistent risk index, such as the loss probability (LP) map, is proposed for a more accurate estimation and communication of flood risk.
SCIENCE OF THE TOTAL ENVIRONMENT
(2024)
Review
Computer Science, Artificial Intelligence
Vahid Bakhtiari, Farzad Piadeh, Albert S. Chen, Kourosh Behzadian
Summary: This review study examines the importance of cutting-edge flood visualisation technologies in managing urban flood risks and focuses on stakeholder analysis. The study finds that while existing research has primarily focused on water utilities and communication with the general public, there is a lack of comprehensive engagement with important stakeholders such as policy-makers, researchers, and insurance providers. The study also highlights the disparities in stakeholder involvement in damage assessment studies and introduces the concept of overlooked key stakeholders and their interconnected impacts.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)