EconPapers    
Economics at your fingertips  
 

Contour models for physical boundaries enclosing star‐shaped and approximately star‐shaped polygons

Hannah M. Director and Adrian E. Raftery

Journal of the Royal Statistical Society Series C, 2022, vol. 71, issue 5, 1688-1720

Abstract: Boundaries on spatial fields divide regions with particular features from surrounding background areas. 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. Such models are needed for physical boundaries. For example, in the Arctic ocean, large contiguous areas are covered by sea ice, or frozen ocean water. We define the ice edge contour as the ordered sequences of spatial points that connect to form a line around set(s) of contiguous grid boxes with sea ice present. Polar scientists need to describe how this contiguous area behaves in present and historical data and under future climate change scenarios. We introduce the Gaussian Star‐shaped Contour Model (GSCM) for modelling boundaries represented as connected sequences of spatial points such as the sea ice edge. GSCMs generate sequences of spatial points via generating sets of distances in various directions from a fixed starting point. The GSCM can be applied to 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‐shapedness. Simulation studies illustrate the performance of the GSCM in different situations.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/rssc.12592

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:71:y:2022:i:5:p:1688-1720

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-19
Handle: RePEc:bla:jorssc:v:71:y:2022:i:5:p:1688-1720