Pan-European monitoring of local forest fragmentation : algorithm theoretical basis document (ATBD).
Date: 2025-08-20
Institutions: Joint Research Centre
Subjects: biodiversity, earth observation, ecosystem, environmental monitoring, forest, forestry research, remote sensing, research report

ISSN 1831-9424 

Pan-European monitoring of local forest 
fragmentation 

Algorithm Theoretical Basis Document (ATBD) 

Vogt, P., Caudullo, G. 

2025 

 EUR 40413 

This document is a publication by the Joint Research Centre (JRC), the European Commission’s science and knowledge 
service. It aims to provide evidence-based scientific support to the European policymaking process. The contents of this 
publication do not necessarily reflect the position or opinion of the European Commission. Neither the European 
Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this 
publication. For information on the methodology and quality underlying the data used in this publication for which the 
source is neither Eurostat nor other Commission services, users should contact the referenced source. The designations 
employed and the presentation of material on the maps do not imply the expression of any opinion whatsoever on the 
part of the European Union concerning the legal status of any country, territory, city or area or of its authorities, or 
concerning the delimitation of its frontiers or boundaries. 

Contact information 
Name: Peter Vogt  
Address: TP261, Via Fermi, 21027 Ispra (VA), Italy 
Email: peter.vogt@ec.europa.eu 
Tel.: +39 0332 78 5002 

EU Science Hub 
https://joint-research-centre.ec.europa.eu 

JRC143248 

EUR 40413 

PDF  

ISBN 978-92-68-31066-3   ISSN 1831-9424   doi:10.2760/8260743  

KJ-01-25-411-EN-N 

Luxembourg: Publications Office of the European Union, 2025  

© European Union, 2025  

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How to cite this report: Vogt, P. and Caudullo, G., Pan-European monitoring of local forest fragmentation - Algorithm Theoretical Basis 
Document (ATBD), Publications Office of the European Union, Luxembourg, 2025, https://data.europa.eu/doi/10.2760/8260743, JRC143248. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

Abstract ...................................................................................................................................................................................................... 2 

Foreword .................................................................................................................................................................................................... 3 

Acknowledgements .............................................................................................................................................................................. 4 

1.  Introduction ....................................................................................................................................................................................... 5 

2.  Implementation summary......................................................................................................................................................... 8 

2.1.  Input data source ................................................................................................................................................................. 8 

2.1.1.  HRL-FTY forest cover ........................................................................................................................................... 8 

2.1.2.  CLC+ land cover ...................................................................................................................................................... 8 

2.1.3.  GISCO country layers ........................................................................................................................................... 9 

2.2.  Forest fragmentation ..................................................................................................................................................... 10 

2.3.  Reporting units ................................................................................................................................................................... 10 

2.4.  Implementation flowchart ........................................................................................................................................... 12 

2.5.  Example: Austria................................................................................................................................................................ 13 

3.  Discussion........................................................................................................................................................................................ 15 

4.  Conclusions ..................................................................................................................................................................................... 16 

References ............................................................................................................................................................................................. 17 

List of abbreviations and definitions ...................................................................................................................................... 18 

List of figures ....................................................................................................................................................................................... 20 

List of tables ......................................................................................................................................................................................... 21 

Annexes ................................................................................................................................................................................................... 22 

Annex 1. File hierarchy and data format ....................................................................................................................... 22 

1 

 
 
Abstract 

This document describes the design process, definitions, and algorithmic implementation for a pan-
European assessment of forest fragmentation. This study is a preceding presentation of the 
indicator 4.7 in the State of Europe’s Forests 2025 report, published by FOREST EUROPE. Forest 
cover is derived from the Copernicus High Resolution Forest Type dataset for the year 2021 at a 
spatial resolution of 10 meters. Forest fragmentation is assessed within a local neighbourhood of 
500 hectare. Spatially explicit maps and statistical summaries are derived for 44 reporting units: 
the entire map coverage, European regions, the EU27, and the EEA38 countries. 

2 

 
 
Foreword 

This publication is a technical report by the Joint Research Centre (JRC), the European Commission’s 
science and knowledge service. It aims to provide evidence-based scientific support to the European 
policymaking process. The scientific output expressed does not imply a policy position of the 
European Commission. Neither the European Commission nor any person acting on behalf of the 
Commission is responsible for the use that might be made of this publication. For information on 
the methodology and quality underlying the data used in this publication for which the source is 
neither Eurostat nor other Commission services, users should contact the referenced source. The 
designations employed and the presentation of material on the maps do not imply the expression of 
any opinion whatsoever on the part of the European Union concerning the legal status of any 
country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or 
boundaries. 

