A mapping package for Matlab
You have collected your data, loaded it into Matlab, analyzed everything todeath, and now you want to make a simple map showing how it relates to the world.
But you can't.
Instead you have to figure out how to save all your data, and thenread it into another program (like, for example GMT), and then spend all thatextra time figuring out why it doesn't give you what you expected itwould...or you can invest in Matlab's own mapping toolbox (with a similarly steep learning curve)... or not!
Announcing M_Map v1.4o!
(released Sept/2023)
M_Map is a set of mapping tools written for Matlab (it also works under Octave). M_Map includes:
- Routines to project data in 21 different projections(and determine inverse mappings), using spherical and ellipsoidal earth-models.
- A grid generation routine to make nice axes with limits eitherin lat/long terms or in planar X/Y terms.
- A coastline database (with 1/4 degree resolution).
- A global elevation database (1 degree resolution).
- Hooks into freely available high-resolution coastline andbathymetry databases.
- Other useful stuff.
Gallery
How to get M_Map
You can download the M_Map toolbox either as a gzipped tar-file ,or as zip archive(Click on these links to download - note, some problems with this have been reported by users of the Chromeweb browser). If you are unpacking the zipfile MAKE SURE YOUALSO UNPACK SUBDIRECTORIES! Both are around 650k in size. Once you havethisarchive, read the Getting started sectionof the User's guide to correctlyinstall this toolbox, and sections 8.6and 9.3 to install ETOPO1and GSHHS respectively.
A number of examples are available tohighlight the various capabilities of M_Map (thumbnails are shownabove).
M_Map is a programming toolbox. However, you can also exploremapping using MAP-LAB,a a MATLAB-based Graphical User Interface (GUI) designed to produce maps and visualize data sets related to geodetic, geophysical and oceanographic applications, which is built on top of M_Map.MAP_Lab is available here.
Release Notes
New in release 1.4o (Sept/2023):
- Added Kavrayski VII projection
- Added option to use an alternative shading scale for
m_shadedrelief
(so you can use bathmetry to addshading to surface temperature, for example) - Curved arrows in
m_vec
New in release 1.4n (Sep/2021)
- Created a separate
/data
directory for coastline databases (instead of defaulting them into/private
). - Updated OCTAVE compatability
New in release 1.4m (Feb/2020):
- Added cylindrical equal-area projection for completeness (don't recommend using it though!)
- Added
m_ginput
to assist in mouse-driven point selection. - Added date argument to
m_coord
so you can use the 13th IGRF model for geomagnetic coordinates at any date between 1900 and 1925. - Fixed bugs in
m_mag2geo
andm_geo2mag
that made them work incorrectly in some circ*mstances, and addeddocumentation about their use to the users guide. - Added
m_northarrow
to show the direction of north. - Added
m_windrose
to show wind rose diagrams on the map.
New in release 1.4k (Mar/2019):
- Finally - a way to handle pixellated data with
m_image
! - Checked in Octave up to v4.4.1
New in release 1.4j (May/2018):
- Shaded relief mapping with
m_shadedrelief
. - An independent grid for UTM maps with
m_utmgrid
New in release 1.4i (Jan/2018):
- Finally sorted out the major "2014b and later matlab graphics engine" related problems with
m_grid
, as well as manyminor graphics improvements. -
m_windbarb
andm_streamline
for meteorologists, alsom_scatter
. - A set of useful colourmaps in
m_colmap
, including a perceptually uniform "jet-like" colourmap. - A colourbar function
m_contfbar
made to work withcontourf
plots. -
m_annotation
andwysiwyg
to help you add arrows and things. - Updated the documentation so it doesn't have that "1990s" look.
- Added link to a Chinese translation of the Users Guide, as well as to the mapping GUI MAP-LAB which is built on top of M_Map.
- List of coded examples updated, and a few new ones added.
New in release 1.4h (Nov/2017) are
- ETOPO2v2 and ETOPO1 support.
- Handled some warnings about BITMAX that arise in Matlab 2014b. Note - I have only been able to fix or workaround SOME of the really bad bugs in 2014b. Use with caution (or better yet don't use). EPS output in particular is really awful, even if the screen plot looks "nice". Fortunately mathworks "may consider fixing this in future releases".
- Added option to output national+state or national borders only in
m_gshhs
.
New in release 1.4g (Jan/2014) are
m_ellipse.m
to plot tidal ellipses (say, from T_Tide )- Option to use either decimal-degrees or degrees/decimal-minutes in grid axis labels
- Matlab 2013b has a bad bug in the
dataaspectratio
axes property that affects pretty much everything graphical. This version of M_Map has a workaround that MOSTLY works, but it would be better to avoid using 2013b.
New in release 1.4f (May/2012) are
m_shaperead.m
to read SHAPEFILES! (so Natural Earth can be used for political boundaries instead of DCW, among other opportunities)- gshhs version 2 support
- partial OCTAVE compatibility
New in release 1.4e (May/2010)
- GSHHS Now comes with the WDB rivers and borders database, and links to them have been added via
m_gshhs.m
- Ellipsoidal Albers and Lambert conic projections included
New in release 1.4d (Oct/2007) are
- Modifications to work around bugs in matlab7
contourf
- Robinson projection
- A few compatibility issues with current matlab versions
- Upgraded hooks into some databases.
