Own exercises in actinia

Meanwhile you have seen a lot of material. Time to try out some further exercises...

1. What is the altitude of the highest point in North Carolina? Check it with actinia.

  • Find the correct raster in the North Carolina location and PERMANENT mapset.
  • Find the relevant raster layer by rendering it
  • Print the information and get altitude of the highest point
  • List of available data in the North Carolina sample dataset.

2. Find the zipcode in Wake county with the most hospitals

  • Find the relevant vector layers
  • Check the zipcode vector layer for the relevant column to get the zipcode
  • Create a process chain as a .json file to ask for the number of hospitals in the zipcodes: Use the GRASS GIS modules g.copy (because you are not allowed to change data from an other mapset), v.vect.stats and v.db.select
  • Post the created process chain to https://actinia.mundialis.de/api/v3/locations/nc_spm_08/processing_async for ephemeral processing
  • Related GRASS GIS manual pages: g.copy, v.vect.stats, v.db.select.

3. Export the water bodies from the available Landsat imagery of North Carolina

  • Create a process chain as a .json file
    • Remember to set the computational region
    • Compute the NDWI (Normalized difference water index); use r.mapcalc or i.vi
    • Filter water bodies by a threshold of e.g. 0.35 using r.mapcalc
  • Either export the water bodies (use the exporter with the ephemeral processing) or render the maps of NDWI and water bodies with a nice color (use r.colors and persistent processing in your own mapset)
  • Related GRASS GIS manual pages: r.mapcalc, i.vi, exporter.

4. Population at risk near coastal areas

  • needed geodata:
    • Worldwide SRTM 30m (already available in actinia as srtmgl1_v003_30m - find out the location yourself)
    • South America Population 2015 (already available in actinia as worldpop_2015_1km_aggregated_UNadj- find out the location yourself)
    • raster shorelines (already available in actinia as ne_1000m_coastlines- find out the location yourself)
  • fetch metadata with actinia interface and render input data
  • proposed workflow:
    • set computational region to a small subregion (hint: align the region resolution to the population raster) and check the pixel number against user constraints
    • buffer the coastlines by 5000 m and set a mask to the result
    • Extract only the peopulation below 10 m
    • Calculate the statistic to get the population at risk near coastal areas
  • Hints for example GRASS modules to use in process chain: g.region, r.buffer, r.mapcalc, r.mask, r.univar
  • Related GRASS GIS manual pages: g.region, r.buffer, r.mask, r.univar.