3 

 
 
 
Acknowledgements 

Special thanks go to Bernhard Wolfslehner and Andrzej Talarczyk from the FOREST EUROPE Liaison 
Unit Bonn for the fruitful discussions and providing feedback during the development and 
implementation phase of this study. Many thanks to the JRC BDAP team for providing computing 
resources to process very large datasets. 

Authors 

Peter Vogt (JRC, D1) 

Giovanni Caudullo (Arcadia SIT s.r.l.) 

4 

 
 
 
 
 
 
 
1.  Introduction 

Forest area and its fragmentation is a key aspect in biodiversity, ecosystem services and the ever-
increasing pressure from anthropogenic land use. Forest fragmentation may lead to the isolation 
and loss of species and gene pools, degraded habitat quality, and a reduction in the forest’s ability 
to sustain the natural processes necessary to maintain ecosystem health. Connectivity can be seen 
as the complement to fragmentation, for example, if a forest is not fragmented at all, it would be 
fully connected. The metric FAD (Forest Area Density) quantifies the degree of connectivity within 
forested land cover. It describes structural connectivity within forest cover and can be derived at 
any suitable analysis scale, which is defined by the size of the local neighbourhood of interest. The 
result of a FAD analysis is a spatially explicit map and tabular summary statistics. At international 
level, the metric FAD was adopted in the US sustainability reporting under the international 
Montréal Process1 (Riitters & Robertson, 2021), the United States Resource Planning Act 
Assessment2, the FAO-UNEP SOFO 20203 report (Vogt et al. 2019a) and by Forest Europe in the 
State of Europe’s Forests 20204 report (Vogt et al. 2019b). Within European Union (EU) policy, the 
indicator was used to measure forest connectivity, or its complement fragmentation, in the MAES5 
project (Maes et al. 2020, Maes et al. 2023), the EU Observatory on Deforestation and Forest 
Degradation6 (Vogt & Caudullo 2022b), the DOPA EU Biodiversity Strategy Dashboard7, the Eurostat 
Regional Yearbook 20228 (Vogt & Caudullo 2022a). Finally, the metric FAD has been adopted into 
the EU policy programs 8th Environment Action Programme (8EAP)9 (indicator 11) and the Nature 
Restoration Regulation (NRR)10 (Annex VI), which is integral to the European Green Deal11, the EU 
Biodiversity Strategy12, and the EU Forest Strategy13.  

FOREST EUROPE (hereafter FE), also known as the Ministerial Conference on the Protection of 
Forests in Europe, is a Pan-European voluntary high-level forest policy process. Since 1990, the aim 
has been to develop common strategies for the 45 signatories (44 European countries and the EU) 
on how to protect and sustainably manage forests. FE achieves this task via a set of criteria and 
indicators, that are internationally regarded as guidelines for sustainable forest management. Every 
five years, FE publishes a flagship report on the State of Europe’s Forests (SoEF). SoEF2020 was the 
first report to include a dedicated indicator on forest fragmentation (indicator 4.7), derived via the 
metric FAD (Vogt et al. 2019b). For the upcoming SoEF2025 report, and after discussions with the 
FE Liaison Unit Bonn, the indicator 4.7 was refined to comply with the following key findings (KF): 

1  
2  
3  
4  
5  
6  
7  
8  
9  
10  
11  
12  
13  

https://montreal-process.org  

https://research.fs.usda.gov/treesearch/66413  

https://www.fao.org/documents/card/en/c/ca8642en  

https://foresteurope.org/wp-content/uploads/2016/08/SoEF_2020.pdf  

https://www.eea.europa.eu/themes/biodiversity/mapping-europes-ecosystems  

https://forest-observatory.ec.europa.eu/  

https://dopa.jrc.ec.europa.eu/kcbd/EUBDS2030-dashboard/indicators/1.1.0.1.3.1/?version=1  

https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Eurostat_regional_yearbook  

https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=COM%3a2022%3a357%3aFIN  

https://eur-lex.europa.eu/eli/reg/2024/1991/oj  

https://eur-lex.europa.eu/EN/legal-content/summary/european-green-deal.html  

https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3a52020DC0380  

https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3a52021DC0572  

5 

 
 
 
—  KF1 - Data source: use Copernicus High Resolution Forest Type (HRL-FTY) raster data.  