New in release 1.4b (Jun/2006) are
- m_hatch for hatched and speckled patches
- old-fashioned speckled coastlines (good for B&W pics - see Example 13).
- m_lldist now also returns points on great circle geodesics.
m_fdist, m_idist
, andm_geodesic
for geodesics on an ellipsoidalearth.
New in release 1.4 (Nov/2005) are
m_pcolor
m_coord
(to allow for geographic and geomagnetic coordinatesystems)- A very few minor bug fixes.
- Some hints about and examples of adding satellite image data toyour maps.
Example Code
1. M_Map Logo
m_proj('ortho','lat',48','long',-123');m_coast('patch','r');m_grid('linest','-','xticklabels',[],'yticklabels',[]);patch(.55*[-1 1 1 -1],.25*[-1 -1 1 1]-.55,'w'); text(0,-.55,'M\_Map','fontsize',25,'color','b',... 'verticalalignment','middle','horizontalalignment','center');
2. Lambert Conformal Conic projection of North American Topography
m_proj('lambert','long',[-160 -40],'lat',[30 80]);m_coast('patch',[1 .85 .7]);m_elev('contourf',[500:500:6000]);m_grid('box','fancy','tickdir','in');colormap(flipud(copper));
3. Stereographic projection of North Polar regions
% Note that coastline is drawn OVER the grid because of the order in which% the two routines are calledm_proj('stereographic','lat',90,'long',30,'radius',25);m_elev('contour',[-3500:1000:-500],'edgecolor','b');m_grid('xtick',12,'tickdir','out','ytick',[70 80],'linest','-');m_coast('patch',[.7 .7 .7],'edgecolor','r');
4. Two Interrupted Projections of the World's Oceans
subplot(211);Slongs=[-100 0;-75 25;0 45; 25 145;45 100;145 295;100 295];Slats= [ 8 80;-80 8; 8 80;-80 8; 8 80;-80 0; 0 80];for l=1:7 m_proj('sinusoidal','long',Slongs(l,:),'lat',Slats(l,:)); m_grid('fontsize',6,'xticklabels',[],'xtick',[-180:30:360],... 'ytick',[-80:20:80],'yticklabels',[],'linest','-','color',[.7 .7 .7]); m_coast('patch','g');endxlabel('Interrupted Sinusoidal Projection of World Oceans');% In order to see all the maps we must undo the axis limits set by m_grid calls:set(gca,'xlimmode','auto','ylimmode','auto');subplot(212);Slongs=[-100 43;-75 20; 20 145;43 100;145 295;100 295];Slats= [ 0 90;-90 0;-90 0; 0 90;-90 0; 0 90];for l=1:6 m_proj('mollweide','long',Slongs(l,:),'lat',Slats(l,:)); m_grid('fontsize',6,'xticklabels',[],'xtick',[-180:30:360],... 'ytick',[-80:20:80],'yticklabels',[],'linest','-','color','k') m_coast('patch',[.6 .6 .6]);endxlabel('Interrupted Mollweide Projection of World Oceans');set(gca,'xlimmode','auto','ylimmode','auto');
5. Oblique Mercator Projection with quiver and contour data
%% Nice looking data[lon,lat]=meshgrid([-136:2:-114],[36:2:54]);u=sin(lat/6);
v=sin(lon/6);m_proj('oblique','lat',[56 30],'lon',[-132 -120],'aspect',.8);subplot(121);m_coast('patch',[.9 .9 .9],'edgecolor','none');m_grid('tickdir','out','yaxislocation','right',... 'xaxislocation','top','xlabeldir','end','ticklen',.02);hold on;m_quiver(lon,lat,u,v);xlabel('Simulated surface winds');subplot(122);m_coast('patch',[.9 .9 .9],'edgecolor','none');
m_grid('tickdir','out','yticklabels',[],... 'xticklabels',[],'linestyle','none','ticklen',.02);hold on;[cs,h]=m_contour(lon,lat,sqrt(u.*u+v.*v));clabel(cs,h,'fontsize',8);xlabel('Simulated something else');
6. Miller Projection with Great Circle
% Plot a circular orbitlon=[-180:180];lat=atan(tan(60*pi/180)*cos((lon-30)*pi/180))*180/pi;m_proj('miller','lat',82);m_coast('color',[0 .6 0]);m_line(lon,lat,'linewi',3,'color','r');m_grid('linestyle','none','box','fancy','tickdir','out');m_northarrow(-150,0,40,'type',4,'linewi',.5);
7. Lambert Conformal Projection with high-resolution bathymetry of Western Mediterranean
m_proj('lambert','lon',[-10 20],'lat',[33 48]); [CS,CH]=m_etopo2('contourf',[-5000:500:0 250:250:3000],'edgecolor','none'); m_grid('linestyle','none','tickdir','out','linewidth',3);colormap([ m_colmap('blues',80); m_colmap('gland',48)]);brighten(.5);ax=m_contfbar(1,[.5 .8],CS,CH);title(ax,{'Level/m',''}); % Move up by inserting a blank line
8. Demonstration of fancy vectors
m_vec; % See code in m_vec.m for details
