The Journal of Spatial Information Science (JOSIS) is an international, interdisciplinary, open-access journal dedicated to publishing high-quality, original research articles in spatial information science. The journal aims to publish research spanning the theoretical foundations of spatial and geographical information science, through computation with geospatial information, to technologies for geographical information use.
Current Issue: Number 18 (2019)
Discovery of topological constraints on spatial object classes using a refined topological model
Ivan Majic, Elham Naghizade, Stephan Winter, and Martin Tomko
Evaluating existing manually constructed natural landscape classification with a machine learning-based approach
Rok Ciglic, Erik Strumbelj, Rok Cesnovar, Mauro Hrvatin, and Drago Perko
A hidden Markov model for matching spatial networks
Benoit Costes and Julien Perret