Towards progressive strategies for spatial sampling in the field

Jingxiong Zhang, Michael Goodchild

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

The geostatistical basis for adaptive/progressive sampling is discussed, following an introduction to the necessary statistical background and developments in geographic information technologies. Where computational resources are limited, as they are in the field, strategies that combine heuristic and numerical approaches are the key to successful field implementation. A sequential algorithm for rapid location of further samples is formulated, using the criterion of maximum global reduction in Kriging variance. Results from a test confirm the effectiveness of the proposed algorithms.

Original languageEnglish (US)
Pages (from-to)441-445
Number of pages5
JournalGeomatics and Information Science of Wuhan University
Volume33
Issue number5
StatePublished - May 5 2008
Externally publishedYes

Fingerprint

Sampling
sampling
information technology
heuristics
kriging
Information technology
resource
test

Keywords

  • Block-kriging
  • Co-Kriging
  • Covariate
  • Spatial sampling

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Earth-Surface Processes

Cite this

Towards progressive strategies for spatial sampling in the field. / Zhang, Jingxiong; Goodchild, Michael.

In: Geomatics and Information Science of Wuhan University, Vol. 33, No. 5, 05.05.2008, p. 441-445.

Research output: Contribution to journalArticle

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