بررسی کاربرد هوش مصنوعی جغرافیایی (GeoAI) در مدیریت و برنامه‌ریزی شهری
محورهای موضوعی : کاربرد GIS&RS در برنامه ریزی
1 - عضو هیئت علمی گروه مهندسی عمران، دانشگاه آزاد اسلامی واحد سمنان
کلید واژه: هوش مصنوعی جغرافیایی GeoAI, مدیریت شهری, برنامه‌ریزی شهری, داده‌های مکانی, یادگیری ماشین, شهر هوشمند, GIS ,
چکیده مقاله :
این مقاله به بررسی جامع کاربرد هوش مصنوعی جغرافیایی (GeoAI) در حوزه مدیریت و برنامه‌ریزی شهری می‌پردازد. با رشد روزافزون داده‌های مکانی و افزایش نیاز به تحلیل‌های دقیق در فرآیندهای شهری، فناوری GeoAI با تلفیق الگوریتم‌های یادگیری ماشین، تحلیل‌های پیشرفته و تجسم سه‌بعدی، نقش مهمی در شناسایی الگوهای پیچیده و پیش‌بینی روندهای رشد و تغییر کاربری مناطق ایفا می‌کند. در این مطالعه، ابتدا مفاهیم پایه‌ای و چارچوب نظری GeoAI تشریح شده و سپس کاربردهای عملی آن در بهبود سیستم‌های حمل و نقل، کاهش تراکم ترافیکی، شناسایی نقاط پرتردد و مدیریت بحران در شهرهای بزرگ مورد بررسی قرار گرفته است. استفاده از GeoAI با ترکیب داده‌های حاصل از سنجش از دور، حسگرهای اینترنت اشیا و نقشه‌های دیجیتال، به مدیران شهری این امکان را می‌دهد تا با دسترسی به اطلاعات به‌روز و دقیق، تصمیمات استراتژیک در راستای توسعه پایدار را اتخاذ نمایند. این فناوری با تحلیل همزمان داده‌های فضایی و توصیفی، نقاط ضعف و قوت سیستم‌های موجود را شناسایی و راهکارهای بهینه جهت برنامه‌ریزی و مدیریت منابع شهری ارائه می‌دهد. علاوه بر این، به‌کارگیری GeoAI موجب کاهش هزینه‌های اجرایی، افزایش کارایی در تخصیص منابع و بهبود کیفیت خدمات شهری می‌شود. نتایج به‌دست آمده نشان می‌دهد که استفاده از هوش مصنوعی جغرافیایی به عنوان ابزاری تحول‌آفرین در برنامه‌ریزی شهری، می‌تواند نقش بسزایی در ایجاد شهرهای هوشمند، پویاتر و پایدار داشته باشد. مقاله علاوه بر ارائه چارچوب مفهومی، پیشنهاداتی جهت توسعه بیشتر فناوری‌های مرتبط و ادغام آن‌ها با سیستم‌های مدیریت شهری ارائه نموده و افق‌های جدیدی را در بهبود عملکرد شهری ترسیم می‌کند.
This paper provides a comprehensive examination of the applications of Geographic Artificial Intelligence (GeoAI) in urban management and planning. With the rapid growth of spatial data and an increasing demand for precise analyses in urban processes, GeoAI—through the integration of machine learning algorithms, advanced analytical techniques, and three-dimensional visualization—plays a pivotal role in identifying complex patterns and forecasting trends in urban growth and land-use changes. In this study, the foundational concepts and theoretical framework of GeoAI are first delineated, followed by an investigation of its practical applications in enhancing transportation systems, reducing traffic congestion, identifying high-density areas, and managing crises in large metropolitan environments.
The utilization of GeoAI, by merging data derived from remote sensing, Internet of Things (IoT) sensors, and digital mapping technologies, empowers urban managers to access accurate and up-to-date information, thereby facilitating strategic decision-making aligned with sustainable development goals. By simultaneously analyzing spatial and attribute data, this technology effectively uncovers the strengths and weaknesses of existing urban systems and offers optimal solutions for planning and resource management. Moreover, the deployment of GeoAI contributes to reduced operational costs, enhanced efficiency in resource allocation, and overall improvement in the quality of urban services.
The findings of this study indicate that employing Geographic Artificial Intelligence as a transformative tool in urban planning can significantly contribute to the development of smarter, more dynamic, and sustainable cities. In addition to presenting a robust conceptual framework, this paper offers recommendations for further advancement of related technologies and their integration into urban management systems, thereby charting new horizons for improved urban performance.
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