Forestry Real-Life Data Collection Use Case

Soil Mission

Forests are changing faster than we can walk through them.

This RAISE Suite use case pairs drone imaging with ground-level soil sensing to spot early signs of forest stress, turning aerial and field data into an openly shared, FAIR-by-design resource for protecting ecosystems.

At a glance

Pilot Period

M6 – M40

(Feb 2026 – Dec 2028)

Partners Involved
Domain

Forestry / Environmental

Location / Study Sites

Mikrokleisoura Forest, Grevena, Greece (next to Aliakmonas river) 

Participants / Scale
  • 1-2 drone flights/month 
  • Ground-based sensors
  • Sentinel-2 for landscape context​
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Main Goal

To investigate how drone-based multispectral imaging, combined with in-situ soil sensing, can support near real-time monitoring of forest ecosystem health. A DJI Mavic 3M drone conducts 1–2 flights per month over fixed transects, capturing canopy reflectance across five spectral bands to assess vegetation stress, crown condition, and stand density. Continuously operating soil sensors add complementary ground-level data on moisture and nutrient dynamics.

Together, these data streams help screen forest stands for early signs of stress or structural change — prioritising areas for field inspection and informing decisions on ecosystem protection, erosion risk, and sustainable forest management.

Domain Challenges

  • Radiometric consistency: Multispectral reflectance values must stay comparable across flights to detect real ecological change over time.

  • Canopy occlusion: Drones capture only the top of the canopy, leaving stressed trees and soil conditions beneath the overstorey largely invisible.

  • Ground truth scarcity: Remote sensing indices need field validation to be ecologically meaningful — a time-consuming, resource-intensive process.

Keywords

environment, forest, drones, ecosystem

Key Figures & Facts

Study Area

Mikrokleisoura, Grevena, Western Macedonia, Greece

Drone Platform

DJI Mavic 3M: RGB + 5-band multispectral (Blue, Green, Red, Red Edge, NIR)

Flight Frequency: 1-2 missions per month over fixed transects

Datasets
  • Multispectral orthomosaics (5 bands) per flight session
  • Vegetation index rasters (NDVI, NDRE, GNDVI)
  • Continuous soil sensor time series (moisture, temperature)
  • Flight logs and radiometric calibration records
  • All datasets deposited to an open repository under CC BY 4.0
Soil Sensoring

Continuous in-situ monitoring of moisture and nutrient levels

Monitoring period

6-8 months of active data collection

Image Resolution

~5 cm ground sampling distance at 80 m altitude

Use Case Implementation Phases

May–December 2026
Data Collection Without RAISE
A full "business as usual" data collection cycle using existing tools: drone flights with the DJI Mavic 3M over fixed paths, ground-based sensors, and Sentinel-2 satellite data. The cycle concludes with a dataset deposit on Zenodo, establishing the baseline for measuring the impact of RAISE Suite.
May–December 2026
January–March 2027
SDK Integration & RAISE Onboarding
The RAISE Suite SDK is integrated into the pilot's data collection environment. The team onboards to the RAISE Portal, creates a machine-actionable Data Management Plan (maDMP), describes datasets with FAIR-aligned metadata, and connects sensors to the automated data ingestion pipeline.
January–March 2027
From March 2027 onwards
Data Collection with RAISE
The same campaign is repeated, now powered by RAISE Suite: data is captured automatically via the SDK and analysed directly on the RAISE Portal. The cycle ends with the publication of a FAIR-compliant forestry dataset on the RAISE Portal and EOSC, plus a scientific publication on the pilot's results.
From March 2027 onwards

Use Case Outcomes

A Lighter Data Workload

Automated Capture, Less Time and Cost

SDK-based automation captures drone and sensor data directly, cutting the time, storage and manual effort forest data management used to demand.

A Guided FAIR Workflow

One Integrated Toolset, No Expertise Gap

A single RAISE Portal workflow and maDMP replace fragmented tools, making FAIR, interoperable data collection achievable without specialist DMP skills.

An Open, Trusted Dataset

Recognised, Citable and GDPR-Compliant

A published, citable forestry dataset on the RAISE Portal and EOSC turns data sharing into visible, credited and compliant research output.