Welcome to the Forest Monitoring Hub!
The FMH combines the European Forest Condition Monitor (EFCM) and projections of the climatic mortality risk of several tree species under different climate scenarios (scenario)
As a result of past drought summers (e.g. 2003, 2015, 2018, 2022), an increased dieback in various tree species was observed throughout Europe. In this context, the EFCM is supposed to visualise the condition of forests in Europe based on canopy greenness (NDVI) normalized against long-term observations. To illustrate both the relative and absolute variation of greenness over the observation period, the EFCM currently offers 2 products:
Quantiles = rank of greenness over all years of data and Proportions = proportional deviations: the percentual deviation of the greenness from the long-term mean.
The scenario maps visualize the impact of 14 different climate scenarios on 24 European tree-species distributions:
The scenarios span 5 climate-normal periods between 1951 and 2100 representative of three CMIP6 climate-change scenarios of SSPs 1-2.6, 2-4.5, and 5-8.5. Moreover, the impacts of a collapse of the AMOC (aka Gulf current) at the end of the 21st century are shown for each SSP scenario.
EFCM interactive map
This interactive map of the forest condition monitor allows for an individual selection (drag and zoom) of any region within Europe to visualize normalized canopy condition at any date over the monitoring period.
EFCM comparison
This comparative tool allows for comparison of canopy greenness between two different dates/regions and parameters (based on the original EFCM).
EFCM temporal trends
This tool allows for visualizing canopy greenness trends for a selected point or region across all years or interannually for the selected parameters.
Scenario interactive map
This interactive map of the forest scenarios allows for an individual selection (drag and zoom) of any region within Europe to visualize the climatic mortality risk at any date for a given species and scenario.
Scenario comparison
This comparative tool allows for comparison of climatic mortality risks between two different scenarios/regions and species.
Background information
Here you will find more detailed descriptions of the products.
Select parameter, date and region of interest:
Fine resolution: spatial resolution of 231 m x 231 m; loading data requires more time!
Medium resolution: aggregated data 5x5 pixels = 1.2 km x 1.2 km; for accelerated plotting
Coarse resolution: aggregated data 10x10 pixels = 2.4 km x 2.4 km; for fast plotting
For further information on methodology and examples on interpretation please see Buras et al., 2021: The European Forest Condition Monitor: using remotely sensed forest greenness to identify hotspots of forest decline. Frontiers in Plant Science, 12:689220, doi: 10.3389/fpls.2021.689220.
If publishing results based on the provided data download, referencing this publication is mandatory.Coordination: Allan Buras (allan.buras@tum.de)
Data download is only possible on country scaleSelect region
Select date
Select parameter
Click on map or enter coordinates:
Select trend
Download trend of selected point
Download trend of area mean
Select tree species, scenario and region of interest:
Description of methods: Heubel S., Rammig A., Buras A., 2025: Projecting the impact of a collapsing Atlantic meridional overturning circulation on European Tree-Species distributions, doi: 10.1111/gcb.70185
The presented maps depict various climate-change scenarios, and are based on climatological averages over 30-year periods. They are therefore subject to statistical uncertainty, which is why the actual occurrence of the projected abundances cannot be guaranteed.
Select region
Select scenario
Select tree species
Quantiles
The quantiles are calculated from 2003 to the present year. Red colors indicate low canopy greenness, blue high canopy greenness in comparison to the same day of year (DOY) in all other years.
The quantiles visualize the DOY-specific ranking of canopy greenness in relation to all years. The main aim of the quantiles is to show positive and negative extreme values, which can indicate particularly favorable (early spring, sufficient rainfall) or unfavorable (drought, late frost, calamities) environmental conditions.
Proportions
The proportions allow a quasi-absolute quantification of canopy greenness in a long-term comparison. To do so, the absolute deviations from the long-term median (i.e. a non-parametric mean) are computed. Quantiles -which do not allow for quantifying the absolute deviations – should always be interpreted in connection with the proportions to get an idea of the absolute greenness deviations.
Resolution
For fine scale assessments on country level please use the fine resolution data.
Winter rest
Dormant = The average monthly temperature did not exceed 5°C, no greeness value was calculated.
Color scaling
The presented colorscale was generated by the following R-code:
Quantiles: colorRampPalette(c(red,orange,grey40,dodgerblue,blue))
Proportions: colorRampPalette(c(red,orange,gold,grey40,grey40,dodgerblue,blue,darkblue))
Climatic mortality risk: c(red,orange,dodgerblue,blue)
Tree species for scenarios
(01) Pinus_halepensis, (02) Acer_pseudoplatanus, (03) Sorbus_aucuparia, (04) Fraxinus_excelsior, (05) Acer_campestre, (06) Picea_abies, (07) Quercus_pubescens, (08) Alnus_incana, (09) Betula_pendula, (10) Carpinus_betulus, (11) Corylus_avellana, (12) Quercus_suber, (13) Betula_pubescens, (14) Fagus_sylvatica, (15) Alnus_glutinosa, (16) Pinus_nigra, (17) Pinus_pinaster, (18) Quercus_ilex, (19) Quercus_robur, (20) Quercus_petraea, (21) Prunus_avium, (22) Pinus_sylvestris, (23) Abies_alba, (24) Populus_tremula
Visit our website
For further information / overview of our archive please visit our website:
Forest Condition MonitorImpressum
FMH Shiny App developed by Dr. Franziska Schnell (franziska.schnell@tum.de) based on original version by Dr. Allan Buras (allan.buras@tum.de).