Standard Article

Distance Sampling

Ecological Statistics

  1. Len Thomas1,
  2. Stephen T. Buckland2,
  3. Kenneth P. Burnham3,
  4. David R. Anderson3,
  5. Jeffrey L. Laake4,
  6. David L. Borchers2,
  7. Samantha Strindberg5

Published Online: 15 JAN 2013

DOI: 10.1002/9780470057339.vad033.pub2

Encyclopedia of Environmetrics

Encyclopedia of Environmetrics

How to Cite

Thomas, L., Buckland, S. T., Burnham, K. P., Anderson, D. R., Laake, J. L., Borchers, D. L. and Strindberg, S. 2013. Distance Sampling . Encyclopedia of Environmetrics. 2.

Author Information

  1. 1

    University of St Andrews, Scotland, UK

  2. 2

    University of St Andrews, Fife, UK

  3. 3

    Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO, USA

  4. 4

    National Marine Mammal Laboratory, Seattle, WA, USA

  5. 5

    Wildlife Conservation Society, Bronx, NY, USA

Publication History

  1. Published Online: 15 JAN 2013

Abstract

Distance sampling is a widely used group of closely related methods for estimating the density and/or abundance of biological populations. The main methods are line-transect sampling and point-transect sampling. In both cases, observer(s) perform a standardized survey along a series of randomly located lines or points, searching for objects of interest (usually animals or clusters of animals). For each object detected, they record the distance from the line or point to the object. Not all objects will be detected, but a fundamental assumption of the basic methods is that all objects that are actually on the line or point are detected. The key to distance sampling analyses is to use the observed distances to fit a detection function that describes how detectability decreases with increasing distance from the transect. The fitted function is used to estimate the average probability of detecting an object; from here, one can readily obtain point and interval estimates for the density and abundance of objects in the survey area. Various extensions to the basic methods allow assumptions to be relaxed, and include methods that integrate capture-recapture and distance sampling, as well as methods to model spatial variation in density.

Keywords:

  • line transect;
  • point transect;
  • mark–recapture distance sampling;
  • density surface model;
  • detection probability modeling;
  • sampling survey;
  • wildlife population assessment;
  • density;
  • abundance;
  • population size