crstools 1.0.0: an R package for cartographic analyses

Andrea Vittorio Pozzi, Ondrej Pelanek, Cecilia Padilla-Iglesias, Evelyn J. Carter, Michela Leonardi, Aramish Fatima, Nile P. Stephenson, Margherita Colucci, Dominik C. Jud, Cassandra Gunasekaram, Andrea Manica

Spatial analyses are central to ecological studies, underpinning applications ranging from species distribution modelling to conservation planning and macroecological inference. However, most of these require translating processes occurring on a spherical surface into a planar map, inevitably introducing distortion biases. Projection choice can therefore influence both visual interpretation and quantitative results. At the same time, assessing the level of distortion caused by each projection can be a demanding task. Despite the significance of these challenges, existing solutions are often restricted to proprietary software or stand-alone tools, creating friction for transparent and reproducible scientific workflows.
Here we introduce crstools, an R package designed to integrate projection selection, distortion visualisation and image georeferencing within a single reproducible environment. This package provides three core functionalities. First, building on established cartographic guidelines, crstools enables users to automate projection choice based on geographic extent and user-defined distortion preferences. Second, crstools allows users to assess projection-induced distortion by graphical visualisation of Tissot’s indicatrices. Third, an interactive georeferencing workflow enables users to extract coordinates of locations of interest from non-georeferenced images.
By integrating these features within a single R-based framework, crstools reduces reliance on ad hoc graphical interfaces and promotes open, scriptable, and fully reproducible cartographic analyses.