Motivation: At this point of time, FTY is one of the most UpToDate and freely available 
European forest cover datasets. FTY are the only pan-European spatially consistent and 
seamless, detailed forest cover maps employing a harmonized method throughout Europe for 
the time series 2018 to 2021. In addition, the spatial resolution of 10 m allows for capturing 
and analysing fine-scale detail impacting fragmentation such as roads, railway tracks, power 
lines and streams. This detail is a notable improvement over the 100 m CORINE (CLC) land 
cover data that was used in the previous SoEF2020 report. The FTY map covers all EEA38 
countries and is displayed in the FTY data viewer. Please note that the earlier FTY editions of 
2015 and 2012 could not be used because they are not compatible with the 2018 and 2021 
datasets due to different processing and different spatial resolution.  

—  KF2 - Definition of Forest: the FTY map distinguishes between deciduous and broadleaved 

forest cover and follows the FAO-definition of forest. The two types are merged to define forest 
cover.  

Motivation: while the FAO-definition of forest may not be compliant with national forest 
definitions it provides a meaningful and congruent base line for a consistent forest 
fragmentation assessment across the EU. This decision is an improvement over the CLC-based 
forest definition used in the SoEF2020 report because the FAO-definition is widely accepted 
and used for international reporting on forests. 

—  KF3 – Methodology: the method “Forest Area Density” (FAD) at Fixed Observation Scale (FAD-
FOS) was selected to best match the fragmentation assessment requirements stipulated by 
FOREST EUROPE. 

Motivation: FAD is a widely accepted metric for forest fragmentation assessments. It is used 
by various international and national organisations and included in EU policy legislation. The 
same methodology was also used in the SoEF2020 report. 

—  KF4 - Analysis scale: a scale of ~ 500 hectare (ha) was selected. 

Motivation: fragmentation is scale-dependent, and each scale has its merit. In the SoEF2020 
report, an analysis scale of 500 ha was used, a decision taken by a Forest Europe lead pilot 
study and using the lower resolution 100 m CLC data. For consistency, we use the same 
analysis scale, which with the 10 m resolution FTY data translates into a moving window size of 
223 x 223 pixels (= 2230 x 2230 m), or a local neighbourhood of 497.29 ha for the FAD metric. 
Please note that in contrast to the lower resolution CLC data, the much higher resolution FTY 
data captures many fine-scale features such as roads, railway tracks, power lines and streams, 
leading to a more realistic assessment but consequently also to an increase in the degree of 
fragmentation when compared to the lower resolution CLC data used in the SoEF2020 report. 

—  KF5 - Fragmentation product: the default FAD 5-class reporting style was selected.  

6 

 
 
 
 
 
 
Motivation: The degree in forest fragmentation is reported in five classes14 : Very High, High, 
Medium, Low, Very Low. The spatial map shows the degree in fragmentation within the local 
neighbourhood of 500 ha around each forest pixel. The statistical summary lists the forest 
proportion in each fragmentation class and two single summary indices: FADAV - the average 
connectivity within the forest cover, and AVCON - the average connectivity within the reporting 
unit. These five fragmentation classes and their statistical summaries are intuitive to 
understand and easy to communicate. Because the georeferenced maps are in equal area 
projection the derived statistics provide forest area and fragmentation statistics in percentage 
as well as actual area in hectares, allowing for a comparative analysis across Europe. 

—  KF6 - Reporting units: the indicator 4.7, with spatial maps and summary statistics, is derived 

for the following 44 reporting units: FTY; EU27 (European Union Member States); five 
geographic regions reported in SoEF2020 and covered by FTY (North Europe, Central-West 
Europe, Central-East Europe, South-West Europe, South-East Europe), and each of the 38 
countries covered by FTY. 

Motivation: this reporting approach is consistent with SoEF2020 and allows for comparisons 
across the entire European continent. 

—  KF7 - Trends: statistics on temporal trends of forest fragmentation are not considered. 

Motivation: the short 3-year time span of the dataset from 2018 to 2021 is not suitable to 
reliably detect changes in forest cover. In particular, the detection of forest gain requires a 
longer time span to be detected from satellite-based observations. 

14  

https://ies-ows.jrc.ec.europa.eu/gtb/GTB/psheets/GTB-Fragmentation-FADFOS.pdf  

7 

 
 
 
 
 
 
2.  Implementation summary 

This section provides an overview of the data source used, necessary pre-processing steps, details 
on the algorithms applied, details on the output format and other documentary information on the 
status product of the indicator 4.7. The status maps and statistics for the year 2021 are available 
on the JRC public data portal (https://jeodpp.jrc.ec.europa.eu/ftp/jrc-
opendata/FOREST/FAL/FE2025_4.7/). 

