Accurately understanding the functions of buildings is crucial for urban monitoring, analysis
of urban economic structures, and effectively allocating resources. Previous studies have …

Artificial intelligence has undergone rapid development in the last thirty years and has been
widely used in the fields of materials, new energy, medicine, and engineering. Similarly, a …

The spatial features and generalisation rules for river network generalisation are difficult to
directly quantify using indicators. To consider dimensional information hidden in river …

GIS and remote sensing techniques were effectively used to analyse the morphometric
parameters including linear, geometric, basin texture (aerial) and relief aspects of the Halda …

Existing research on automatic river network classification methods has difficulty
scientifically quantifying and determining feature threshold settings and evaluating weights …

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 …

Landslide susceptibility assessment (LSA) is vital for landslide mitigation and management.
Existing LSA methods only consider local environmental characteristics associated with …

Landform type recognition presents significant implications for understanding landform
origins, evolutionary mechanisms, and morphological differences. Artificial intelligence (AI) …

Road network simplification is a complex decision-making process. Such a multi-factor
decision and scaling operation traditionally applied rule-based methods. The establishment …

Accurately monitoring soil moisture content (SMC) in the field is crucial for achieving
precision irrigation management. Currently, the development of UAV platforms provides a …