What is it about?
The purpose of this paper is to compare some spatial strategies for sampling polygons onto a grid partitioning a study area. Most of the schemes considered in the paper are aimed at avoiding the selection of neighboring polygons. When one or more auxiliary variables are similar or well correlated with the values of the survey variable, the auxiliary information is adopted at estimation level by means of the difference or the regression estimators, or at design level, using the values of auxiliary variables to determine the inclusion probabilities.
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Why is it important?
Several problems arising in environmental surveys can be mentioned for motivating the necessity of effective sampling schemes selecting spatial units from regular grids. The necessity may arise in forest inventories.
Perspectives
In this paper, the spatial information has been taken separate from other auxiliary information. In other words, the problem of avoiding selection of contiguous units (in the genuine spatial sense) has been handled by the sampling schemes, while other sources of information has been exploited to determine inclusion probabilities or to predict the target variabile. Alternatively, the spatial coordinates can be merged with the other auxiliary variables, and the spatial schemes can be used to provide balance in the Euclidean space determined by all the variables. In addition, contrary to the strategies adopted in this paper, a hybrid use of the auxiliary information is possible; that is, the auxiliary variables can be jointly used at design and estimation level.
Piermaria Corona
CREA Research Centre for Forestry and Wood
Read the Original
This page is a summary of: Design-based strategies for sampling spatial units from regular grids with applications to forest surveys, land use, and land cover estimation, Environmetrics, March 2015, Wiley,
DOI: 10.1002/env.2332.
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