Our article in MEE got accepted “r.pi: a GRASS GIS package for semi-automatic spatial pattern analysis of remotely sensed land cover data” by Martin Wegmann, Benjamin Leutner, Markus Metz, Markus Neteler, Stefan Dech, Stefan and Duccio Rocchini. It outlines the capabilities of the r.pi package to analyze spatial patterns derived from remote sensing land cover data to inform about landscape conditions and changes. Such fragmentation measures are relevant for ecology or conservation as well as for remote sensing to produce value-added landcover maps that provide details on the spatial structure of the landscape.
New publication: Mapping animal paths using drones and deep learning
We're pleased to share our latest open-access research on automatically detecting animal paths in Africa's Kruger National Park using drone imagery and deep learning. Published in Ecological Informatics, our study demonstrates how deep learning can be employed to...