2.1.  Input data source 

The pan-European assessment of forest fragmentation requires three basemaps: a) the Copernicus 
HRL-FTY forest cover map, b) the CLC+ land cover map, from which the land/sea mask will be 
derived, and c) the GISCO map of country boundaries, needed for clipping out the individual 
reporting units.  

2.1.1.  HRL-FTY forest cover 

The HRL-FTY forest cover raster map provides the two tree types broadleaved and coniferous at a 
spatial resolution of 10 m. It is important to note that the FTY excludes tree cover with a density of 
less than 10%, trees located in urban areas or under agricultural use, and group of trees smaller 
than 0.5 ha. These settings were applied to retrieve a tree cover map that is compliant with the FAO 
forest definition. The two tree type classes are merged to form the forest cover map. Because the 
FTY map provides no clear coastline, which is required to derive the reporting unit area, the 
rectifying information is obtained from the CLC+ land cover map of the respective year. 

2.1.2.  CLC+ land cover 

The CLC+ land cover raster maps identify 11 land cover classes at a spatial resolution of 0.01 ha 
per pixel (10 x 10 m) over Europe for a series of assessment years and identical geospatial 
information as the FTY maps. Further details on CLC+ are available in the technical documents 
available on the 2021 (doi) land cover dataset website. 

The European mainland part of the 2021 CLC+ land cover dataset (V1_1, equal-area projection 
LAEA, EPSG:3035) were downloaded  as a single GeoTIFF formatted file of size 650,000 x 460,000 
pixels. The map is in data type Byte and contains 11 land cover classes [1, 11], the class 253 
(coastal seawater buffer), 254 (outside area), and 255 (no data). Using GWB_REC all pixels in the 
classes outside area, coastal seawater, and nodata were assigned to the value 0. All CLC+ land 
cover classes but Inland water are assigned the value 1, the CLC+ class Inland Water the value 3, 
and all forest pixels of FTY are added to this map with a value of 2. The resulting map maintains all 
forest information of FTY but shows an improved land/sea mask compared to FTY, in compliance 
with KF1 and KF2. 

8 

 
 
 
 
 
Figure 1. Comparison of original FTY, derived forest map, and CLC+ in Finland.  

Source: JRC, 2025  

Figure 1 shows a comparison of the original FTY map, the derived forest map, and the CLC+ map 
for an example area in Finland. Compared to the original FTY, the forest map now shows all FTY 
forest cover but with a proper land/sea mask. The two highlighted areas in the CLC+ land cover map 
show brown-coloured pixels of the CLC+ class 5 ‘Low-growing woody plants’. But only in one case 
are they classified in FTY as forest. This example suggests that FTY is more suited to map forest 
compared to grouping CLC+ land cover classes. 

2.1.3.  GISCO country layers 

Providing maps and statistics for individual reporting units (countries or European regions) requires 
masking and clipping the European-wide map to the region of the reporting unit. This process 
requires selecting the country boundary outline of a given reporting unit. Eurostat’s GISCO 
(Geographic Information System of the Commission) provides official vector layers of country 
boundaries. The current version 2024 at a scale of 1:100,000 was rasterised to a 10 m map, 
matching the geospatial attributes of the forest map. In addition, the coastlines of all countries 
were extended into the sea to include the Exclusive Economic Zone15 (up to 200 nautical miles from 
the actual coastline). Intersecting this so-extended territorial mask to the CLC+ derived forest mask 
ensures to capture all land cover pixels of a given country regardless of spatial shifts along and in 
the vicinity of the costal boundaries. 

Kosovo: within the context of this analysis, Kosovo (under United Nations Security Council 
Resolution 1244) is not listed separately but is a part of Serbia. 

15  

https://en.wikipedia.org/wiki/Exclusive_economic_zone  

9 

 
 
 
 
 
 
2.2.  Forest fragmentation 

The methodology (KF3) to measure forest fragmentation applies the metric FAD (Forest Area 
Density), defined as the area of all forest pixels in the local neighbourhood divided by the 
neighbourhood area, hence area density. FOS measurements (FOS = FAD at Fixed Observation 
Scale) are conducted via a moving window algorithm to create a new map of FAD: the given 
neighbourhood - a square window of size 223x223 pixels ~ 500 ha (KF4) - is centred over a given 
forest pixel, FAD within that neighbourhood is measured and assigned in a new map at the location 
of the subject forest pixel. This process is repeated for all forest pixels resulting in a new map of 
the same dimensions but showing FAD for the analysed neighbourhood. For each forest pixel, the 
FAD values in [0, 100] % are colour-coded into five classes (KF5) showing the degree of forest 
fragmentation as: Very High (FAD in [0, 10] %), High (FAD in [10, 40] %), Medium (FAD in [40, 60] 
%), Low (FAD in [60, 90] %), and Very Low (FAD in [90, 100] %). 

