AIMC Topic: City Planning

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Geospatial modeling and forecasting of urban land use change using Google Earth Engine and machine learning.

PloS one
Urban expansion and Land Use Land Cover (LULC) change pose critical challenges for sustainable urban planning and risks to food security. This study analyzes multi-temporal Landsat imagery from 1990 to 2020 for five major cities, Islamabad, Karachi, ...

The First Seasonal Green View Index Mapping Dataset across Chinese cities powered by deep learning.

Scientific data
Multi-temporal mapping of the Green View Index (GVI) is crucial for understanding how urban residents perceive seasonal changes in streetscape greenness. Compared to street view imagery (SVI), remote sensing data offers higher temporal frequency and ...

Predictive modelling of land use land cover dynamics for a coastal urban city in Brazil.

Journal of environmental management
Better urban planning depends on assessing how land use and land cover (LULC) have evolved in recent decades and what the prospects are for change in the future. Cities are the result of various factors interacting, and land configuration directly in...

Planning and layout of tourism and leisure facilities based on POI big data and machine learning.

PloS one
The spatial arrangement of tourism cities and the strategic placement of tourism and leisure facilities are pivotal to the development of smart tourism cities. The integration of Point of Interest (POI) data, enriched with location-specific insights,...

Semantic segmentation of urban environments: Leveraging U-Net deep learning model for cityscape image analysis.

PloS one
Semantic segmentation of cityscapes via deep learning is an essential and game-changing research topic that offers a more nuanced comprehension of urban landscapes. Deep learning techniques tackle urban complexity and diversity, which unlocks a broad...

Study of medium and long-term free flow capacity and queue discharge rates on roads.

PloS one
With the rise in vehicle ownership, traffic congestion has emerged as a major barrier to urban progress, making the study and optimization of urban road capacity exceedingly crucial. The research on the medium and long-term free-flowing capacity and ...

Investigating the Association between Streetscapes and Mental Health in Zhanjiang, China: Using Baidu Street View Images and Deep Learning.

International journal of environmental research and public health
Mental health is one of the main factors that significantly affect one's life. Previous studies suggest that streets are the main activity space for urban residents and have important impacts on human mental health. Existing studies, however, have no...

Examining the Relationship between Land Use/Land Cover (LULC) and Land Surface Temperature (LST) Using Explainable Artificial Intelligence (XAI) Models: A Case Study of Seoul, South Korea.

International journal of environmental research and public health
Understanding the relationship between land use/land cover (LULC) and land surface temperature (LST) has long been an area of interest in urban and environmental study fields. To examine this, existing studies have utilized both white-box and black-b...

Characterisation of urban environment and activity across space and time using street images and deep learning in Accra.

Scientific reports
The urban environment influences human health, safety and wellbeing. Cities in Africa are growing faster than other regions but have limited data to guide urban planning and policies. Our aim was to use smart sensing and analytics to characterise the...

Research on Architectural Planning and Landscape Design of Smart City Based on Computational Intelligence.

Computational intelligence and neuroscience
City brain is a complex system, including online center, server network, and system with given algorithm. The core of the city brain is the intelligent system. After putting the urban brain into the intelligent nerve center, on the basis of not chang...