Development of GeoAI Techniques for Urban Applications

Session Title: 

Development of GeoAI techniques for urban applications

Organized by:

Focus:

This special session focuses on the development of GeoAI techniques for urban applications, including mapping, monitoring, change detection, and spatial analysis. It aims to bring together contributions that advance machine learning, deep learning, and emerging geospatial foundation models to better understand the structure, dynamics, and transformation of urban areas. Particular attention will be given to AI-driven methodological developments, including the design of novel neural network architectures, super-resolution techniques, image analysis methods, and advanced data fusion approaches for integrating multi-source geospatial data, including optical and SAR imagery.

Topics of interest include the automated extraction and vectorization of buildings, roads, and other urban features; building delineation and height estimation; urban morphology characterization; and the monitoring of urban growth, density, green spaces, heat, land use, disasters vulnerability, and environmental conditions. The session will highlight methodological innovations that support practical applications and demonstrate how GeoAI can contribute to urban planning, digital twins, resilience assessment, and evidence-based decision-making in cities.