9. Zoom in on Prince Edward Island to show different coastline resolutions
% Example showing the default coastline and all of the different resolutions% of GSHHS coastlines as we zoom in on a section of Prince Edward Island. clf axes('position',[.35 .6 .37 .37]); m_proj('albers equal-area','lat',[40 60],'long',[-90 -50],'rect','on'); m_coast('patch',[0 1 0]); m_grid('linestyle','none','linewidth',2,'tickdir','out',... 'xaxisloc','top','yaxisloc','right','fontsize',6); m_text(-69,51,'Standard coastline','color','r','fontweight','bold'); m_ruler([.5 .9],.8,3,'fontsize',8) axes('position',[.09 .5 .37 .37]); m_proj('albers equal-area','lat',[40 54],'long',[-80 -55],'rect','on'); m_gshhs_c('patch',[.2 .8 .2]); m_grid('linestyle','none','linewidth',2,'tickdir','out',... 'xaxisloc','top','fontsize',6); m_text(-80,52.5,'GSHHS\_C (crude)','color','m','fontweight','bold'); m_ruler([.5 .9],.8,2,'fontsize',8); axes('position',[.13 .2 .37 .37]); m_proj('albers equal-area','lat',[43 48],'long',[-67 -58],'rect','on'); m_gshhs_l('patch',[.4 .6 .4]); m_grid('linestyle','none','linewidth',2,'tickdir','out','fontsize',6); m_text(-66.5,43.5,'GSHHS\_L (low)','color','m','fontweight','bold'); m_ruler([.5 .9],.8,3,'fontsize',8); axes('position',[.35 .05 .37 .37]); m_proj('albers equal-area','lat',[45.8 47.2],'long',[-64.5 -62],'rect','on'); m_gshhs_i('patch',[.5 .6 .5]); m_grid('linestyle','none','linewidth',2,'tickdir','out',... 'yaxisloc','right','fontsize',6); m_text(-64.4,45.9,'GSHHS\_I (intermediate) ','color','m',... 'fontweight','bold','horizontalalignment','right'); m_ruler([.5 .8],.1,3,'fontsize',8); axes('position',[.5 .1 .37 .37]); m_proj('albers equal-area','lat',[46.375 46.6],'long',[-64.2 -63.7],'rect','on'); m_gshhs_h('patch',[.6 .7 .6]); m_grid('linestyle','none','linewidth',2,'tickdir','out',... 'xaxisloc','top','yaxisloc','right','fontsize',6); m_text(-64.18,46.4,'GSHHS\_H (high)','color','m','fontweight','bold'); m_ruler([.5 .8],.2,3,'fontsize',8); axes('position',[.55 .35 .37 .37]); m_proj('albers equal-area','lat',[46.55 46.65],'long',[-63.97 -63.77],'rect','on'); m_gshhs_f('patch',[.7 .9 .7]); m_grid('linestyle','none','linewidth',2,'tickdir','out',... 'xaxisloc','top','yaxisloc','right','fontsize',6); m_text(-63.95,46.56,'GSHHS\_F (full)','color','m','fontweight','bold'); m_ruler([.5 .8],.2,3,'fontsize',8);
10. Tracklines and UTM projection
m_proj('UTM','long',[-72 -68],'lat',[40 44]); m_gshhs_i('color','k'); m_grid('box','fancy','tickdir','in'); m_ruler(1.2,[.5 .8]); % fake up a trackline lons=[-71:.1:-67]; lats=60*cos((lons+115)*pi/180); dates=datenum(1997,10,23,15,1:41,zeros(1,41)); m_track(lons,lats,dates,'ticks',0,'times',4,'dates',8,... 'clip','off','color','r','orient','upright'); m_northarrow(-68.5,43.4,.4,'type',2);
11. Range rings
m_proj('hammer','clong',170);m_grid('xtick',[],'ytick',[],'linestyle','-');m_coast('patch','g');m_line(100.5,13.5,'marker','square','color','r');m_range_ring(100.5,13.5,[1000:1000:15000],'color','b','linewi',2);xlabel('1000km range rings from Bangkok');
12. Speckled boundary
bndry_lon=[-128.8 -128.8 -128.3 -128 -126.8 -126.6 -128.8]; bndry_lat=[49 50.33 50.33 50 49.5 49 49]; clf; m_proj('lambert','long',[-130 -121.5],'lat',[47 51.5],'rectbox','on'); m_gshhs_i('color','k'); % Coastline... m_gshhs_i('speckle','color','k'); % with speckle added m_line(bndry_lon,bndry_lat,'linewi',2,'color','k'); % Area outline ... m_hatch(bndry_lon,bndry_lat,'single',30,5,'color','k'); % ...with hatching added. m_grid('linewi',2,'linest','none','tickdir','out','fontsize',12); title({'Speckled Boundaries','for nice B&W presentation','(best in postscript format)'}); m_text(-128,48,{'Pacific','Ocean'},'fontsize',18); m_northarrow(-122.5,50.2,.8,'type',3,'linewi',2);
13. Blue Ocean
