2000
DOI: 10.2307/177447
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Geostatistical Estimation Variance for the Spatial Mean in Two-Dimensional Systematic Sampling

Abstract: JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. Ecological Society of America is collaborating with JSTOR to digitize, preserve and extend access to Ecology.Abstract. Many ecologists use two-dimensional systematic sampling … Show more

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Cited by 18 publications
(31 citation statements)
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“…Several aspects of the model-based approach merit consideration. First, the literature pertaining to variance estimation for model-based estimates for regions consisting of multiple pixels is sparse; Gregoire (1998), Aubry and Debouzie (2000), and McRoberts (2006) are among the few references. Second, unlike sample-based approaches, including stratified estimation, the issue of bias may be more difficult to assess for model-based approaches.…”
Section: Introductionmentioning
confidence: 99%
“…Several aspects of the model-based approach merit consideration. First, the literature pertaining to variance estimation for model-based estimates for regions consisting of multiple pixels is sparse; Gregoire (1998), Aubry and Debouzie (2000), and McRoberts (2006) are among the few references. Second, unlike sample-based approaches, including stratified estimation, the issue of bias may be more difficult to assess for model-based approaches.…”
Section: Introductionmentioning
confidence: 99%
“…Alternatively, two-dimensional systematic sampling (2DSS) represents a straightforward way of achieving spatial balance (e.g. Aubry and Debouzie 2000;D'Orazio 2003). The scheme is based on a regular grid of polygons (the SUs) superimposed onto the study area which is subsequently partitioned into regular sub-regions each containing an equal number of polygons.…”
Section: Discussionmentioning
confidence: 99%
“…Along this line of thought, Matérn (1986) proposes a method where each observation is compared to observations made in its geographical vicinity. Aubry & Debouzie (2000), following such an approach, report that the geostatistical error estimate is a more reliable tool than the simple random sample variance estimate for calculating a confidence interval of the mean because the location and size of the sampling units can be taken into account.…”
Section: Uncertaintymentioning
confidence: 99%