Line-intercept sampling: Difference between revisions
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[[Image:LiTrSa42008Geelhoed.svg|thumb|right|Click to see animation of line-intercept sampling.]] |
[[Image:LiTrSa42008Geelhoed.svg|thumb|right|Click to see animation of line-intercept sampling.]] |
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In [[statistics]], '''line-intercept sampling (LIS)''' is a method of sampling elements in a region whereby an element is sampled if a chosen line segment, called a “transect”, intersects the element <ref name="Sarndal">Kaiser, L, 1983. Unbiased Estimation in Line-Intercept Sampling, Biometrics 39. pp 965–976. </ref>. |
In [[statistics]], '''line-intercept sampling (LIS)''' is a method of sampling elements in a region whereby an element is sampled if a chosen line segment, called a “transect”, intersects the element <ref name="Sarndal">Kaiser, L, 1983. Unbiased Estimation in Line-Intercept Sampling, Biometrics 39. pp 965–976. </ref>. |
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Line intercept sampling has proven to be a reliable, versatile, and easy to implement method to analyze an area containing various objects of interest <ref name="Buckland">Buckland, S.T. Introduction to distance sampling: estimating abundance of biological populations, New York, Oxford University Press; 2001.</ref>. It has recently also been applied to estimating variances during particulate material sampling <ref>http://www.saimm.co.za/Journal/v110n06p323.pdf</ref>. |
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== References == |
== References == |
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Revision as of 11:02, 30 July 2010
In statistics, line-intercept sampling (LIS) is a method of sampling elements in a region whereby an element is sampled if a chosen line segment, called a “transect”, intersects the element [1].
Line intercept sampling has proven to be a reliable, versatile, and easy to implement method to analyze an area containing various objects of interest [2]. It has recently also been applied to estimating variances during particulate material sampling [3].
References
- ^ Kaiser, L, 1983. Unbiased Estimation in Line-Intercept Sampling, Biometrics 39. pp 965–976.
- ^ Buckland, S.T. Introduction to distance sampling: estimating abundance of biological populations, New York, Oxford University Press; 2001.
- ^ http://www.saimm.co.za/Journal/v110n06p323.pdf
See also
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