m_proj('miller','lat',[-77 77]); m_coast('patch',[.7 1 .7],'edgecolor','none'); m_grid('box','fancy','linestyle','-','gridcolor','w','backcolor',[.2 .65 1]); cities={'Cairo','Washington','Buenos Aires'}; lons=[ 30+2/60 -77-2/60 -58-22/60]; lats=[ 31+21/60 38+53/60 -34-45/60]; for k=1:3 [range,ln,lt]=m_lldist([-123-6/60 lons(k)],[49+13/60 lats(k)],40); m_line(ln,lt,'color','r','linewi',2); m_text(ln(end),lt(end),sprintf('%s - %d km',cities{k},round(range))); end; title('Great Circle Routes','fontsize',14,'fontweight','bold'); set(gcf,'color','w'); % Need to do this otherwise 'print' turns the lakes black
14. One Ocean Projection
% This projection shows all the oceans connected to each other - the outside ring % is the Asian coastline (Thanks to M B-O for this idea) % otherwise its just an example of different map types. m_proj('azimuthal equal-area','radius',156,'lat',-46,'long',-95,'rot',30); ax1=subplot(2,2,1,'align'); m_coast('patch','r'); m_grid('xticklabel',[],'yticklabel',[],'linestyle','-','ytick',[-60:30:60]); ax2=subplot(2,2,2,'align'); m_elev('contourf',[-7000:1000:0 500:500:3000],'edgecolor','none'); colormap(ax2,[m_colmap('blues',70);m_colmap('gland',30)]); caxis(ax2,[-7000 3000]); m_grid('xticklabel',[],'yticklabel',[],'linestyle','-','ytick',[-60:30:60]); ax3=subplot(2,2,3,'align'); colormap(ax3,[m_colmap('blues',70);m_colmap('gland',30)]); caxis(ax3,[-7000 3000]); m_elev('image'); m_grid('xticklabel',[],'yticklabel',[],'linestyle','-','ytick',[-60:30:60]); ax4=subplot(2,2,4,'align'); colormap(ax4,[m_colmap('blues')]); caxis(ax4,[-8000 000]); m_elev('shadedrelief','gradient',.5); m_coast('patch',[.7 .7 .7],'edgecolor','none'); m_grid('xticklabel',[],'yticklabel',[],'linestyle','-','ytick',[-60:30:60]); ha = axes('Position',[0 0 1 1],'Xlim',[0 1],'Ylim',[0 1],'Box','off',... 'Visible','off','Units','normalized', 'clipping' , 'off'); text(0.5, 0.98,'This projection shows all oceans connected to each other',... 'horiz','center','fontsize',20);
15. Stepped jet colormap
% get delta-SA data from the TEOS-10 gsw atlas at 2500 dbar [LG,LT]=meshgrid(0:360,-86:89); dSA=ones(size(LG)); dSA(:)=gsw_deltaSA_atlas(3000*dSA(:),LG(:),LT(:)); % Rearrange data to lie in the longitude limits I give for the % projection ind=[31:361 1:30]; % Move left side to right dSA=dSA(:,ind); LT=LT(:,ind); LG=LG(:,ind);LG(LG>30)=LG(LG>30)-360; %...and subtract 360 to some longitudes clf; m_proj('robinson','lon',[-330 30]); m_pcolor(LG,LT,dSA*1000); m_coast('patch',[.7 .7 .7],'edgecolor','none'); m_grid('tickdir','out','linewi',2); % This is a perceptually uniform jet-like color scale, but in m_colmap % we can add some simple graduated steps to make the pcolor look a little % more like a contourf colormap(m_colmap('jet','step',10)); h=colorbar('northoutside'); title(h,'\deltaSA/(g/kg) at 2000 dbar','fontsize',14); set(h,'pos',get(h,'pos')+[.2 .05 -.4 0],'tickdir','out') set(gcf,'color','w'); % Need to do this otherwise 'print' turns the lakes black
16. Bathymetry
load /ocean/rich/home/dens14/VENTSlp=load('/ocean/rich/home/dens14/Linep_201402'); m_proj('lambert','long',[-160 -115],'lat',[32 60]);[CS,CH]=m_etopo2('contourf',[-7000:1000:-1000 -500 -200 0 ],'edgecolor','none');m_gshhs_f('patch',[.7 .7 .7],'edgecolor','none');h1=m_line(vents.lon,vents.lat,'marker','s','color',[0 .5 0],... 'linest','none','markerfacecolor','w','clip','point');h2=m_line(lp.POS(:,2),lp.POS(:,1),'marker','o','color','r','linewi',2,... 'linest','none','markersize',8,'markerfacecolor','w');m_grid('linest','none','tickdir','out','box','fancy','fontsize',16);legend([h1(1),h2(1)],'Known Hydrothermal vents','Line-P Stations','location','southwest');colormap(m_colmap('blues')); caxis([-7000 000]);[ax,h]=m_contfbar([.55 .75],.8,CS,CH,'endpiece','no','axfrac',.05);title(ax,'meters')set(gcf,'color','w'); % otherwise 'print' turns lakes black
17. Shaded Relief (Example 1)
m_proj('lambert','lat',[5 24],'long',[105 125]);set(gcf,'color','w') % Set background colour before m_image callcaxis([-6000 0]);colormap(flipud([flipud(m_colmap('blues',10));m_colmap('jet',118)]));m_etopo2('shadedrelief','gradient',3); m_gshhs_i('patch',[.8 .8 .8]); m_grid('box','fancy');ax=m_contfbar(.97,[.5 .9],[-6000 0],[-6000:100:000],'edgecolor','none','endpiece','no');xlabel(ax,'meters','color','k');
