Free and open source tools present numerous opportunities to support current urban
planning practice. However, their overview is fragmented, and the uptake among planning …

The past decade has witnessed the rapid development of geospatial artificial intelligence
(GeoAI) primarily due to the ground-breaking achievements in deep learning and machine …

The mapping process generally involves intricate operations, such as symbol design, layout
design, and text annotation, demanding a high level of professional expertise. The high …

The rapid advancement of artificial intelligence (AI) such as the emergence of large
language models including ChatGPT and DALLE 2 has brought both opportunities for …

Abstract Generative Adversarial Network (GAN) is widely used in many generative
problems, including in spatial information sciences and urban systems. The data generated …

This study examines methods of geographic features recognition from historic maps using
CNN and OBIA. These two methods are compared to reveal which one is most suitable to be …

Most image-to-image translation models postulate that a unique correspondence exists
between the semantic classes of the source and target domains. However this assumption …

In recent years, the integration of deep learning technology based on convolutional neural
networks with historical maps has made it possible to automatically extract roads from these …

Machine learning is increasingly used as a computing paradigm in cartographic research. In
this extended editorial, we provide some background of the papers in the CaGIS special …

Recent years have witnessed the development of artificial intelligence (AI) technologies that
are capable of solving a wide range of practical problems. Scholars from cartography and …