The statistical summary of a forest fragmentation map lists: the reporting unit area, forest area, 
forest proportion, the proportion of forest cover in the five fragmentation classes, FADAV - the 
average connectivity within the forest cover, and AVCON - the average connectivity within the 
reporting unit. 

2.3.  Reporting units 

The EU-wide fragmentation map was cut into several reporting units (KF6, Table 1) and each 
reporting unit received its dedicated statistical summary. 

Table 1. Forest fragmentation reporting units 

Number  Code  Name 1 

ALB 

Albania 

AUT 

Austria 

BEL 

Belgium 

BGR 

Bulgaria 

Member 

Albania 

Austria 

Belgium 

Bulgaria 

BIH 

Bosnia and Herzegovina 

Bosnia and Herzegovina 

CHE 

Switzerland 

Switzerland 

CYP 

Cyprus 

CZE 

Czechia 

DEU 

Germany 

DNK 

Denmark 

ESP 

Spain 

EST 

Estonia 

EUR 

EU-27 

Cyprus 

Czechia 

Germany 

Denmark 

Spain 

Estonia 

Austria, Belgium, Bulgaria, Croatia, Cyprus, 
Czechia, Denmark, Estonia, Finland, France, 

10 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

 
 
Number  Code  Name 1 

Member 

14 

FEA 

FE North Europe 

15  

FEB 

FE Central-West Europe 

16 

FEC 

FE Central-East Europe 

17 

FED 

FE South-West Europe 

18 

FEE 

FE South-East Europe 

Germany, Greece, Hungary, Ireland, Italy, 
Latvia, Lithuania, Luxembourg, Netherlands, 
Poland, Portugal, Romania, Slovakia, 
Slovenia, Spain, Sweden 

Denmark, Estonia, Finland, Iceland, Latvia, 
Lithuania, Norway, Sweden 

Austria, Belgium, France, Germany, Ireland, 
Liechtenstein, Luxembourg, Netherlands, 
Switzerland, United Kingdom 

Czechia, Hungary, Poland, Romania, 
Slovakia 

Andorra, Holy See, Italy, Malta, Monaco, 
Portugal, Spain 

Albania, Bosnia and Herzegovina, Bulgaria, 
Croatia, Cyprus, Greece, Montenegro, North 
Macedonia, Serbia, Slovenia, Türkiye 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

31 

32 

33 

34 

35 

36 

37 

FIN 

Finland 

FRA 

France 

Finland 

France 

FTY 

HRL-FTY 

FTY map extent 

GRC 

Greece 

HRV 

Croatia 

HUN 

Hungary 

IRL 

Ireland 

ISL 

Iceland 

ITA 

Italy 

Greece 

Croatia 

Hungary 

Ireland 

Iceland 

Italy 

LIE 

Liechtenstein 

Liechtenstein 

LTU 

Lithuania 

Lithuania 

LUX 

Luxembourg 

Luxembourg 

LVA 

Latvia 

Latvia 

MKD  North Macedonia 

North Macedonia 

MLT  Malta 

MNE  Montenegro 

NLD 

Netherlands 

NOR  Norway 

POL 

Poland 

Malta 

Montenegro 

Netherlands 

Norway 

Poland 

11 

 
Number  Code  Name 1 

38 

39 

40 

41 

42 

43 

44 

PRT 

Portugal 

ROU 

Romania 

SRB 

Serbia 

SVK 

Slovakia 

SVN 

Slovenia 

SWE 

Sweden 

TUR 

Türkiye 

Member 

Portugal 

Romania 

Serbia 

Slovakia 

Slovenia 

Sweden 

Türkiye 

Forest Europe (FE) Regions follow the SoEF2020 definition (page 249) and contained in FTY coverage. 

1 
Source: Soef2020 and JRC, 2025 

2.4.  Implementation flowchart 

Figure 2 provides an overview of the processing chain to derive the forest fragmentation maps and 
statistics. The top panel (a) shows the setup of the forest mask, the central panel (b) the derivation 
of forest fragmentation, and the bottom panel (c) the segmentation into the 44 reporting units. The 
source code for pre- and post-processing steps (fe2025.pro in the IDL language) and all output 
maps and statistics are provided in a single directory FE2025_4.7. Further details on the individual 
processing steps are summarised in the Annex or directly in the script fe2025.pro.  

Figure 2. Flowchart to derive forest fragmentation maps and statistics.  

