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Average annual area affected by water deficit, by land cover type and country

Data Visualization Created 17 Aug 2020 Published 30 Oct 2020 Last modified 30 Oct 2020
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Methodology

Standardized anomalies of yearly vegetation productivity during 2000-2016 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.

Unit

The vegetation productivity index is a dimensionless measure. It is calculated as the integral value of the yearly vegetation index. Hence, digital values indicate the approximated productivity of the land surface vegetation. The anomalies are standardised and hence are expressed in standard deviation units. The affected area is exressed in km2.

Data sources

Vegetation productivity 2000-2016 provided by European Environment Agency (EEA)

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Based on data

Data Annual above ground vegetation productivity time-series This raster data set corresponds to the above ground vegetation biomass productivity time-series 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 5-days compositing period.
Data
Archived
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/daviz/average-yearly-area-under-drought or scan the QR code.

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