Published May 13, 2019 | Version v1
Dataset Open

Database with GRTS sampling design used for the C-Mon project.

  • 1. Research Institute for Nature and Forest (INBO)

Contributors

Project leader:

Project member:

  • 1. Research Institute for Nature and Forest (INBO)

Description

 A SQLite database holding a realisation of a GRTS design using the principles of Reverse Randomized Quadrant-Recursive Raster method (Theobold et al 2007). The database covers a square 2D grid with 32768 (2^15) pixels in both dimensions. This allows aselect and spatially balanced sampling in Flanders (Belgium) at 10 x 10 m resolution. In the framework of the C-Mon project, selection of plots for sampling soil organic carbon (SOC) stocks over all landuses is performed based on this realisation. It is envisaged that the plots will be monitored over decades to quantify SOC stock changes over time, along with landuse changes. .   

The R script used to generate the database and to sample from the database is provided. The algorithm itself is available on GitHub (10.5281/zenodo.2784016).

The C-Mon project, entitled (in Dutch): 'Actualisatie van de onderbouwing van een methodiek voor de systematische monitoring van koolstofvoorraden in de bodem' was financed by the Department Vlaams Planbureau voor Omgeving from the Flemish Government. Project-ID: OMG/VPO/BODEM/TWOL/2017/1 

Files

Files (26.7 GB)

Name Size Download all
md5:f2e7e2bc3252282a5d2309d7ff0745a6
26.7 GB Download
md5:54b5220e80a2e4aed572557b9fa7ec50
955 Bytes Download

Additional details

Related works

Is compiled by
10.5281/zenodo.2784016 (DOI)

References

  • Stevens & Olsen (1999) Spatially balanced sampling of natural resources. Journal of the American Statistical Association, 99, 262-278
  • Theobald, Stevens et al. (2004) Using GIS to generate spatially balanced random survey designs for natural resource applications. Environmental Management, 40, 134-146