Source: JRC, 2025  

The IDL-script fe2025.pro has the following sections to conduct the individual processing steps: 

—  Step1: setup FTY2021 forest map with proper coastlines and inland water. 

12 

 
 
 
—  Step_2: use GWB_FRAG to do the fragmentation analysis. 

—  Step_3a: extract EUR: the EU27 member states. 

—  Step_3b: extract FEA: the FE category "North Europe". 

—  Step_3c: extract FEB: the FE category "Central-West Europe". 

—  Step_3d: extract FEC: the FE category "Central-East Europe". 

—  Step_3e: extract FED: the FE category "South-West Europe". 

—  Step_3f: extract FEE: the FE category "South-East Europe". 

—  Step_3g: extract the individual EEA38 reporting units. 

—  Step_4: build statistical summary for each reporting unit. 

Details on the file hierarchy and the input and output file data assignments are summarised in the 
Annex at the end of this document. 

2.5.  Example: Austria 

This section exemplifies the results of the fragmentation analysis for the reporting unit Austria. A 
zoom in on the region east of Vienna airport Schwechat (Figure 3) shows the fine-scale detail 
mapped in the FTY forest cover map.  

Figure 3. Forest fragmentation east of Vienna airport Schwechat.  

Source: GoogleMaps (retrieval date: 07/07/2025); JRC, 2025. 

13 

 
 
 
 
For example, the dissection of forest by the motorway A4, small streams north and south of the 
Danube river, and even a cycle path running north of the Danube river through forest cover. The 
bottom part of the figure shows the statistical summary for the entire reporting unit Austria. The 
summary statistics lists the area of the reporting unit (LAND), the forest area (FAREA), the 
proportion of forest cover within the reporting unit (FCOVER), the proportion of the total forest area 
in the five fragmentation classes (Very High to Very Low), the average degree of connectivity within 
the forest cover (FADAV), and the average degree of connectivity within the reporting unit (AVCON).  

The map and summary statistics are complemented by a histogram of forest fragmentation. This 
chart provides insights into the distribution of forest fragmentation across the entire forest cover 
within a reporting unit, for example Austria, Belgium, and Ireland in (Figure 4). The histogram 
reveals that Austria's forest cover is predominantly characterized by Medium and Low 
fragmentation. In contrast, Belgium exhibits a more uniform distribution across all fragmentation 
classes. Ireland shows a distinct prevalence of Very High and High fragmentation. 

Figure 4. Fragmentation histogram of Austria, Belgium, and Ireland.  

Source: JRC, 2025. 

In the summary table of all 44 reporting units’ statistics can be sorted for various aspects. For 
example, by sorting by 'AVCON' (average connectivity within the reporting unit), Slovenia is 
identified as having the highest overall connectivity at 47.55%. With 35.42% Bulgaria has the 
highest proportion of forest cover in the fragmentation class Very Low (Figure 5). The highest 
proportion of forest cover is found for Finland (63.61%), while Sweden has the largest forest area 
of the 38 EEA countries. 

Figure 5. Extract of the statistical summary table, sorted by the fragmentation class ‘Very Low’.  

Source: JRC, 2025. 

14 

 
 
 
 
3.  Discussion 

The aim of this study was to conduct a pan-European assessment of forest fragmentation for the 
upcoming 2025 edition of Forest Europe’s State of Europe’s Forests report. Because forest 
fragmentation is a spatial feature, it must be derived from contiguous spatial coverage. Within this 
scope, and after discussions with the FE Liaison Unit Bonn, we selected the most recent Copernicus 
HRL-FTY forest cover dataset of 2021. This dataset applies the FAO-definition of forest excluding 
agricultural and urban trees and applying a minimum mapping unit of 0.5 ha. While this definition is 
widely accepted and serves as a general reference it may not be compliant with the definition of 
forest stipulated by the individual countries in Europe. What is a forest by CMA Hendriks from the 
EEA’s FISE project provides insights into the various forest definitions in Europe. Similarly, the 
European Forest Institute (EFI) has published a summary of national forest definitions, which shows 
the variety of criteria and threshold values used to define forest at national level.  

