Two data.frames must be provided to dsm. They are referred to as observation.data and segment.data.
The segment.data table has the sample identifiers which define the segments, the corresponding effort (line length) expended and the environmental covariates that will be used to model abundance/density. observation.data provides a link table between the observations used in the detection function and the samples (segments), so that we can aggregate the observations to the segments (i.e. observation.data is a "look-up table" between the observations and the segments).
observation.data - the observation data.frame must have (at least) the following columns:
object |
unique object identifier |
Sample.Label |
the identifier for the segment that the observation occurred in |
size |
the size of each observed group (e.g 1 if all animals occurred individually) |
One can often also use observation.data to fit a detection function (so additional columns for detection function covariates are allowed in this table).
segment.data: the segment data.frame must have (at least) the following columns:
Effort |
the effort (in terms of length of the segment) |
Sample.Label |
identifier for the segment (unique!) |