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Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

EU-Forest, a high-resolution tree occurrence dataset for Europe.

Achille Mauri¹, Giovanni Strona¹, Jesús San-Miguel-Ayanz¹

¹European Commission, Joint Research Centre, Directorate D-Sustainable Resources, Bio-Economy Unit, Via Enrico Fermi 2749, Ispra 21027, Italy.

Scientific Data

|January 6, 2017

Summary

We created EU-Forest, a comprehensive European tree species distribution dataset. This extensive resource significantly expands available data for forestry, conservation, and ecological research.

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Area of Science:

Ecology
Forestry
Environmental Science

Background:

Accurate tree species distribution data is crucial for ecological research and forest management.
Existing datasets on European tree distribution are fragmented and limited in scope.

Purpose of the Study:

To present EU-Forest, a novel dataset integrating and substantially extending European tree species distribution information.
To provide a harmonized, high-resolution dataset beneficial for multiple scientific disciplines.

Main Methods:

Integration of an unpublished database of harmonized forest plot surveys from National Forest Inventories.
Data organized on an INSPIRE-compliant 1 km x 1 km grid, covering approximately 96% of occurrence records.
Extension of publicly available information by nearly an order of magnitude.

Main Results:

The EU-Forest dataset offers an unprecedented scale of European tree species occurrence records.
The dataset is harmonized and spatially explicit, facilitating diverse ecological and forestry applications.
Significant enhancement of available data for biodiversity, bioeconomy, and pest management research.

Conclusions:

EU-Forest represents a major advancement in European tree distribution data availability.
The dataset is poised to support advancements in forestry, biodiversity conservation, palaeoecology, plant ecology, bioeconomy, and pest management.
This resource will enable more robust ecological modeling and informed environmental management strategies.