Environmental covariates

EURODEER database hosts not only data on animals (movement, individual, population, survival, capture, etc.), but also data sets related to many environmental covariates. The idea is that data sets available and consistent for the whole area covered by the project are used to characterize locations, transforming coordinates into "habitats",  and also to describe the ecological attributes of other spatial features derived from tracking data (e.g. home ranges), making possible comparative analysis across different study areas. An example to calculate the percentage of each land cover class and NDVI statistics for monthly Minimum Convex Polygon of an individual is described on the EURODEER GitHub repository.

The database stores both static layers and time dependant variables that are periodically updated. The main information (that cover the whole EUROPE) in the DB at the moment are:

  • Raw NDVI from MODIS sensor (spatial resolution 250 m; temporal resolution 16-daily) from LP DAAC
  • NDVI smoothed from MODIS (spatial resolution 250 m; temporal resolution 10-daily; SWETS smoother, generated with SPIRITS software)
  • NDVI smoothed from MODIS (spatial resolution 250 m, only over EURODEER study areas; temporal resolution 7-daily; Whittaker smoother; provided by BOKU University, you can find the technical documentation here [for EURODEER users])

examples_ndvi2

examples_lc

  • European administrative units
  • ASTER DEM (30 m; altitude, slope, aspect)
  • SRTM DEM (90 m; altitude, slope, aspect - available for latitude -60° to 60°)
  • Digital Elevation Model over Europe, EU-DEM (30 m; altitude, slope, aspect). EU-DEM is now used as main reference.

In addition, we have a number of derived indicators that were calculated for specific studies and that are now available to all EURODEER users, namely:

  • NDVI-based temporal variability (computed by EURODEER based on MODIS NDVI, you can find the technical documentation here [for EURODEER users])
    • Constancy (inter-annual variability based on NDVI)
    • Contingency (seasonality or within-year variability based on NDVI)
    • Predictability (variation among successive periods of a periodic phenomenon based on NDVI)

examples_contingency_2

  • Average vegetation phenology (pixel based, derived from MODIS NDVI, generated with SPIRITS software)
    • Average start of the growing season
    • Average end of the growing  season
    • Average max of the growing  season
    • Average length of the season
    • Number of growing seasons
  • Yearly winter Severity (based on Modis Snow: % of time a cell is covered by snow in the period 1st of October to 31th of March), you can find the technical documentation here [for EURODEER users])

examples_winter

One of the ongoing activities to extend the EURODEER platform is the integration of the tools offered by Google Earth Engine and to investigate possible applications of the new SENTINEL-2 data.