Robotic monitoring of grasslands: a dataset from the EU Natura2000 habitat 6210* in the central Apennines (Italy)

Published in Research Data
Robotic monitoring of grasslands: a dataset from the EU Natura2000 habitat 6210* in the central Apennines (Italy)

Life on Earth is inevitably tangled to biodiversity preservation. Habitat monitoring is the main tool that human beings have to avoid biodiversity loss. Monitoring consists in the repetitive and continuous evaluation of the habitat conservation status. However, this operation is expensive from both a time and a cost perspective.

Robotics could enhance human monitoring capabilities, and this work makes a first step towards this direction, focusing on the grassland habitat “6210 - Semi-natural grasslands and scrubland facies on calcareous substrates”, which is among the most species-rich habitat in Europe. Specifically, we openly share data collected during monitoring tasks by the quadrupedal robot ANYmal C. The dataset creation has been performed by a team composed of robotic engineers and plant scientists, and it contains information on the robot state, videos, and images acquired during surveys, and a collection of videos and pictures about two typical and one early warning species of habitat 6210.

The data are available open access via the repository Zenodo ( ), and their goal is to push forward robotic habitat monitoring research. From one point of view, computer scientists could employ data gathered by the robot to train or validate their classification algorithms. Alternatively, robot state information or point clouds could be used by engineers to test their methodologies. Finally, plant scientists could exploit these data to propose new metrics or simply check robot performance in monitoring activities.

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Subscribe to the Topic

Research Data
Research Communities > Community > Research Data

Related Collections

With collections, you can get published faster and increase your visibility.

Medical imaging data for digital diagnostics

This Collection presents a series of articles describing annotated datasets of medical images and video. All medical specialities are considered and data can be derived from study participants, tissue samples, electronic health records (EHRs) or other sources.

Publishing Model: Open Access

Deadline: Dec 20, 2023

Ecological data for tracking biological diversity and environmental change

This collection presents data contributions addressing topics in biodiversity and ecology.

Publishing Model: Open Access

Deadline: Jan 31, 2024