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?
Distance sampling training workshop
In 2017, the structure of training workshops is changing. We will offer an intermediate-level training workshop 31 July - 04 August 2017 in St Andrews. Details describing what is covered and how to register available at the workshop website.
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.
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 (July 2017) we have just released Distance (graphical interface) version 7.1. Version 7.1 contains all the features of version 6.2 with the addition of a simulation engine and an engine for analysis of data with unidentified sightings, model or covariate uncertainty. We are placing all our development effort into version 7.1 and encourage users to switch to version 7.1. Version 6.2 will remain available on this website but will receive no further enhancements.
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:
- If you are just beginning to collect and analyse distance sampling data, download the Distance package from CRAN and work through the example analyses provided under the Getting Started heading as well as several case studies provided on the website to accompany Buckland et al. (2015) Distance sampling: methods and applications.
- If you have been using the graphical interface version of Distance, there is an R package,
readdstthat can take data and model definitions from existing Distance projects and bring them into R for further analysis. A vignette describing the use of