18. Shaded Relief (Example 2)
m_proj('utm','ellipse','grs80','zone',10,'lat',[49+15.7/60 49+21/60],... 'long',[-123-15/60 -123-3/60]); % Uses multibeam bathymetry with 10m horizontal resolution% Already regularly gridded in UTM coords with vector x2/y2, and% matrix Z2.caxis([-150 0]);colormap([m_colmap('water',128)]);m_shadedrelief(x2,y2,-Z2,'lightangle',-45,'gradient',8,'coord','z');% Add some contourshold on;[cs,h]=contour(x2,y2,Z2,[0:20:150],'color','k');clabel(cs,h,'fontsize',6);hold off;% Land parts from a previously saved high-resolution coastlinecol=[255 214 140]/255; % CHS chart land colourm_usercoast('/ocean/rich/more/mmapbase/bcgeo/PNW.mat','patch',col);m_usercoast('/ocean/rich/more/mmapbase/bcgeo/PNWrivers.mat','patch',col);% Lat/long AND a UTM grid m_grid('tickdir','out','fontsize',12,'linest','none','xaxisloc','top','yaxisloc','right');m_utmgrid('xcolor','b','ycolor','b','linest','-'); m_ruler([.5 .8],.9,'tickdir','out','ticklen',[.007 .007]);m_northarrow(-123-4.5/60,49+19.5/60,1/60,'type',4,'aspect',1.5);xlabel('Vancouver Harbour','color','k');
19. Wind Roses
clf;set(gcf,'color','w'); m_proj('oblique','lon',[-125.3 -122.6],'lat',[50.1 48.6] ,'dir','vert','aspect',0.45)% Database 1 coastlinem_usercoast('/ocean/rich/more/mmapbase/bcgeo/PNW.mat',... 'patch',[.8 .8 .8],'edgecolor','k');% Database 2 riverm_usercoast('/ocean/rich/more/mmapbase/bcgeo/PNWrivers.mat',... 'patch',[.8 .8 .8],'edgecolor','k');% Elevation database in structure SOGbathhold on; m_contourf(SOGbath.lon,SOGbath.lat,SOGbath.Z,[500 500],... 'edgecolor','none','facecolor',[.7 .7 .7]); hold off;m_grid('linewi',2,'tickdir','out','ticklen',.03,'linestyl','none','color','k');m_northarrow(-125.4,49.7,.2,'type',2);title({'Winter','ONDJFM',' '},'fontsize',14);% Wind data in struct arrays - pass each parameter to M_WINDROSE as a 1xN % cell array of data in the order you want them plotted (ones on top later% in list)levels=[0:4:24]; % Binning for speedsk=[1 15 18 6 3 19 4 5 7 8 10 9 11 12 2 13 14 16 17 ]; % change order to % make overlaps look nicerm_windrose({Winter(k).lon},{Winter(k).lat},{Winter(k).wdir},{Winter(k).wspd},... 'size',.17,'nspeed',levels,'alpha',1);colormap(m_colmap('jet'));caxis([0 24]);axb=m_contfbar(.8,[.6 .9],levels,levels);axb.YLabel.String='Wind speeds m/s';axb.YTick=levels;
20. Colourmaps
% This command generates the figure % In each subplot title is the M_COLMAP call that % generated the colourmap displayed. % % Uses of these colourmaps can be seen % in other maps in this gallery. m_colmap demo
Examples of satellite data manipulation
1. Global SST (or any variable on a global Lat/Long grid)
% NOAA/NASA Pathfinder AVHRR SST product % https://podaac.jpl.nasa.gov/sst/ [P,map]=imread('../m_mapWK/199911h54ma-gdm.hdf'); % Documentation for the 54km dataset gives % this formula for temperature P=0.15*double(P)-3; % deg C %...and defines this Lat/Long grid for the data Plat=90-.25-[0:359]*.5;Plon=-180+.25+[0:719]*.5; % Since the grid is rectangular in lat/long (i.e. not % really a projection at all, although it is included in % m_map under the name 'equidistant cyldindrical'), we % don't want to use the 'image' technique. Instead... % Create a grid, offsetting by half a grid point to account % for the flat pcolor [Plg,Plt]=meshgrid(Plon-0.25,Plat+0.25); m_proj('hammer-aitoff','clongitude',-150); % Rather than rearranging the data so its limits match the % plot I just draw it twice (you can see the join at 180W % because of the quirks of flat pcolor) (Note that % all the global projections have 360 deg ambiguities) m_pcolor(Plg,Plt,P);shading flat;colormap(map); hold on; m_pcolor(Plg-360,Plt,P);shading flat;colormap(map); m_coast('patch',[.6 1 .6]); m_grid('xaxis','middle'); % add a standard colorbar. h=colorbar('h'); set(get(h,'xlabel'),'string','AVHRR SST Nov 1999');
2. SSM/I Ice cover (data provided on a fixed grid) (HDF format)
