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Week 5: Raster Data and Environmental Covariates

Core Questions

  • How do rasters represent environmental variation?
  • How do resolution, extent, alignment, and NoData values affect biodiversity analysis?
  • Which environmental covariates are biologically meaningful for a study system?

Concepts

  • Raster versus vector data.
  • Cells, pixels, resolution, extent, and NoData.
  • Raster alignment and extraction.
  • Elevation, climate, land cover, remote sensing, terrain, and microclimate.
  • Temporal alignment and ecological interpretation of predictors.

Python Tools

  • rasterio.
  • rioxarray.
  • xarray.
  • NumPy.

Applied Lab

Students extract elevation, temperature, precipitation, slope, and land cover values at species occurrence locations, producing an analysis table that combines species, coordinates, and environmental covariates.

Deliverable

Submit a predictor inventory table with source, temporal coverage, resolution, units, ecological justification, and preprocessing notes.