An additional issue is the reporting of land use versus land cover. Satellite-derived data typically 
show the de-facto status of forest cover, accounting for and mapping temporally cleared forest 
areas due to harvesting, forest fires, storms, or insect infestations. In contrast, these forest 
clearings are not accounted for in land use reporting, where forest area is assigned to the intended 
land use, regardless of the actual conditions. Because national reporting is based on land use, 
satellite-derived forest cover estimates are typically lower than the forest area reported in national 
documents. For example, according to the Austrian Forest Report 2023, the forest area in Austria 
was 4,015,000 ha while our satellite-derived assessment for 2021 list 3,696,500 hectares. 
Regardless of these constraints, and with the FAO-definition being the only internationally accepted 
common forest definition, satellite-derived forest mapping is likely the only feasible solution for a 
consistent and comparable pan-European assessment of forest fragmentation. In this regard, the 
Copernicus HRL-FTY data used in this report is the most UpToDate, consistent, suitable, and publicly 
available dataset at this time.  

The spatially explicit map and the tabular summary statistics are complemented by a histogram, 
providing summary details on the degree of fragmentation within the forest cover. The histogram 
shows how much of the forest area in a reporting unit falls into which degree of fragmentation. 
Compared to the 5-class summary statistics, the histogram provides full details on the distribution 
of forest fragmentation within the total forest area. It allows comparing fragmentation across 
different reporting units and provides more details for a better assessment of temporal changes, 
once suitable data will become available. For example, a statistical summary index is just the 
average value and may not change for two points in time. However, this same average value can be 
obtained by different distributions of forest fragmentation, a feature that is not captured in 
summary statistics but will become visible in the histogram.  

15 

 
 
 
 
 
 
 
4.  Conclusions  

This report describes a methodology to map and quantify forest fragmentation for the indicator 4.7 
in the upcoming SoEF2025 report. The fragmentation product is composed of three parts: the 
spatially explicit map, the histogram, and the tabular summary statistics. The conceptual design 
assures to simultaneously consider key aspects of fragmentation including, the amount of forest, 
perforations inside forest patches, patch shape and linear features, and the proximity of individual 
forest patches. The accuracy of the derived status data is directly related to the accuracy of the 
input data used, which is documented and quantified in the HRC-VLCC ATBD and the product user 
manual. Evidently, these specifications may differ from official national statistics on the forest area 
obtained by other means. In this context, the results of this study can only be indicative but are 
consistent across the pan-European assessment area. 

The map product provides information on spatial position and local intensity of forest 
fragmentation. The map is the key product from which any other summary is derived. Maps are 
needed to locate hotspots, monitor progress, and quantify temporal evolution at any geospatial 
location. They also form the prerequisite for any policy planning, allowing to uncover where forest 
management measures are most suitable, or to prioritise regions for restoration measures. Any 
geospatial question can be answered from a map product only: 

—  Where are forests and what is their degree of fragmentation? 

—  Where in the reporting unit are small/large forest patches? 

—  Where are forest patches close to each other? 

The tabular summary statistics provide a concise and comparative overview allowing to answer 
essential quantitative assessment questions: 

—  Which reporting unit has the highest contribution in a specific fragmentation class? 

—  Which reporting unit has the highest degree in overall connectivity (AVCON)? 

—  Which reporting unit has the highest area of forest cover (FAREA) or forest proportion (FCOVER)? 

The above, and other similar questions, can be easily addressed by using the filter function in the 
summary spreadsheets forest_stats2021_FTY.xslx. 

16 

 
References 

Maes, J., Teller, A., Erhard, M., Condé, S., Vallecillo, S. et al. Mapping and Assessment of Ecosystems 
and their Services: An EU ecosystem assessment, EUR 30161 EN, Publications Office of the 
European Union, Ispra, 2020, ISBN 978-92-76-17833- 0, JRC120383, 
https://doi.org/10.2760/757183  

Maes, J., Bruzón, A.G., Barredo, J.I., Vallecillo, S., Vogt, P., et al. ‘Accounting for forest condition in 
Europe based on an international statistical standard’. Nature Communications, Volume 14, 3723, 
2023, https://doi.org/10.1038/s41467-023-39434-0 

Riitters, K., Robertson, G. ‘The United States Implementation of the Montréal Process Indicator of 
Forest Fragmentation’. Forests, 2021, 12(6), 727, https://doi.org/10.3390/f12060727  

Vogt, P., Riitters, K., Caudullo, G., and Eckhardt, B., (2019a). FAO – State of the World’s Forests: 
Forest Fragmentation, EUR 29972 EN, Publications Office of the European Union, Luxembourg, 
2019, ISBN 978-92-76-13036-9, JRC118594, https://doi.org/10.2760/145325  

Vogt, P., Riitters, K., Caudullo, G., Eckhardt, B., and Rǎsi, R., (2019b). An approach for pan-European 
monitoring of forest fragmentation, EUR 29944 EN, Publications Office of the European Union, 
Luxembourg, 2019, ISBN 978-92-76-10374-5, JRC118541, https://doi.org/10.2760/991401   