%Near-Real-Time SSM/I-SSMIS EASE-Grid Daily Global Ice Concentration and % Snow Extent, Version 5%% Brodzik, M. J. and J. S. Stewart. 2016. Near-Real-Time SSM/I-SSMIS EASE-Grid % Daily Global Ice Concentration and Snow Extent, Version 5. Boulder, Colorado % USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. % doi: https://dx.doi.org/10.5067/3KB2JPLFPK3R.Q=hdfinfo('NISE_SSMISF18_20171124.HDFEOS')% Q.Attributes(2).Value says% UpperLeftPointMtrs=(-9036842.762500,9036842.762500)% LowerRightMtrs=(9036842.762500,-9036842.762500)% ProjParams=(6371228,0,0,0,0,90000000,0,0,0,0,0,0,0)% and% Q.Attributes(3).Value says% 'Data Value Parameter% 0 snow-free land% 1-100 sea ice concentration percentage% 101 permanent ice (Greenland, Antarctica)% 102 not used% 103 dry snow% 104 wet snow% 105-251 not used% 252 mixed pixels at coastlines (unable to reliably apply microwave algorithm)% 253 suspect ice value% 254 corners(undefined)% 255 oceanP=hdfread('NISE_SSMISF18_20171124.HDFEOS','Northern Hemisphere','fields','Extent');P(P==255)=105; % Put ocean at top of indicesP(P>105)=0;% According to web site this is is the projection info. I make te radius% of my map less than the actual data field though.m_proj('azimuthal equal-area','latitude',90,'radius',47,'rectbox','on'); clf% Plot data as an imageoffs=9036842.762500/6371228; % Convert projection coords to units of earth radiiimage([-offs offs],[offs -offs],P); set(gca,'ydir','normal');colormap([.2 .5 .2; % 0 jet(100); % 1-100 1 1 1; % Greenland 0 0 0 ; .9 .9 .9; % dry snow .8 .8 .8; % wet snow 0 0 .5]); % 105 - now oceancaxis([0 105]);m_coast('color','k');m_grid('linewi',2,'tickdir','out');title({'SSM/I Ice cover Nov 24, 2017',''},'fontsize',14,'fontweight','bold');hh=colorbar('h');set(hh,'tickdir','out');xlabel(hh,'% Ice cover');
3. Aerial photos on an UTM grid
% This image comes from the TerraServer % (http://terraserver.microsoft.com/ - now greatly altered) % and has been georeferenced to UTM coords. The UTM projection % uses UTM coordinates on the screen (as long as the ellipse % parameter is set to something other than the default), [P,map]=imread('../m_mapWK/oncehome.jpeg'); % Set the projection limits to the lat/long of image % corners. m_proj('UTM','long',[-71-6/60-30/3600 -71-4/60-43/3600],... 'lat',[42+21/60+13/3600 42+22/60+7/3600],'ellipse','wgs84'); clf; image([326400 328800],[4692800 4691200],P);set(gca,'ydir','normal'); m_grid('tickdir','out','linewi',2,'fontsize',14); title('A home for certain nerds','fontsize',16);
4. A subset of a global dataset (HDF format)
% Ocean colour data from http://seawifs.gsfc.nasa.gov/SEAWIFS.html % % Take a 4km weakly average dataset and plot a map for the Strait of % Georgia and outer coast. Note that most of this code is used % for reading in and subsetting the data. LATLIMS=[47 51]; LONLIMS=[-130 -121]; % Note - This is probably not the most efficient way to read and % handle HDF data, but I don't usually do this... % % First, get the attribute data PI=hdfinfo('../m_mapWK/A20040972004104.L3m_8D_CHLO_4KM'); % And write it into a structure pin=[]; for k=1:59 nm=PI.Attributes(k).Name;nm(nm==' ')='_'; if isstr(PI.Attributes(k).Value), pin=setfield(pin,nm,PI.Attributes(k).Value); else pin=setfield(pin,nm,double(PI.Attributes(k).Value)); end end; % lon/lat of grid corners lon=[pin.Westernmost_Longitude:pin.Longitude_Step:pin.Easternmost_Longitude]; lat=[pin.Northernmost_Latitude:-pin.Latitude_Step:pin.Southernmost_Latitude]; % Get the indices needed for the area of interest [mn,ilt]=min(abs(lat-max(LATLIMS))); [mn,ilg]=min(abs(lon-min(LONLIMS))); ltlm=fix(diff(LATLIMS)/pin.Latitude_Step); lglm=fix(diff(LONLIMS)/pin.Longitude_Step); % load the subset of data needed for the map limits given P=hdfread('../m_map/WKA20040972004104.L3m_8D_CHLO_4KM','l3m_data',... 