Online workshop: Spatially explicit models for distance sampling data: density surface modelling in practice
This online course will cover how to fit spatial models to distance sampling data (“density surface modelling”) in R. This will include:
- Brief overview of distance sampling
- Generalized additive models
- Fitting, checking and selecting density surface models
- Predicting abundance
- Making maps
Examples will be based around a line transect survey of sperm whales in the western Atlantic.
David L Miller
16th-20th August 2021, 16:00-18:00 British Summer Time (BST - i.e., GMT+1).
Registration is limited to 15 participants.
Format and Delivery method
The course will consist of 5 live sessions delivered over videoconference. Between these sessions there will be practical R exercises to complete and to assist with these practicals there will be text-based “office hours”, where participants questions can be addressed. Each videoconference session will include time for lecturing and discussion of practical exercises.
You should already know about distance sampling, for example by having taken a face-to-face introductory workshop or an online workshop (either interactive or via our free pre-recorded lectures ). You should also have experience using R, and have the relevant software downloaded and installed in advance of the workshop. We will offer pre-workshop group meetings to check the video-conferencing software, and that you have the software correctly installed.
Registration and Payment
Registration for this workshop is now closed.
All participants are asked to abide by our workshop code of conduct.
Widening participation scholarship
We are offering one free place on the workshop to encouraging participation by scientists from countries with fewer resources, and from groups traditionally under-represented in wildlife science. Please see here for more information. The closing date for scholarship applications is June 15th.
For more information about the workshop or registration process please contact Dave Miller, email: firstname.lastname@example.org