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Dashboard (Tableau)

Drought impact on ecosystems in Europe, 2000-2019

Dashboard (Tableau)
Prod-ID: DAS-275-en
Published 26 Oct 2021
1 min read
Yearly vegetation productivity during 2000-2019 are analysed in areas under drought pressure, measured as precipitation shortages and low soil moisture content. Vegetation productivity values are disaggregated and detailed by year and by detailed land cover categories. Strong negative values indicate strong drought intensity, with vegetation productivity values lower than the long term average normal condition. Scroll down to the More information section for further details.

More information

Access the soil moisture dataset here:

https://www.eea.europa.eu/data-and-maps/data/soil-moisture-deficit-during-the 

Access the vegetation productivity dataset here:

https://www.eea.europa.eu/data-and-maps/data/annual-above-ground-vegetation-productivity 

Standardized anomalies of yearly vegetation productivity during 2000-2019 are analyzed in areas with statistically significant drought pressure measured as precipitation shortages and low soil moisture content.

Anomalies are expressed in standard deviations compared to the long term average vegetation productivity conditions for each 500m grid cell in the EEA39 region. Negative vegetation productivity anomalies indicate vegetation productivity conditions that are less than the long term normal condition.

The extent of the impacted area is calculated from the sum of those grid cells where the vegetation productivity anomaly was below -1 standard deviation in the given year.

In order to exclude low vegetation anomaly signals in the time series, only those grid cells were considered in this analysis where the Corine Land Cover (CLC) 2000-2018 series indicated no land use change between 2000-2018.

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Based on data

Data Soil moisture deficit during the vegetation growing season, annual time-series, 2000-2019 The dataset consists of a collection of annual soil moisture (SM) anomalies during the vegetation growing season (GS) for the years 2000-2019 across EEA 38 area and the United Kingdom. The vegetation growing season is defined by EEA´s phenology data series "Vegetation growing season length 2000-2016" [https://www.eea.europa.eu/data-and-maps/data/annual-above-ground-vegetation-season]. The anomalies are calculated based on the European Commission's Joint Research Centre European Drought Observatory (EDO) Soil Moisture Index (SMI) with respect to the 1995–2019 base period. The yearly start and end of GS periods are dynamic and calculated according to the EEA Phenology Indicators. A positive anomaly indicates that the observed SM was wetter than the long-term SM average for the base period, while a negative anomaly indicates that the observed SM was drier than the reference value. Because SM anomalies are measured in units of standard deviation from the long-term SMI average, they can be used to compare annual deficits/surplus of SM between geographic regions. EDO is one of the early warning and monitoring systems of the Copernicus Emergency Management Service. As the dataset builds on EDO's SMI, it therefore contains modified Copernicus Emergency Management Service information (2019).
Data Vegetation productivity 2000-2016 The raster files are the above ground vegetation productivity time-series and the derived linear trend for the period 2000-2016.The data set addresses trends in land surface productivity derived from remote sensing observed time series of vegetation indices. The vegetation index used in the indicator is the Plant Phenology Index (PPI, Jin and Eklundh, 2014). PPI is based on the MODIS Nadir BRDF-Adjusted Reflectance product (MODIS MCD43 NBAR. The product provides reflectance data for the MODIS “land” bands (1 - 7) adjusted using a bi-directional reflectance distribution function. This function models values as if they were collected from a nadir-view to remove so called cross-track illumination effects. The Plant Phenology Index (PPI) is a new vegetation index optimized for efficient monitoring of vegetation phenology. It is derived from radiative transfer solution using reflectance in visible-red (RED) and near-infrared (NIR) spectral domains. PPI is defined to have a linear relationship to the canopy green leaf area index (LAI) and its temporal pattern is strongly similar to the temporal pattern of gross primary productivity (GPP) estimated by flux towers at ground reference stations. PPI is less affected by presence of snow compared to commonly used vegetation indices such as Normalized Difference Vegetation Index (NDVI) or Enhanced Vegetation Index (EVI).The product is distributed with 500 m pixel size (MODIS Sinusoidal Grid) with 8-days compositing period.

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For references, please go to https://www.eea.europa.eu/data-and-maps/data/data-viewers/drought-impact-on-ecosystems-in or scan the QR code.

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