'Index',{[ilt ilg],[],[ltlm lglm]}); % Convert data into log(Chla) using the equations given. Blank no-data. P=double(P); P(P==255)=NaN; P=(pin.Slope*P+pin.Intercept); % log_10 of chla LT=lat(ilt+[0:ltlm-1]);LG=lon(ilg+[0:lglm-1]); [Plg,Plt]=meshgrid(LG,LT); % FINALLY....Draw the map... clf; m_proj('lambert','lon',LONLIMS,'lat',LATLIMS); m_pcolor(Plg,Plt,P);shading flat; m_gshhs_i('color','k');; m_grid('linewi',2,'tickdir','out');; h=colorbar; set(get(h,'ylabel'),'String','Chla (\mug/l)'); set(h,'ytick',log10([.5 1 2 3 5 10 20 30]),'yticklabel',[.5 1 2 3 5 10 20 30],... 'tickdir','out'); title(['MODIS Chla ' ... datestr(datenum(pin.Period_Start_Year,1,0)+pin.Period_Start_Day) ... ' -> ' ... datestr(datenum(pin.Period_Start_Year,1,0)+pin.Period_End_Day) ],... 'fontsize',14,'fontweight','bold');
5. Meteorological data (netCDF format)
iday=156; % the day to show% use ncdisp(filename) to discover file contents...lat=ncread('uwnd.10m.gauss.2017.nc','lat');lon=ncread('uwnd.10m.gauss.2017.nc','lon');[LN,LT]=meshgrid(lon,lat);mtime=ncread('uwnd.10m.gauss.2017.nc','time')/24+datenum(1800,1,1,0,0,0);u=ncread('uwnd.10m.gauss.2017.nc','uwnd',[1,1,iday],[192,94,1]);v=ncread('vwnd.10m.gauss.2017.nc','vwnd',[1,1,iday],[192,94,1]);prate=ncread('prate.sfc.gauss.2017.nc','prate',[1,1,iday],[192,94,1]);m_proj('miller','lon',[100 260],'lat',[0 65]);m_coast('patch',[.8 .8 .8]);hold on [CS,CH]=m_contourf(LN,LT,prate'*1e3,[0.05:.05:.7],'edgecolor','none');m_windbarb(LN,LT,u' ,v',2,'units','m/s','linewi',1,'color','r');hold off;m_grid('box','fancy','tickdir','out');ax=m_contfbar([.3 .7],.05,CS,CH);set(ax,'fontsize',12)xlabel(ax,'Mean Daily Precipitation Rate/(kg/m^2/s)');title(['North Pacific Surface Winds : ' datestr(mtime(iday))],'fontsize',16);colormap(flipud(m_colmap('Blues')))
6. ARGO drifter tracks (netCDF format)
% Argo stuff% Go to:% https://www.usgodae.org/cgi-bin/argo_select.pl% Select area you want and date range, download all profiles% tar -xvzf them into directory...basname='./argo';% base mapm_proj('lambert','lons',[-150 -124],'lat',[40 60],'rectbox','on');[cs,h]=m_etopo2('contourf',[-7000:500:0],'edgecolor','none');m_gshhs_l('patch',[.5 .8 0],'edgecolor','none');m_grid('linewi',2,'layer','top');caxis([-7000 000]);m_contfbar(.92,[.2 .5],cs,h,'endpiece','no','axfrac',.02);colormap(m_colmap('blue')); title('Argo float trajectories NE Pacific (2017)');% Add ARGO float trajectories% 1) draw a scale arrowvecscl=0.015;m_vec(vecscl ,-126,58,-0.01,0,'r','shaftwidth',2,'headlength',10,... 'key',{'1 cm/s','Mean Drift'},'centered','yes'); dirs=dir(basname);m=0;for k=3:length(dirs) profname=dir([dirs(k).folder '/' dirs(k).name]); for l=3:length(profname) fname=[profname(l).folder '/' profname(l).name '/' profname(l).name '_Rtraj.nc']; %ncdisp(fname); argo.id=ncread(fname,'PLATFORM_NUMBER'); argo.mtime=ncread(fname,'JULD')+datenum(1950,1,1); argo.lat=ncread(fname,'LATITUDE'); argo.lon=ncread(fname,'LONGITUDE'); % Long are stored between -180 and +180; this removes artificial % jumps which might happen just left of the map limits. argo.lon(argo.lon>0)=argo.lon(argo.lon>0)-360; ii=find(isfinite(argo.lon)); if any(ii ) m_line(argo.lon(ii),argo.lat(ii),'color',[0 0 0]); % Sometimes first point is an error of some sort so skip it Dlon=argo.lon(ii([2 end])); Dlat=argo.lat(ii([2 end])); t=diff(argo.mtime(ii([2 end]))); % time between the points % Distance between the points [d,a12]=m_idist(Dlon(1),Dlat(1),Dlon(2),Dlat(2)); % Store stuff m=m+1; spd(m)=d/(t*86400) ;% m/s % Find midpoint on geodesic and store as well [Clon(m),Clat(m),a21(m)]=m_fdist(Dlon(1),Dlat(1),a12,d/2); end end endClon=rem(Clon-360,360); % Get it into the right rangea21=rem(a21-180,360); % I need the opposite direction% Draw all the 'mean speed' arrows, centered at the midpoint of the% geodesic between first and last points.m_vec(vecscl ,Clon,Clat,spd.*sind(a21),spd.*cosd(a21),'r',... 'centered','yes','shaftwidth',2,'headlength',10);
7. SAR image of internal waves (HDF-5 format)
