A multi-source remote sensing dataset for large-scale forest monitoring

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Authors: Giovanni D’Amico, Davide Botticelli, Giacomo Marcelli, Walter Mattioli, Gherardo Chirici, Elia Vangi, Costanza Borghi, Piermaria Corona, Johannes Schumacher, Johannes Breidenbach, Yang Su, Lauri Mehtätalo
+1 more Saverio Francini
Cited by: 1
References: 14

Abstract

This data article presents a multi-source dataset of satellite-based auxiliary data designed for forest modelling and monitoring. The dataset integrates annual medoid composites derived from Sentinel-1, Sentinel-2, and Landsat imagery, together with spectral indices, Landsat-based 3I3D change metrics, forest mask and forest type layers, and terrain variables derived from the Copernicus GLO-30 DEM, offering comprehensive information on forest cover, spectral behavior, and change metrics. It provides harmonized predictors across seven European countries, ensuring consistency, scalability, and ease of use for researchers developing or validating models to understand forest dynamics and estimate forest-related variables such as biomass or canopy recovery. A curated subset of the dataset is distributed via Zenodo, along with direct public access links to the complete multi-terabyte archive. The data support applications in forest biodiversity conservation, carbon monitoring, biomass modelling, and climate-change impact assessment.

Fields of Study & Subjects

Remote Sensing and LiDAR Applications Remote Sensing in Agriculture Remote-Sensing Image Classification

Publication details

Journal / source
Data in Brief
Volume
67
Pages
112945–112945
Publication date
6 June 2026
Language
EN