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 …

地图制图学包含地图制作与地图应用两大任务, 分别与人工智能技术有不解之缘.
经历了符号主义智能表达的地图制图专家系统, 行为主义智能表达的空间优化决策后 …

Spatially explicit, fine-grained datasets describing historical urban extents are rarely
available prior to the era of operational remote sensing. However, such data are necessary …

Cartographic representations are subject to sensory perception and rely on the translation of
sensory perceptions into cartographic symbols. In this respect, cartography is closely related …

Topographical maps from the nineteenth century hold significant historical and
environmental value, providing insights into landscape changes over the past two centuries …

Recently, many researchers tried to generate (generalised) maps using deep learning, and
most of the proposed methods deal with deep neural network architecture choices. Deep …

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 …

Schematic maps are popular for representing transport networks. In the last two decades,
some researchers have been working toward automated generation of network layouts (ie …

Administrative regions are fundamental geographic elements on maps, thus making their
detection in map images crucial to enhancing intelligent map interpretation. However …

Propelled by emerging technologies such as artificial intelligence and deep learning, the
essence and scope of cartography have significantly expanded. The rapid progress in …