fname='SAR_IMP_1PNESA19920724_190439_00000018C086_00199_05354_0000.h5';%h5disp(fname) % See the structuretitlestr=h5readatt(fname,'/metadata/MPH','STATE_VECTOR_TIME');datsize=double([ h5readatt(fname,'/bands/Amplitude','raster_width') ... h5readatt(fname,'/bands/Amplitude','raster_height')]);tielat=h5read(fname,'/tie_point_grids/latitude');tielon=h5read(fname,'/tie_point_grids/longitude');stp=[h5readatt(fname,'/tie_point_grids/latitude','sub_sampling_x') ... h5readatt(fname,'/tie_point_grids/latitude','sub_sampling_y') ];% Pull out a subsection in by [2000 2500] from one corner and in % [600 2000] from the opposite corneristart=[2000 2500];strd=[3 3];cnt=fix([(datsize(1)-istart(1)-600)/strd(1) (datsize(2)-istart(2)-2000)/strd(2)]);% ...and read.subimg=h5read(fname,'/bands/Amplitude',istart,cnt,strd);% ....smooth it a bit...subf=filter2(ones(3,3)/9,subimg);% Now generate lat/lon for all pixels by interpolating from% the tie points.Ty=[0:size(tielat,2)-1]*stp(2)+1;Tx=[0:size(tielat,1)-1]*stp(1)+1;Iy=istart(2)+[0:size(subimg,2)-1]*strd(2);Ix=istart(1)+[0:size(subimg,1)-1]*strd(1);sublat=interp2(Ty',Tx,tielat,Iy',Ix);sublon=interp2(Ty',Tx,tielon,Iy',Ix);% Now make the mapm_proj('lambert','lon',[-123-25/60 -122-40/60],'lat',[48+42/60 49+9/60]);m_pcolor(sublon,sublat,subf);shading flat;m_grid('box','fancy','tickdir','out');m_ruler(1.03,[.15 .5],'ticklen',[.01]);caxis([0 450]);colormap(gray);title(titlestr)
8. Shaded Relief from a high-resolution topography (netCDF format)
clat=[48+46/60 49+5/60];clon=[-125-15/60 -124-55/60]; % Barkley Sound%% Read data from a netcdf filefname='/ocean/rich/more/mmapbase/noaa_bc3/barkley_sound_1_navd88_2016.nc';lat=ncread(fname,'lat');lon=ncread(fname,'lon');ilat=lat>=clat(1) & lat<=clat(2);ilon=lon>=clon(1) & lon<=clon(2);Z=ncread(fname,'Band1',[ find((ilon),1,'first') find((ilat),1,'first')],... [ sum(ilon) sum(ilat)],[1 1]);m_proj('equidistant','lon',clon,'lat',clat); % Projection% The shaded relief version (right hand plot))subplot(1,2,2);caxis([-300 1210]); % 1210 chosen by manual adjustment % since 'waterline" appears to be at about Z=2 (vertical datum for % bathymetry is 'lowest normal tide')colormap([m_colmap('blues',32);m_colmap('gland',128)]); % Colormap sizes chosen because... % ... 32/128 = (300+2)/(1210-2)m_shadedrelief(lon(ilon),lat(ilat),Z'); m_grid('box','fancy','grid','none','fontsize',14);m_contfbar( [.3 .7],.98, Z',[-300:1210],... 'axfrac',.02,'endpiece','no','levels','match','edgecolor','none'); % The normal contour version (left hand plot))subplot(1,2,1);m_contourf(lon(ilon),lat(ilat),Z',[-300:25:-25 2 50:50:200 300:100:1200 1210]);caxis([-300 1210]); colormap([m_colmap('blues',32);m_colmap('gland',128)]);m_grid('box','fancy','tickdir','out','grid','none','fontsize',14);m_contfbar( [.3 .7],.98, Z',[-300:25:-25 2 50:50:200 300:100:1200 1210],... 'axfrac',.02,'endpiece','no','levels','match');
9. Google Maps Static API
% Axis limits lms=[ -123-[14 8]/60 49+[10 13.5]/60 ]; % plot_google_maps.m from the mathworks user contributed files database:% https://www.mathworks.com/matlabcentral/fileexchange/27627-zoharby-plot_google_map% accesses the static google maps map tiles, returning a lat/long gridded% image that is just bigger than the given limits.clf;axis(lms);[Glon,Glat,Gimg]=plot_google_map('maptype','satellite','refresh',0,'autoaxis',0);clf;% Now draw it! m_proj('utm','lat',lms(3:4),'lon',lms(1:2));m_image(Glon,Glat,Gimg); m_grid('tickdir','out','box','fancy');m_ruler([.4 .9],1.05,6,'tickdir','in','ticklen',.01);
Citation
If you decide that M_Map made a significant contribution to a project, and you want acknowledge that contribution with a citation (thanks!), I recommend something like the following:
- Pawlowicz, R., 2020. "M_Map: A mapping package for MATLAB", version 1.4m, [Computer software], available online at www.eoas.ubc.ca/~rich/map.html.
Acknowledgements
A number of people have helped out with suggestions, code fixes,etc. I am especially grateful for the work done by E. Firing, D.Byrne, M. Mann, J. Pringle, J. E. Nilsen, M.Halverson, Jamie Tsoa, Shi Weiheng, and W. Brown who have allcontributed code.