Improving the Monitoring of Europe’s Small Landscape Elements

Improving the Monitoring of Europe’s Small Landscape Elements

17 Oct 2024

Accurate and regularly updated data about Europe's linear and patchy landscape features is vital for many Copernicus users. These small landscape elements, such as hedgerows, ditches, stone walls, and ponds, play a critical role in ecology, culture, and agriculture. As part of the CLMS (Copernicus Land Monitoring Service), EvoLand is leading efforts to enhance the monitoring of these features by developing a new prototype that goes beyond the current Small Woody Features (SWF) product. Using innovative Earth Observation (EO) data, this prototype aims to improve both the accuracy and efficiency of mapping Small Landscape Features (SLF), which are crucial for conservation, climate adaptation, and biodiversity across Europe.

Small Woody Features (SWFs) are an essential part of the European landscape, providing a wide range of benefits, both ecological and cultural. They serve as crucial elements that support four major functions:

  • Soil and water conservation: hedgerows slow water runoff from fields, filtering out pollutants before they reach rivers and streams.
  • Climate protection and adaptation: SWFs have a significant role in flood and landslide mitigation, carbon storage and sequestration.
  • Biodiversity support: SWFs support biological diversity by facilitating the free movement of species between habitats patches, thus providing important services for habitats and ecosystems.
  • Cultural heritage: SWFs compose and structure rural landscapes. They reflect the local agricultural history and provide a large variety of traditional landscapes throughout(?) Europe, thus providing an important cultural value.

Currently, these features are mapped by the CLMS HRL SWF product, updated every three years with a 5-metre spatial resolution. However, other landscape features play vital roles in supporting biodiversity and mitigating climate change: these are ditches, grass margins, stone walls or small ponds. EvoLand’s Small Landscape Features candidate prototype aims at improving the existing SWF product by adding new classes of features and improving spatial resolution of the layer. As indicated by the name of the prototype, these to-be-mapped features are very small elements to be mapped from space.

The existing CLMS HRL SWF product uses Very High Resolution (VHR) Earth Observation imagery to map landscape elements, but it has limitations. Although it represents a significant advancement in mapping trees outside forests, its 5-metre resolution prevents it from capturing smaller elements. This partial mapping does not always meet the needs of users, particularly when dealing with biodiversity indicators or local land management.

Innovations in the EvoLand Prototype

The EvoLand prototype seeks to address these gaps by improving the spatial resolution, making it possible to map smaller elements with greater precision. Adding new classes of landscapes features that also play a role in climate protection and biodiversity support is an important requirement of local and European institutions as they contribute to 3 of the 10 key objectives of the European Common Agricultural Policy (CAP), in particular climate change, environmental care, and landscapes. Existing SWFs are already used as an input to derive CAP biodiversity indicator (CAP I.21), and the relevance of this indicator would be improved with the output of this prototype.

Figure 1: VHR imagery (Bing Virtual Earth)

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Figure 2: CLMS HRL SWF 2018 results (brown: Forested area; green: small woody features)

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Figure 3: EvoLand C6 results (brown: forested areas; green: small woody features; yellow: new class of landscape features)

evoland_SLF

This prototype proposes the following advances to enable the detection of new landscape classes:

  1. Higher Spatial Resolution: Using VHR imagery with improved resolution will allow more precise and complete mapping of woody vegetation in the fields. The prototype will mitigate the current limitations of VHR acquisition frequency by implementing time series of super-resolved Sentinel 2 imagery, thus allowing the identification of new classes. The small features can be identified due to their stability over time compared to the harvest and growth seasons visible in their agricultural “background”.
  2. Use of height data from stereoscopy: this will help distinguish new classes (e.g. ditches vs grass margin).

A two-phase approach for effectively improving the CLMS portfolio

The above-described principles and approaches are currently being implemented, following the two-phase approach by EvoLand. The second development phase began in autumn 2024, taking feedback from first interactions on the usefulness of potentially very challenging detection of natural ponds, for example.

The project will end in December 2025 but the results and details on the achievements of the project will be made publicly available through a results portal in October 2025.

Overall, the Small Landscape Features prototype aims to build on existing CLMS HRL SWF by including new classes and improved spatial resolution through the analysis of new EO datasets. By addressing the limitations of the existing products and adding more detailed information, this EvoLand prototype will provide a more accurate and useful tool for monitoring and managing Europe’s diverse and intricate landscapes.

Would you be interested to follow the results of EvoLand and the development of this candidate prototype? Sign up for our newsletter (here below or via this form), follow us on LinkedIn, Mastodon or X (Twitter).

Questions about the article or the project? E-mail us at contact@evo-land.eu.

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This article is part of a series providing more details on all 11 EvoLand candidate prototypes

Previous article in the series: 

Transforming approaches to forest biomass estimations – EvoLand (evo-land.eu)

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