نوع مقاله : مقاله پژوهشی
نویسندگان
1 پژوهشگر دکتری شهرسازی، گروه طراحی شهری، دانشکده معماری وشهرسازی، دانشگاه هنر ایران، تهران، ایران .
2 دانشیار، گروه طراحی شهری، دانشکده معماری وشهرسازی، دانشگاه هنر ایران، تهران، ایران .
چکیده
شهرهای امروزی با طیف فزایندهای از بحرانها مواجهند که مدیریت هوشمند آنها به یک اولویت حیاتی تبدیل شده است. در پی تحولات سریع فناوریهای دیجیتال، همزاد دیجیتال شهری بهعنوان یک نوآوری کلیدی در قرن ۲۱ ظهور کرده که ابزاری محوری در مدیریت بحران محسوب میشود. در همین راستا، هدف این پژوهش، بررسی جامع ظرفیتهای مفهومی و عملیاتی همزاد دیجیتال شهری در بهینهسازی و ارتقای مؤثر چرخه مدیریت بحرانهاست. این پژوهش سعی بر تبیین چگونگی مداخله این ابزار کاتالیزوری در هر یک از مراحل مدیریت بحران (کاهش خطر، آمادگی وپاسخ و بازیابی) و ارتقای تصمیمگیری هوشمند برای کاهش آسیبهای مالی و جانی دارد.این پژوهش با اتخاذ یک رویکرد کیفی تفسیری و راهبرد استدلالی قیاسی، درک عمیقی از ابعاد مفهومی و ساختارهای پیچیده این فناوری در بستر شهری ارائه میدهد. ماهیت پژوهش بنیادی_توسعهای است و لحاظ بُعد زمانی، از دسته مطالعات طولی محسوب میشود.نتایج نشان میدهد که همزادهای دیجیتال شهری تأثیرات عمیقی در زمینههایی مانند جمعآوری دادههای بلادرنگ، پیشبینیپذیری، سنجش راهبردها و مدلسازی و شبیهسازی با وضوح بالا دارند. شواهد به وضوح تأیید میکند که همزاد دیجیتال شهری فراتر از یک فناوری صرف، به یک مؤلفه ضروری در اکوسیستم مدیریت هوشمند بحرانها تبدیل شده است. قابلیتهای این فناوری در یکپارچهسازی دادهها، شبیهسازی سناریوهای پیچیده و ارائه تحلیلهای پیشبینانه، پشتیبانی قدرتمندی را در هر سه فاز چرخه مدیریت بحران فراهم میکند؛ در فاز آمادگی با بهینهسازی مسیرهای تخلیه و تقویت زیرساختها، در لحظه بحران با ارزیابی سریع خسارت و ارائه پاسخ هوشمند و در فاز پس از بحران بهعنوان پلتفرم اطلاعاتی جامع برای بهینهسازی سیستم پیشگیری و افزایش تابآوری آتی، فرآیند مدیریت بحران های شهری را بهبود می بخشد.
کلیدواژهها
موضوعات
عنوان مقاله [English]
An Overview of the Concept of Urban Digital Twin and Its Role in Urban Crisis Management
نویسندگان [English]
- Ali Riahi Dehkordi 1
- Amir Shakibamanesh 2
1 Department of Urban Design, Faculty of Architecture and Urban Planning, Iran University of Art, Tehran, Iran.
2 Department of Urban Design, Faculty of Architecture and Urban Planning, Iran University of Art, Tehran, Iran.
چکیده [English]
Highlights
An integrated framework links multilayer urban digital twin architecture with risk reduction, preparedness, response, and recovery across the crisis management cycle.
Natural and human-made crises are comparatively examined to clarify how urban digital twins support effective management across distinct contexts.
Urban digital twins enhance situational awareness, city visualization, simulation, prediction, and resilience within complex urban crisis management processes and decision-making.
Implementation challenges are classified across data, infrastructure, modeling, cybersecurity, governance, and organizational acceptance within urban digital twin systems and practices.
Localization requirements and enabling conditions for digital twins are identified for developing countries, with particular emphasis on implementation in Iran.
Extended Abstract
Introduction
The growing frequency and complexity of natural and human-made crises, alongside concentrated populations, infrastructure, and economic activity, have made crisis management a central concern in planning and governance. This issue is particularly significant in developing countries facing deteriorating infrastructure, limited resources, institutional misalignment, and social vulnerability. Iran’s seismic exposure, climatic diversity, uneven urban expansion, and exposure to natural, industrial, and social hazards require a shift from reactive management toward anticipatory, data-driven approaches.
Traditional crisis management often relies on cross-sectional data, fragmented organizations, and post-event decision-making. In complex cities, where infrastructure, communication networks, population behavior, and decision-making interact, such approaches have limited capacity to predict cascading impacts or identify effective strategies.
Urban digital twins connect cities with dynamic digital representations for monitoring, prediction, scenario testing, and intervention. Yet the literature remains fragmented, architecturally inconsistent, predominantly focused on response, and lacking a framework that links technical structures to the full crisis management cycle. This study examines their effects on decision-making, coordination, and resource allocation across risk reduction, preparedness, response, and recovery in natural and human-made crises.
