Thesis subject

MSc thesis topic: Suitability of coastal areas for seaweed cultivation

Seaweed is cultivated everywhere across the world, from cold Northern Japan and Norway to warm tropical Indonesia (Buschmann et al., 2017; FAO, 2018). The sector is growing, yet to date we lack maps of sites suitable for seaweed cultivation.

A global model for predicting site suitability has been developed by van Oort et
al (2022). World Ocean Atlas (WOA) input data for the seaweed site suitability model are at 1o spatial and 1 month temporal resolution. WOA provides poor
coverage of the coastal regions, see the picture above. Coastal regions are
economically more attractive for seaweed cultivation, because (1) productions
costs are lower, don’t have to go far by boat for planting / harvesting the
seaweed and (2) nutrient concentrations are generally higher near shore (see
picture). The research question addressed in this thesis is “which coastal
sites are best suited for seaweed cultivation?”

This research is conducted in collaboration with Agrosystems Research (part of WUR) in the context of the project Aquatic Systems. In this MSc thesis you will

  • further develop your GIS skills in spatial extrapolation methods like Inverse Distance Weighting (IDW) etc;
  • further develop your GIS skills in working with projections, for area and distance calculations;
  • generate high resolution monthly geodata for environmental variables in selected coastal regions, including the North Sea and Indonesia and more coastal regions (depending on data availability);
  • calibrate / validate the high resolution data you generated with observed data;
  • adapt the site suitability model to run with the new high resolution coastal data;
  • simulate site suitability and present new site suitability maps.


  • Produce high spatial resolution monthly geodata sets for environmental variables in the coastal regions
  • Calibrate/validate with high resolution data
  • Simulate seaweed site suitability for the coastal regions



  • Minimal knowledge of programming (R preferred).

Theme(s): Modelling & visualisation