Machine learning for spatial analyses in urban areas: a scoping review

The challenges for sustainable cities to protect the environment, ensure economic growth, and maintain social justice have been widely recognized. Along with the digitization, availability of large datasets, Machine Learning (ML) and Artificial Intelligence (AI) are promising to revolutionize the way we analyze and plan urban areas, opening new...

Mapping as Gap-Finder: Geddes, Tyrwhitt, and the Comparative Spatial Analysis of Port City Regions

Politicians, planners, and mapmakers have long used mapping to depict selected spaces, to document natural and humanmade changes within them, and to identify spaces where planning intervention is needed or can be helpful. Recent innovations involving big data, GIS-based research and digital datasets offer opportunities for maps and mapping that...

Towards a Comparative Spatial Analysis for Port City Regions Based on Historical Geo-spatial Mapping

Researchers from multiple disciplines study ports and port cities using various forms of visualization. To better understand port cities’ challenges and opportunities, some use mathematical modeling of economic flows or shipping, while others use geo-spatial mapping of land and water territories. In the visualization of port city regions,...