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Distance Sampling

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International Encyclopedia of Statistical Science

Distance sampling is a widely used methodology for estimating animal density or abundance. Its name derives from the fact that the information used for inference are the recorded distances to objects of interest, usually animals, obtained by surveying lines or points. The methods are also particularly suited to plants or immotile objects, as the assumptions involved (see below for details) are more easily met. In the case of lines the perpendicular distances to detected animals are recorded, while in the case of points the radial distances from the point to detected animals are recorded. A key underlying concept is the detection function, usually denoted g(y) (here y represents either a perpendicular distance from the line or a radial distance from the point). This represents the probability of detecting an animal of interest, given that it is at a distance y from the transect. This function is closely related to the probability density function (pdf) of the detected distances, f(y), a...

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References and Further Reading

  • Buckland ST (1992) Fitting density functions with polynomials. Appl Stat 41:63–76

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  • Buckland ST (2006) Point transect surveys for songbirds: robust methodologies. The Auk 123:345–357

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  • Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (2001) Introduction to distance sampling: estimating abundance of biological populations. Oxford University Press, Oxford

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  • Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (2004) Advanced distance sampling. Oxford University Press, Oxford

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  • Thomas L, Buckland ST, Rexstad R, Laake L, Strindberg S, Hedley S, Bishop J, Marques TA, Burnham KP (2010) Distace software: design and analysis of distance sampling surveys for estimating population size. J App Ecol 47:5–14

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© 2011 Springer-Verlag Berlin Heidelberg

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Marques, T.A., Borchers, S.T.B., Borchers, D.L., Rexstad, E.G., Thomas, L. (2011). Distance Sampling. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_214

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