Welcome to the Distance project website

The Distance project provides software for the design and analysis of distance sampling surveys of wildlife populations. This software takes two forms: a Windows-based program and a suite of packages for the statistical programming language R.

If you are unfamiliar with distance sampling concepts, or are looking for links to books and literature or introductory training videos, please visit the page – What is distance sampling?

We need your help!

We plan to develop new software to aid distance sampling practitioners in survey design and we would like you to help us make sure our software meets your needs.

Distance for Windows is currently the only software which provides practitioners with the tools to be able to design surveys and generate sets of randomised transects for carrying out distance sampling surveys. We now plan on making similar tools available in R, meaning it can be used on any platform. This software will allow you to define a survey design, assess the properties of the design as well as generate a set of transects for your survey.

We would appreciate it if you could fill in our short questionnaire, to ensure that we can best meet your needs.

Distance sampling training workshop

Our 2018 training workshop in St Andrews took place between the 26th and 31st of August. It consisted of a one-day Distance sampling using R workshop and a five-day Intermediate distance sampling including spatial modelling. We are currently planning the 2019 training workshops.

A complete introductory distance sampling training workshop is available online. Complete with 24 video lectures and 12 exercises along with solutions and software demonstrations, this is a good resource to aide your understanding of distance sampling design, analysis and interpretation.

Photos of a polar bear, grouse and lizard, taken by Tiago Marques (bear/lizard) and Steve Buckland (grouse)

Software to design and analyse distance sampling surveys

There are two routes you can choose to analyse your data. You can either use the “standalone” Windows software Distance or use packages available in the R programming language. In reality, you are (mostly) using packages written in R whichever you choose; the first option provides a graphical interface to the underlying analysis software. To help you decide which software will best meet your needs, we have summarised which features are implemented in each R package and which features are available in Distance: Distance Feature Table.

Distance for Windows

The graphical interface of Distance has been in existence since 1997 and nearly 50,000 users from > 110 countries have grown accustomed to it. At time of this writing (June 2018) we have just released Distance (graphical interface) version 7.2. Version 7.2 contains all the features of version 7.1 with the addition of point transect analyses in both the mark-recapture distance sampling engine and the density surface modelling engine. We are placing all our development effort into version 7.2 and encourage users to switch to version 7.2.

Distance is available for download from this web site at no cost.

Distance R packages

We encourage people who analyse distance sampling data to consider migrating from the graphical interface version to the use of R. The single exception to this is survey design which at present can only be performed using the graphical interface. Granted, this requires some investment in learning to use R. Why would users not all choose to use the graphical interface version of Distance? There are at least three reasons:

  • New developments in distance sampling analysis is first developed in R, only later is a graphical interface to the R software developed.
  • Some functionality of the software written in R is not accessible through the graphical interface. It is challenging for development of the interface to keep up with developments in the underlying analysis software. Our programmer time must be allocated between the tasks of developing analysis software and updating the graphical interface.
  • Some users maintain their distance sampling data using the database features of R. Consequently, their data reside in R and analysis is most readily performed by remaining in R.

There are two packages (and associated vignettes) to ease the transition to R:

Further information on Distance-related R packages

Other pages on this site