MATLAB Examples

Antbounds Contents and data masking tips

The functions in this plugin for Antarctic Mapping Tools for Matlab are intended to simplify the process of Antarctic data masking. We use the the MEaSURES Antarctic Boundaries for IPY 2007-2009 from Satellite Radar dataset Version 2, which has been kindly provided by Mouginot et al. (see citation below) and is described in full on the NSIDC site here.


Line data

The dataset contains data for the Antarctic grounding line, coast line, and ice shelf outlines. This toolbox has a function for loading the line data, and another function for plotting the line data.

  • antbounds_data lets you easily load grounding line, coast, or ice shelf outline data. The grounding line in this dataset is obtained by the same InSAR methods which were used for the measures_data grounding line; however, the antbounds_data is continuous around the continent and represents only a single snapshot in time, whereas the measures_data is discontinous and lets you see grounding line evolution through time.
  • antbounds simply plots the line data given by antbounds_data.
  • labelshelves simply labels the ice shelves plotted by the antbounds function.

Logical functions for data masking

This toolbox contains five functions which are optimized to load Mouginot et al.'s Mask_Antarctica data and and interpolate to determine whether locations correspond to grounded ice, ice shelves, open ocean, etc.

  • isgrounded determines whether input coordinates correspond to grounded ice.
  • isiceshelf determines whether input coordinates correspond to ice shelf (not sea ice).
  • isopenocean determines whether input coordinates correspond to open ocean (no grounded ice, and no ice shelves, but sea ice is considered open ocean).
  • isice determines whether input coordinates correspond to any part of the ice sheet, grounded ice or ice shelves. This is the logical NOT of isopenocean.
  • istidal determines whether input coordinates are seaward of the landward limit of flexure as measured by InSAR. This is the logical NOT of isgrounded.

Tips for data masking

If you're working with a dataset that comes with its own mask (e.g., Bedmap2, RTopo-2, etc.), it might make sense to use the mask associated with that dataset. Otherwise, the logical is* functions listed above are in many cases the easiest to work with. For example, consider this 50 km resolution grid over Dronning Maud Land, which we create with psgrid:

[lat,lon] = psgrid('dronning maud land',3000,50);

Plot the grid, a grounding line, and a coast line for context:

plotps(lat,lon,'.','color',.5*[1 1 1])
hold on
axis tight

To determine which grid points correspond to open ocean, use isopenocean:

ocean = isopenocean(lat,lon);

It's just as easy to determine which grid points correspond to grounded ice, ice shelves, etc. However, if you need to know which grid points correspond to a particular ice shelf rather than just any ice shelf, you'll need to load the outline of the ice shelf with antbounds_data, then use inpolygon. And to use inpolygon we should be in x,y space rather than lat,lon space:

[X,Y] = ll2ps(lat,lon);

Let's load the outline of Baudouin Ice Shelf:

[x_baudouin,y_baudouin] = antbounds_data('Baudouin','xy');

Now we can determine which grid points are inside the Fimbul outline:

fimbul = inpolygon(X,Y,x_baudouin,y_baudouin);

And we can add some junk to the map if we so desire:


Another fun little function

There's one more function in this toolbox:

  • dist2mask calculates the distance from any point(s) to the nearest mask type. This can be useful if you want to plot data as a function of distance from the grounding line, or if you have a bunch of mooring data, and you only want to consider the moorings that were collected within some number of kilometers of an ice shelf front. This is similar to the bedmap2_dist function found in the Bedmap2 plugin for AMT.

Citing this dataset

If you use this dataset, please cite the following:

  • The dataset: Mouginot, J., B. Scheuchl, and E. Rignot. 2017. MEaSUREs Antarctic Boundaries for IPY 2007-2009 from Satellite Radar, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center.

Author Info

This toolbox and supporting documentation were written by Chad A. Greene of the University of Texas Institute for Geophysics (UTIG), November 2016. Updated May 2017 for version 2 of the dataset.