Some variants of adaptive sampling procedures and their applications

Sengupta, Raghu Nandan; Sengupta, Angana

doi:10.1016/j.csda.2011.05.020

Cited by 2 publications

(1 citation statement)

References 31 publications

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“…Thus, adaptive spatial sampling provides a viable solution to the longstanding problem of estimating the abundance of rare populations and it has gained rapid acceptance in the natural and social sciences (Seber, 1986;Ramsey and Seber, 1992;Brown, 1994Brown, , 1996Khan and Muttlak, 2002;Stein and Ettema, 2003;Sengupta and Sengupta, 2011;Jain and Chang, 2004;Thompson, 2011;Yu et al, 2012). However, adaptive procedures are more complicated to design and analyze, and computational implementations are few as a results of the complexity of the algorithms for spatial analysis (Thompson, 2011). This implementation requires at least three steps: the development of a computational design for a regular grid; the selection of specific areas of the grid to identify which part of the grid the data are in; and identifying the neighbors of the selected areas: upper, lower, right and left.…”

Section: Introductionmentioning

confidence: 99%

A SAS Macro for Adaptive Spatial Sampling

Silva¹,

Mauriz²

2015

IJSP

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This paper presents a SAS macro to estimate adaptive spatial sampling, which has been used to survey rare species. This technique is computationally difficult because of use of algorithms with GIS features such the creation of a grid, points inside polygons and contiguity. The results indicates that the SAS macro that was developed was capable of incorporating these GIS features, as well as estimating the parameters of the adaptive spatial sampling.

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