Vogt, P., Riitters, K., Rambaud, P., d’Annunzio, R., Lindquist, E., Pekkarinnen, A. ‘GuidosToolbox 
Workbench: spatial analysis of raster maps for ecological applications’. Ecography, 2022:e05864, 
2022, https://doi.org/10.1111/ecog.05864  

Vogt, P. and Caudullo, G. (2022a). EUROSTAT – Regional Yearbook 2022: Forest Connectivity, EUR 
31072 EN, Publications Office of the European Union, Luxembourg, 2022, ISBN 978-92-76-52435-
9, JRC129266, https://doi.org/10.2760/838111  

Vogt, P. and Caudullo, G. (2022b). Global analysis of forest attribute layers for the EU Observatory 
on Deforestation and Forest Degradation, Publications Office of the European Union, Luxembourg, 
2022, JRC130494, https://doi.org/10.2760/41048  

17 

 
 
 
List of abbreviations and definitions 

Abbreviations 

Definitions 

8EAP 

ATBD 

AVCON 

BDAP 

CLC 

CLC+ 

EEA 

EEA38 

EIONET 

EFI 

EU 

EU27 

FAO 

FAD 

FADAV 

FE 

FISE  

8th Environment Action Programme 

Algorithm Theoretical Basis Document 

Average connectivity within the reporting unit 

JRC Big Data Analytics Platform 

CORINE land cover 

CLCplus Backbone land cover 

European Environment Agency 

EIONET countries 

European Environment Information and Observation 
Network 

European Forest Institute 

European Union 

European Union 27 member states 

Food and Agriculture Organization of the United Nations 

Forest Area Density 

Average connectivity across all forest pixels 

Forest Europe 

Forest Information System for Europe 

FTY (or HRL-FTY) 

Forest Type 

GIS 

GWB 

Geographic Information System 

GuidosToolbox Workbench 

18 

 
Abbreviations 

Definitions 

HRL 

JRC 

LAEA 

NRR 

Copernicus High Resolution Layer 

European Commission Joint Research Centre 

Lambert Azimuthal Equal Area projection 

Nature Restoration Regulation 

19 

 
 
 
List of figures 

Figure 1. Comparison of original FTY, derived forest map, and CLC+ in Finland. ........................................... 9 

Figure 2. Flowchart to derive forest fragmentation maps and statistics. ........................................................ 12 

Figure 3. Forest fragmentation east of Vienna airport Schwechat. ..................................................................... 13 

Figure 4. Fragmentation histogram of Austria, Belgium, and Ireland. ............................................................... 14 

Figure 5. Extract of the statistical summary table, sorted by the fragmentation class ‘Very Low’. . 14 

20 

 
 
List of tables  

Table 1. Forest fragmentation reporting units ................................................................................................................. 10 

21 

 
 
Annexes 

Annex 1. File hierarchy and data format 

This section describes the file hierarchy and output formats in the various sub-directories of the 
base directory FE2025_4.7. Files are shown in italics and directories in bold.  

—  2021: fragmentation product for each reporting unit and year. 

•

•

<iso3-code><year>_fad5_223_tif: GeoTIFF map of reporting unit.

<iso3-code><year>_fad5_223_png: histogram chart of reporting unit.

—  fe2025.pro: IDL program (source code) for pre- and post-processing, providing step-by-step 

instructions on the individual processing methodologies. 

—  forest_stats2021_FTY.xslx: tabular fragmentation summary statistics. 

—  hrlwcolors.sav: colour table used by fe2025.pro. 

Note: to keep the file size of the base-directory FE2025_4.7 to the minimum, the original publicly 
available input maps and intermediate data sets are not included in the archive. The spatial 
coverage of the fragmentation map is identical to the coverage in HRL-FTY map.  

All map products are provided in GeoTIFF format and in the data type byte. Details of the geo-
header information can be retrieved with the ‘gdalinfo’ command or by any GIS application. The 
output pixel assignment in <iso3-code>2021_fad5_223_tif is as follows: 

Value 

RGB colour code  Description 

0-9

215/50/40 

Forest pixels in fragmentation class: Very High 

10-39

250/140/90 

Forest pixels in fragmentation class: High 

40-59

255/200/0 

Forest pixels in fragmentation class: Medium 

60-89

140/200/100 

Forest pixels in fragmentation class: Low 

90-100

0/175/0 

Forest pixels in fragmentation class: Very Low 

101 

102 

105 

175/175/175 

Non-forest land 

255/255/255 

Missing or outside of reporting unit 

0/100/255 

Inland water 

22 

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