Theoretical Framework
The framework integrates crisis management, urban digital twins, and smart urban governance. Crisis management is treated as a cycle comprising risk reduction, preparedness, response, and recovery. These stages are interdependent: response should facilitate recovery, while lessons from recovery should contribute to reducing future risks and strengthening preparedness. Effective management therefore requires the preservation, transfer, and continuous updating of knowledge throughout the cycle.
An urban digital twin is a dynamic, multilayered system that synchronizes physical and digital spaces, analyzes urban behavior, and simulates potential decisions and interventions. Its five layers comprise physical assets, populations, infrastructure, and sensors; virtual representations; historical, real-time, and external data; mathematical models, machine-learning algorithms, and simulations; and services such as dashboards, warnings, decision support, and infrastructure control.
A bidirectional loop transfers sensor, satellite, drone, social, traffic, modeling, and historical data into the digital model. Artificial intelligence and cloud, edge, or fog computing process these inputs. Outputs are returned as models, dashboards, warnings, scenarios, and commands. Three major capacities emerge: situational awareness and visualization; simulation and predictability; and collaboration, policymaking, and resilience.
Methodology
This qualitative, interpretivist, fundamental–developmental study employed a structured conceptual review. Deductive reasoning was used to apply crisis-management theory and digital-twin architecture to the classification of evidence, while conceptual synthesis was employed to reconstruct relationships among system structure, data flows, analytical capabilities, and crisis-cycle stages.
Web of Science, Scopus, ScienceDirect, and Google Scholar were searched for publications from 2009 to 2026 using combinations of crisis management, hazard management, digital twin, urban digital twin, digital twin city, and smart city digital twin. Most of the selected studies were published between 2020 and 2025. Direct relevance to concepts, architectures, data models, applications, hazard types, and implementation challenges guided inclusion. Recent sources were prioritized, while foundational studies were retained. Seventy-four articles were selected.
The analysis standardized crisis concepts and stages, compared architectures based on layers, inputs, processes, and outputs, examined capabilities before, during, and after natural and human-made crises, and classified data-related, infrastructural, systemic, organizational, and governance challenges. The findings were synthesized into a model linking technical architecture, decision-support capacities, crisis types, management stages, and institutional requirements.
Results and Discussion
Findings show that urban digital twins transform fragmented information into coherent, dynamic, decision-ready representations. By integrating historical and real-time data, physical and behavioral models, and alternative scenarios, they shift crisis management from reactive activity toward a more anticipatory, adaptive, and learning-oriented process. They support rather than replace decision-makers by reducing uncertainty, comparing interventions, and accelerating coordination.
During risk reduction and preparedness, digital twins identify physical, infrastructural, and social vulnerabilities, map hazards, predict cascading impacts, evaluate preventive strategies, and support training, evacuation exercises, route assessment, and public awareness. During preparedness and response, sensors, the Internet of Things, satellite and drone imagery, traffic data, and social sensing generate real-time situational awareness. This enables rapid damage assessment, identification of critical areas, prioritization of relief efforts, allocation of equipment, safe evacuation routing, active decision support, and, in some cases, infrastructure control. During recovery, comparisons of pre- and post-event conditions, analysis of damage, identification of weaknesses, and prediction of secondary hazards support reconstruction, policy revision, institutional learning, and resilient rebuilding.
Natural-crisis applications emphasize physical hazard processes, spatiotemporal analysis, and infrastructure vulnerability. Flood models combine hydrological, environmental, and population data; earthquake models integrate buildings, infrastructure, seismic information, and post-event imagery; and fire models simulate fire and smoke propagation, emergency routes, and evacuation. Human-made applications emphasize operational monitoring, behavior, security, and rapid control, including failure prediction, pollutant-release simulation, threat analysis, crowd-bottleneck detection, exit optimization, and emergency coordination.
Both crisis groups follow a common logic: data acquisition, situational representation, consequence simulation, intervention comparison, recommendation transfer, and model updating. Differences concern data types, processing speeds, uncertainty, and model characteristics. Natural crises generally require environmental and terrain-based models, whereas human-made crises depend more heavily on real-time behavioral, security, and operational data.
Challenges include poor data quality, heterogeneity, missing information, sensor noise, the absence of standards, communication failures, and weak integration among information models and geographic information systems. Cybersecurity, privacy, data ownership, unclear governance, organizational resistance, undefined responsibilities, and weak participation may further undermine implementation. Technical models may also neglect social realities, local knowledge, and spatial inequalities.
For Iran and similar contexts, implementation requires digital infrastructure, clear legal frameworks, technological capacity, and organizational acceptance. Pilot projects, interoperable spatial databases, emergency communication networks, data-sharing protocols, and institutional cooperation can support localization. Maturity depends on data synchronization, predictive validity, infrastructural resilience, organizational interoperability, and social legitimacy.
Conclusion
Urban digital twins can support crisis management by connecting cities, real-time data, simulation models, and decision-making processes. Their effectiveness requires reliable data, interoperable standards, robust communication systems, cybersecurity, transparent governance, collaboration, and citizen participation. They improve resilience only when developed as human-centered, learning-oriented ecosystems embedded within broader crisis governance.
کلیدواژهها [English]
- Urban digital twin
- natural crises
- human-made crises
- smart crisis management
)