Convert Matrix to ArcGIS raster

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Diego Fonseca
Diego Fonseca 2020-5-31
回答： Robert Daly 2022-11-30
Hello Everybody,
I am working in a project, where a team is generating simulations with a model and exporting results in .mat files (x, y, z). I need to plot the results with ArcGIS (only ploting without doing further interpolations or operations, just setting colors and legend).
The problem is I need to generate a raster in matlab so ArcGIS can read it. If I only import x,y,z points into ArcGIS I will need to create a shapefile with them and interpolate it to generate a raster, which is not the best option, as it can differ from Matlab results (interpolation method etc).
So, anyone could help me converting a mx3 matlab variable (containing x, y coordinates in WGS84) and a variable z into a raster so I can read it directly into ArcGIS as a raster file?
Thanks in advance.
Best regards,
Diego

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KSSV
KSSV 2020-5-31
It depends whether your data is structured or unstructured. Based on the data, the folloiwng is the procedure. Let A be your (x,y,z) data.
x = A(:,1) ; y = A(:,2) ; z = A(:,3) ;
%%structured
xi = unique(x) ; yi = unique(y) ;
[X,Y] = meshgrid(xi,yi) ;
Z = reshape(z,size(X)) ;
figure
surf(X,Y,Z)
%%unstructured
Z = griddata(x,y,z,X,Y) ;
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KSSV
KSSV 2020-6-8
编辑：KSSV 2020-6-8
WGS84 means UTM coordinates?
Just use
ncwrite(file,'z',Z) ; % write 2D data
Diego Fonseca
Diego Fonseca 2020-6-8
No, UTM is the projection, WGS 84 is the datum for geographic coordinates. However, this is not a major issue, as I can project the netcdf in arcgis (it was just to speed up the process).

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Robert Daly
Robert Daly 2022-11-30
Following on from KSSV in the comments...
You can export the data to a netCDF file then import that in ArcGIS.
To define the coordinate system for ArcGIS you need to add a bunch of attributes to the variables.
To work out the important attributes I exported a source raster to netCDF using "Multidimension tools>Raster to NetCDF"
Then in matlab use
ncdisp('export.nc')
to read the attributes.
The "esri_pe_string" attribute value is important according to this article Stackexchange
I got the string from the exported example.
% nc filename to be written
file = 'test.nc' ;
% create test dataset
Z=rand(10,10);
x = [2.2493e+05:2.2493e+05+10]
y = [6.1817e+06:6.1817e+06+10]
[x,y]=meshgrid(x,y)
% Write X and Y variables
% Get data
X = x(1,:) ;
Y = y(:,1) ;
%% Define data dimensions and write data
nccreate(file,'x','Dimensions',{'x',1,length(X)},'DeflateLevel',5) ;
ncwrite(file,'x',X) ;
nccreate(file,'y','Dimensions',{'y',1,length(Y)},'DeflateLevel',5) ;
ncwrite(file,'y',Y) ;
nccreate(file,'z','Dimensions',{'x','y'},'DeflateLevel',5) ;
ncwrite(file,'z',Z',[1,1]) ; % write 2D data
nccreate(file,'transverse_mercator','Dimensions',{'transverse_mercator',1,Inf},'DeflateLevel',5) ;
% Add projection attributes for ArcGIS
ncid = netcdf.open(file,'WRITE')
netcdf.reDef(ncid);
netcdf.putAtt(ncid,0,'units','Meter')
netcdf.putAtt(ncid,0,'long_name', 'Easting')
netcdf.putAtt(ncid,0,'standard_name','projection_x_coordinate')
netcdf.putAtt(ncid,0,'axis','X')
netcdf.putAtt(ncid,1,'units','Meter')
netcdf.putAtt(ncid,1,'long_name', 'Northing')
netcdf.putAtt(ncid,1,'standard_name','projection_y_coordinate')
netcdf.putAtt(ncid,1,'axis','Y')
netcdf.putAtt(ncid,2,'long_name','Habitat Suitability Index')
netcdf.putAtt(ncid,2,'standard_name','HSI')
netcdf.putAtt(ncid,2,'esri_pe_string','PROJCS["GDA2020_MGA_Zone_54",GEOGCS["GDA2020",DATUM["GDA2020",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",10000000.0],PARAMETER["Central_Meridian",141.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]')
netcdf.putAtt(ncid,2,'coordinates','x y')
netcdf.putAtt(ncid,2,'grid_mapping','transverse_mercator')
netcdf.putAtt(ncid,3,'grid_mapping_name','transverse_mercator')
netcdf.putAtt(ncid,3,'longitude_of_central_meridian',141)
netcdf.putAtt(ncid,3,'latitude_of_projection_origin',0)
netcdf.putAtt(ncid,3,'scale_factor_at_central_meridian',0.9996)
netcdf.putAtt(ncid,3,'false_easting',500000)
netcdf.putAtt(ncid,3,'false_northing',10000000)
netcdf.close(ncid)

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