urban

GeoAI and planning

Advancing Urban Planning with GeoAI through Global Street Network Analysis

By Shahabuddin Amerudin Introduction Geographic Artificial Intelligence (GeoAI) integrates Geographic Information Systems (GIS) with artificial intelligence (AI), offering advanced capabilities for urban planning and development. This convergence allows for a more nuanced understanding of spatial dynamics and provides tools to address complex urban challenges. By harnessing GeoAI, urban planners can optimize infrastructure, manage resources more efficiently, and create sustainable urban environments. This article delves into how GeoAI can be applied to enhance city planning by analyzing street network configurations across different global cities. Understanding GeoAI GeoAI represents the intersection of spatial data analysis and AI technologies, including machine learning and […]

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Configurations of street networks in densely populated cities

The Influence of Street Network Configurations on Urban Planning and Population Dynamics

By Shahabuddin Amerudin Introduction Urban planning is a multifaceted discipline that orchestrates the development and organization of cities to optimize functionality, sustainability, and livability. A fundamental component of urban planning is the design and configuration of street networks, which serve as the skeletal framework of urban spaces. Street networks not only facilitate transportation and connectivity but also profoundly influence land use patterns, economic activities, social interactions, and environmental outcomes (Hillier & Hanson, 1984; Marshall, 2005). The interplay between street network configurations and city populations is intricate, reflecting historical contexts, geographical constraints, and evolving urban development philosophies. This article delves into

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boids simulation

Boids Algorithm for Simulating Crowd Movement in Urban Planning and Disaster Management

By Shahabuddin Amerudin Abstract The ability to accurately simulate crowd movement during emergencies is critical in urban planning and disaster management, as it helps design effective evacuation strategies and minimizes the potential for casualties. The Boids algorithm, initially developed to replicate the flocking behavior of birds, provides a versatile framework for modeling the dynamics of crowd movement. This paper explores the application of the Boids algorithm in simulating crowd movement during emergency situations such as floods, analyzing its strengths and limitations. Supported by a comprehensive literature review, this discussion examines the algorithm’s effectiveness in various scenarios, its potential for integration

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