Spatially stratified sampling using auxiliary information for geostatistical mapping

This paper presents a method of spatial sampling based on stratification by Local Moran's I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hy...

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Bibliographic Details
Published in:Environmental and ecological statistics 2011-03, Vol.18 (1), p.93-108
Main Authors: Falk, Matthew G, Denham, Robert J, Mengersen, Kerrie L
Format: Article
Language:English
Subjects:
Accuracy
Biomedical and Life Sciences
Case studies
Chemistry and Earth Sciences
Computer Science
data collection
Datasets
Ecology
Geostatistics
Health Sciences
kriging
Life Sciences
Mapping
Math. Appl. in Environmental Science
Medicine
Methods
Physics
Regression analysis
sampling
Sampling techniques
spatial data
Statistics for Engineering
Statistics for Life Sciences
Studies
Theoretical Ecology/Statistics
Topography
Variables
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Description
Summary:This paper presents a method of spatial sampling based on stratification by Local Moran's I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.
ISSN:1352-8505
1573-3009
DOI:10.1007/s10651-009-0122-3