Constrained optimisation of soil sampling for minimisation of the kriging variance

J.W. van Groenigen, W. Siderius, A. Stein

Research output: Contribution to journalArticleAcademicpeer-review

218 Citations (Scopus)


This paper introduces the extended Spatial Simulated Annealing (SSA) method to optimise spatial sampling schemes for obtaining the minimal kriging variance. Sampling schemes are optimised at the point level. Boundaries and previous observations can be taken into account. This procedure extends ordinary SSA which focuses entirely on variogram estimation and even distribution of observations over the area. We applied it to texture and phosphate content on a river terrace in Thailand. First, sampling was conducted for estimation of the variogram using ordinary SSA. The variograms thus obtained were used in extended SSA, yielding a reduction of the mean kriging variance of the sand percentage from 28.2 to 23.7(%)2. The variograms were used subsequently in a geomorphologically similar area. Optimised sampling schemes for anisotropic variables differed considerably from those for isotropic ones. The schemes were especially efficient in reducing high values of the kriging variance near boundaries of the area.
Original languageEnglish
Pages (from-to)239-259
Publication statusPublished - 1999


  • soil analysis
  • sampling
  • spatial variation
  • geostatistics


Dive into the research topics of 'Constrained optimisation of soil sampling for minimisation of the kriging variance'. Together they form a unique fingerprint.

Cite this