  Boundaries on spatial fields divide regions with particular features from
surrounding background areas. These boundaries are often described with contour
lines. To measure and record these boundaries, contours are often represented
as ordered sequences of spatial points that connect to form a line. Methods to
identify boundary lines from interpolated spatial fields are well-established.
Less attention has been paid to how to model sequences of connected spatial
points. For data of the latter form, we introduce the Gaussian Star-shaped
Contour Model (GSCM). GSMCs generate sequences of spatial points via generating
sets of distances in various directions from a fixed starting point. The GSCM
is designed for modeling contours that enclose regions that are star-shaped
polygons or approximately star-shaped polygons. Metrics are introduced to
assess the extent to which a polygon deviates from star-shaped. Simulation
studies illustrate the performance of the GSCM in various scenarios and an
analysis of Arctic sea ice edge contour data highlights how GSCMs can be
applied to observational data.
