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EBV Data Portal

The EBV Data Portal includes a variety of EBV raster datasets. You can import these datasets into the map with a single click. You can also upload your own EBV raster data or vector data for private use or sharing with others.
GEO BON

EBV Data Portal

The EBV Data Portal includes a variety of EBV raster datasets. You can import these datasets into the map with a single click. You can also upload your own EBV raster data or vector data for private use or sharing with others.
GEO BON

EBV Data Portal

The EBV Data Portal includes a variety of EBV raster datasets. You can import these datasets into the map with a single click. You can also upload your own EBV raster data or vector data for private use or sharing with others.

MEASURING THE BIODIVERSITY OF OUR PLANET

BIODIVERSITY OBSERVATIONS FOR A BETTER FUTURE

Essential Biodiversity Variables (EBVs), defined as the derived measurements required to study, report, and manage biodiversity change, focusing on status and trend in elements of biodiversity. EBVs play the role of brokers between monitoring initiatives and decision makers. They provide the first level of abstraction between low-level primary observations and high-level indicators of biodiversity.

Latest EBV Datasets

FILTER LATEST DATASETS BY

Global

Changes in bird diversity at the grid cell level caused by land-use, estimated by the cSAR model (Pereira et al). It reports changes in species number (percentage and absolute), relative to 1900, for all bird s...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Birds
  • cSAR model
  • LUH 2.0 projections
  • PREDICTS
  • land-use

Global

We use an existing spatially contiguous, global remote-sensing data product (i.e. the 27-year annual ESA CCI land cover maps which can be categorized as an EBV ‘Ecosystem Distribution’) to derive an annual ...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • ESA
  • land cover maps
  • grid cell
  • time-series

Global

Data in this layer were generated using multi-spectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+) sensor. The clear surface observations from over 600,000 images were analysed using Google...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Forest loss
  • Google
  • AI
  • Machine Learning
  • Global Change

Global

Data on Area Of Habitat (AOH) for 5090 mammals from 2015 to 2100, in 5 year intervals.

Download Data (netCDF)


  • Mammals
  • Species
  • Habitats
  • Global
  • Land cover

Community composition

Changes in bird diversity at the grid cell level caused by land-use, estimated by the cSAR model (Pereira et al). It reports changes in species number (percentage and absolute), relative to 1900, for all bird s...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Birds
  • cSAR model
  • LUH 2.0 projections
  • PREDICTS
  • land-use

Ecosystem structure

We use an existing spatially contiguous, global remote-sensing data product (i.e. the 27-year annual ESA CCI land cover maps which can be categorized as an EBV ‘Ecosystem Distribution’) to derive an annual ...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • ESA
  • land cover maps
  • grid cell
  • time-series

Ecosystem structure

Data in this layer were generated using multi-spectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+) sensor. The clear surface observations from over 600,000 images were analysed using Google...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Forest loss
  • Google
  • AI
  • Machine Learning
  • Global Change

Species populations

Data on Area Of Habitat (AOH) for 5090 mammals from 2015 to 2100, in 5 year intervals.

Download Data (netCDF)


  • Mammals
  • Species
  • Habitats
  • Global
  • Land cover

Terrestrial

Changes in bird diversity at the grid cell level caused by land-use, estimated by the cSAR model (Pereira et al). It reports changes in species number (percentage and absolute), relative to 1900, for all bird s...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Birds
  • cSAR model
  • LUH 2.0 projections
  • PREDICTS
  • land-use

Terrestrial

We use an existing spatially contiguous, global remote-sensing data product (i.e. the 27-year annual ESA CCI land cover maps which can be categorized as an EBV ‘Ecosystem Distribution’) to derive an annual ...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • ESA
  • land cover maps
  • grid cell
  • time-series

Terrestrial

Data in this layer were generated using multi-spectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+) sensor. The clear surface observations from over 600,000 images were analysed using Google...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Forest loss
  • Google
  • AI
  • Machine Learning
  • Global Change

Terrestrial

Data on Area Of Habitat (AOH) for 5090 mammals from 2015 to 2100, in 5 year intervals.

Download Data (netCDF)


  • Mammals
  • Species
  • Habitats
  • Global
  • Land cover

Decade

Changes in bird diversity at the grid cell level caused by land-use, estimated by the cSAR model (Pereira et al). It reports changes in species number (percentage and absolute), relative to 1900, for all bird s...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Birds
  • cSAR model
  • LUH 2.0 projections
  • PREDICTS
  • land-use

Yearly

We use an existing spatially contiguous, global remote-sensing data product (i.e. the 27-year annual ESA CCI land cover maps which can be categorized as an EBV ‘Ecosystem Distribution’) to derive an annual ...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • ESA
  • land cover maps
  • grid cell
  • time-series

Yearly

Data in this layer were generated using multi-spectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+) sensor. The clear surface observations from over 600,000 images were analysed using Google...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Forest loss
  • Google
  • AI
  • Machine Learning
  • Global Change

Every 5 years

Data on Area Of Habitat (AOH) for 5090 mammals from 2015 to 2100, in 5 year intervals.

Download Data (netCDF)


  • Mammals
  • Species
  • Habitats
  • Global
  • Land cover

Species Taxonomy

Changes in bird diversity at the grid cell level caused by land-use, estimated by the cSAR model (Pereira et al). It reports changes in species number (percentage and absolute), relative to 1900, for all bird s...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Birds
  • cSAR model
  • LUH 2.0 projections
  • PREDICTS
  • land-use

Ecosystem Types

We use an existing spatially contiguous, global remote-sensing data product (i.e. the 27-year annual ESA CCI land cover maps which can be categorized as an EBV ‘Ecosystem Distribution’) to derive an annual ...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • ESA
  • land cover maps
  • grid cell
  • time-series

Ecosystem Types

Data in this layer were generated using multi-spectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+) sensor. The clear surface observations from over 600,000 images were analysed using Google...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Forest loss
  • Google
  • AI
  • Machine Learning
  • Global Change

Species Taxonomy

Data on Area Of Habitat (AOH) for 5090 mammals from 2015 to 2100, in 5 year intervals.

Download Data (netCDF)


  • Mammals
  • Species
  • Habitats
  • Global
  • Land cover

Ines Martins

Changes in bird diversity at the grid cell level caused by land-use, estimated by the cSAR model (Pereira et al). It reports changes in species number (percentage and absolute), relative to 1900, for all bird s...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Birds
  • cSAR model
  • LUH 2.0 projections
  • PREDICTS
  • land-use

Babak Naimi

We use an existing spatially contiguous, global remote-sensing data product (i.e. the 27-year annual ESA CCI land cover maps which can be categorized as an EBV ‘Ecosystem Distribution’) to derive an annual ...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • ESA
  • land cover maps
  • grid cell
  • time-series

Matthew Hansen

Data in this layer were generated using multi-spectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+) sensor. The clear surface observations from over 600,000 images were analysed using Google...

Download Data (netCDF)


  • Big Data
  • Remote Sensing
  • Forest loss
  • Google
  • AI
  • Machine Learning
  • Global Change

Daniele Baisero

Data on Area Of Habitat (AOH) for 5090 mammals from 2015 to 2100, in 5 year intervals.

Download Data (netCDF)


  • Mammals
  • Species
  • Habitats
  • Global
  • Land cover
MEASURING THE BIODIVERSITY OF OUR PLANET

EBV Data Portal

With Support By

The EBV Data Portal is supported by

eShape
iDiv
Philipps-University Marburg
Martin-Luther-University Halle-Wittenberg